Next Article in Journal
Association of CD206 Protein Expression with Immune Infiltration and Prognosis in Patients with Triple-Negative Breast Cancer
Next Article in Special Issue
Involvement of HHV-4 (Epstein–Barr Virus) and HHV-5 (Cytomegalovirus) in Inflammatory Bowel Disease and Colorectal Cancer: A Meta-Analysis
Previous Article in Journal
Validation of MRI-Based Models to Predict MGMT Promoter Methylation in Gliomas: BraTS 2021 Radiogenomics Challenge
Previous Article in Special Issue
Inflammation- and Metastasis-Related Proteins Expression Changes in Early Stages in Tumor and Non-Tumor Adjacent Tissues of Colorectal Cancer Samples
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Biomarkers in Metastatic Colorectal Cancer: Status Quo and Future Perspective

by
Alberto Puccini
1,2,†,
Andreas Seeber
3,† and
Martin D. Berger
4,*
1
Medical Oncology Unit 1, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
2
Department of Internal Medicine and Medical Specialties (DIMI), School of Medicine, University of Genoa, 16132 Genoa, Italy
3
Department of Hematology and Oncology, Comprehensive Cancer Center Innsbruck, Medical University of Innsbruck, 6020 Innsbruck, Austria
4
Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Cancers 2022, 14(19), 4828; https://doi.org/10.3390/cancers14194828
Submission received: 22 August 2022 / Revised: 20 September 2022 / Accepted: 28 September 2022 / Published: 3 October 2022
(This article belongs to the Special Issue Biomarker in Metastatic Colorectal Cancer)

Abstract

:

Simple Summary

Despite recent progress in the treatment of metastatic colorectal cancer patients, novel therapeutic approaches are highly warranted to further improve outcome. Additionally, it is of utmost importance to define subgroups of patients who may derive the most benefit from a specific treatment, as we are moving forward in the field of personalized medicine. This review provides an overview about established biomarkers helping us to better guide treatment. Moreover, we report on emerging and potential promising biomarkers having the potential to be implemented into clinical practice in the near future.

Abstract

Colorectal cancer (CRC) is the third most frequent cancer worldwide, and its incidence is steadily increasing. During the last two decades, a tremendous improvement in outcome has been achieved, mainly due to the introduction of novel drugs, targeted treatment, immune checkpoint inhibitors (CPIs) and biomarker-driven patient selection. Moreover, progress in molecular diagnostics but also improvement in surgical techniques and local ablative treatments significantly contributed to this success. However, novel therapeutic approaches are needed to further improve outcome in patients diagnosed with metastatic CRC. Besides the established biomarkers for mCRC, such as microsatellite instability (MSI) or mismatch repair deficiency (dMMR), RAS/BRAF, sidedness and HER2 amplification, new biomarkers have to be identified to better select patients who derive the most benefit from a specific treatment. In this review, we provide an overview about therapeutic relevant and established biomarkers but also shed light on potential promising markers that may help us to better tailor therapy to the individual mCRC patient in the near future.

1. Introduction

Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, and its global incidence is continuously increasing [1]. Thus, the global burden of CRC will pose significant challenges to the health care system due to increasing financial costs [2]. Whereas the median overall survival (mOS) of patients with metastatic CRC (mCRC) did not exceed 6 months in the eighties, nowadays the median survival reaches almost 30 months [3,4]. The implementation of upfront antiangiogenic agents in right-sided RAS wild-type mCRC, the addition of anti-epithelial growth factor receptor (EGFR) antibodies in left-sided RAS wild-type mCRC, and the introduction of tyrosine kinase inhibitors and further chemotherapeutics have led to a significant improvement in prognosis over time [5,6,7,8]. Certainly, the establishment of interdisciplinary tumor boards, advances in surgical techniques and local ablative and stereotactic procedures, especially in oligometastatic disease, have further contributed to this successful development [9]. Additionally, CPIs have significantly improved OS in approximately 3–5% of mCRC patients harboring microsatellite instable (MSI) or mismatch repair-deficient (dMMR) tumors [10]. Patients harboring a BRAFV600E mutation (8–15%) undergoing a combination therapy with encorafenib and cetuximab in second- and further-lines have demonstrated a longer survival compared to those who received physician’s choice therapy [11]. Currently, the efficacy of this combination is further explored in the first-line setting [12]. Moreover, just recently, several small clinical phase 1 and 2 trials demonstrated encouraging response rates in pretreated mCRC patients harboring KRASG12C mutations (3–4% of all mCRC), NTRK- (0.5%) or RET fusions (0.2–1.6%) who underwent treatment with KRASG12C inhibitors in combination with anti-EGFR agents, larotrectinib or entrectinib, or selpercatinib, respectively [13,14,15,16]. However, advances in drug development are highly warranted to further improve prognosis. In the past, research focused more towards directly targeting the tumor cells, while neglecting the crucial role of the tumor microenvironment (TME) and its influence on tumor progression. A growing body of evidence nowadays indicates that targeting cells within the TME might be promising to further enhance anti-tumorigenic properties or to impede pro-tumorigenic effects [17,18]. To keep up with the latest progress in drug development, further biomarkers have to be defined and promising platforms such as ex vivo culturing of tumors are to be established to help personalize treatment and to identify patients who may benefit most from a specific therapy. In the present review, we will provide an overview about currently established biomarkers that guide clinical decision-making but also shed light on promising markers that may be clinically useful in the near future. Table 1 outlines a selection of requirements for an effective prognostic or predictive biomarker [19,20,21,22,23]. While a prognostic biomarker predicts the outcome of a disease irrespective of the applied treatment and thus may serve as an independent indicator of tumor biology, a predictive biomarker predicts the outcome of a disease depending on a specific treatment [24]. Diagnostic biomarkers do not play a role in mCRC. An elevation of the carcinoembryonic antigen (CEA) can indicate or support the presence of colon cancer but is not diagnostic, as an increased CEA level is rather unspecific and can also be observed in the presence of inflammation or other malignancies. Conversely, a normal CEA level does not exclude colon cancer.

2. Established Biomarkers in mCRC

The advances of precision medicine have produced unprecedented paradigm shifts in the treatment algorithms of advanced cancers. However, CRC remains far behind the other solid tumors (e.g., non-small cell lung cancer, melanoma, genitourinary tract cancers). To date, only a few biomarkers have sufficient actionable and clinical implications to warrant international guideline-recommended routine testing [25]. Table 2 provides an overview of established biomarkers in mCRC.
Only in approximately 5% of mCRC patients, namely those harboring an MSI/dMMR tumor, we observed outstanding and practice-changing results with CPI therapy. The treatment of the remaining vast majority of mCRC patients (who are microsatellite stable—MSS) is still based upon only a few molecular and/or clinical determinants: sidedness of the primary tumor location, RAS and BRAF mutational status [26]. Another well-established biomarker is HER2 amplification, since several trials have shown the clinical activity of a combination strategy for HER2 blockade [27], although no standard treatments have been approved by regulatory agencies for these patients.
NTRK fusions are extremely rare in CRC patients (<1%). Despite this, the recent positive and practice-changing basket trials of TRK inhibitors (larotrectinib [28] and entrectinib [15]) encourage clinicians to test for NTRK in mCRC patients, especially in later-lines of therapy [29]. Several other molecular determinants are under clinical investigation. Some of them are expected to become part of our practice routine and change our therapeutic paradigms in the near future: circulating tumor DNA (ctDNA), POLE alteration, KRASG12C mutation, FGFR fusions, altered DNA damage repair (DDR) genes, tumor mutational burden (TMB) and consensus molecular subtypes classification (CMS), as well as ALK/RET/ROS fusions [30].

2.1. Sidedness

Primary tumor sidedness (right- versus left-sided) is considered an established and crucial prognostic and predictive factor in the treatment of mCRC [31,32,33,34]. Besides the difference in their origin, these tumors exhibit different histology. While right-sided tumors are often associated with sessile serrated adenomas or mucinous adenocarcinomas, left-sided tumors are related to tubular, villous and typical adenocarcinomas. Usually, left-sided tumors exhibit a polypoid growth pattern and are therefore easier to detect compared to right-sided tumors which are more frequently flat [35].
Comparative molecular analyses of right- and left-sided CRCs revealed molecular distinctions, such as different mutation rates in TP53, KRAS, PIK3CA, BRAF and diverse methylation patterns, as well as different MSI/dMMR rates [36,37,38]. Another study demonstrated that right-sided colon cancers had higher rates of MSI, more frequent aberrant activation of the EGFR/MAPK pathway including higher BRAF mutation rates and an increased mutational burden compared to left-sided CRCs [36].
A retrospective study using data from the SEER registry demonstrated that patients with right-sided stage III or IV colon cancers had worse survival outcomes in comparison to left-sided CRC patients [39]. Another study indicated that right-sided colon cancers were associated with a high CpG island methylator phenotype (CIMP) and BRAF mutations, translating into inferior OS and a worse response to anti-EGFR treatment [40].
Therefore, one may assume that mCRC with primary tumors located in the left colon display a different tumor biology with a different response to therapy compared to those arising in the right colon. This hypothesis has been confirmed in multiple exploratory post-hoc analyses of large, randomized trials [8,33,41,42,43] (see Table 2). Just recently, the findings of the phase III PARADIGM study have been presented at the ASCO Annual Meeting 2022. Patients with left-sided RAS wild-type mCRC treated with FOLFOX and panitumumab showed a prolonged mOS compared to those receiving FOLFOX and bevacizumab in the first-line setting (37.9 vs. 34.3 months, HR 0.82, p = 0.031) [44,45].
For these reasons, to date, the treatment algorithm for mCRC patients in the first-line setting is based on the primary tumor location: chemotherapy plus anti-EGFR regimen is recommended for left-sided MSS, RAS and BRAF wild-type tumors, while chemotherapy plus anti-VEGF (bevacizumab) is recommended for right-sided MSS mCRC patients [46].

2.2. DNA Mismatch Repair Deficiency (dMMR) and/or Microsatellite Instability (MSI)

dMMR comprises about 15% of all CRC. It is more frequently observed in early- than in late-stage disease (stage I–II: 15–20%, stage III: 10–15%, stage IV: around 5%) [47,48]. The mismatch repair system (MMR) status can be investigated by testing for loss of an MMR protein by immunohistochemistry (IHC) or for MSI using a PCR- or NGS-based assay. dMMR or MSI-high (MSI-H) tumors display the loss of at least one MMR protein with IHC (MLH1, MSH2, MSH6, and PMS2) or instability in two or more of the five microsatellite markers (BAT25, BAT26, D2S123, D5S346 and D17S250) with a PCR-based assay [49,50], respectively. Concordance between these two techniques is quite high (>90%) [51], thus usually IHC testing is performed to determine the MMR status. However, further PCR- or NGS-based testing is recommended in case of undetermined or inconclusive IHC findings [26,52]. MSI-H/dMMR mCRC are more frequently right-sided and poorly differentiated and correlate more often with BRAF mutations [49].
Testing for dMMR/MSI-H status is mandatory and crucial for the management of CRC patients for mainly four reasons: (a) universal screening for Lynch syndrome, which is the most common cause of hereditary CRC [53,54]; (b) dMMR status is one of the most studied and well-established biomarkers for better prognosis, especially in stage II CRC patients. In all the studies, MSI-H has been associated with a better outcome in comparison to MSS, in terms of time to recurrence (TTR), relapse-free survival (RFS) and OS [55,56]; (c) in stage II, CRC dMMR status is also a strong negative predictive biomarker of 5-fluorouracil efficacy, thus guiding adjuvant chemotherapy choice [57]; (d) in the metastatic setting, MSI-H/-dMMR status is a strong positive factor for predicting response upon CPI, as was first shown by the landmark studies by Le et al. [58,59]. Recently, the final analysis of the phase II KEYNOTE-164 trial was presented, yielding durable and clinical meaningful benefit, with a 30% plateau of both progression-free survival (PFS) and OS curves at five years and a manageable safety profile in patients with previously treated MSI-H/dMMR mCRC [60].
MSI-H/dMMR status is a well-established biomarker predictive of CPI response. The rationale is based on the significantly increased number of mutation-associated neoantigens resulting from mismatch-repair deficiency. In fact, MSI-H mCRC has an immunogenic TME, characterized by dense immune infiltration and a Th1-associated cytokine-rich environment [61]. Several trials demonstrated that CPI as monotherapy or combined with other agents were associated with improved clinical outcome in this subgroup of patients [62,63]. Currently, the phase II CheckMate 142 trial explores the impact of nivolumab monotherapy and in combination with ipilimumab in previously treated or untreated patients with MSI-H/dMMR or MSS/MMR-proficient mCRC [64]. A robust and durable clinical benefit with a manageable safety profile in previously treated patients with MSI-H/dMMR mCRC was shown [62,63]. A recent report with 4 years of follow-up confirmed impressive and unprecedented results with nivolumab (3 mg/kg) plus low-dose (1 mg/kg) ipilimumab in this setting: ORR was 65%, with a disease control rate (DCR) of 81%. The 48-month rates of PFS and OS were 53% and 71%, respectively [64].
Based on these results, nivolumab combined with ipilimumab obtained approval in Europe, while Japan and the United States approved nivolumab as a single-agent treatment and combined with ipilimumab in pretreated MSI-H/dMMR mCRC patients. These exceptional findings have also been confirmed in the first-line setting: with a median follow-up of 29.0 months, nivolumab plus low-dose ipilimumab showed an ORR and a DCR of 69% and 84%, respectively. Furthermore, the 24-month rates of PFS and OS were 74% and 79%, respectively [65]. In this setting, the results are awaited from the current phase III CheckMate 8HW trial (NCT04008030).
Finally, the KEYNOTE-177 phase III randomized trial showed that pembrolizumab led to significantly longer PFS than chemotherapy plus antibody (16.5 vs. 8.2 months) in newly diagnosed MSI-H/dMMR mCRC, with significant fewer treatment-related adverse events [10]. Moreover, 3-year OS (3-yr OS) was 61.4% in the experimental arm, much higher than that of the control arm (3-yr OS 50.3%) [66]. Considering these results, the Food and Drug Administration (FDA) first and then the European Medicines Agency (EMA) approved pembrolizumab alone as a first-line treatment for patients with MSI-H/dMMR mCRC.
These results led to a paradigm shift in the management of MSI-H/dMMR mCRC patients in recent years [67]. Many studies are still warranted to improve our knowledge, especially about primary resistance to CPIs, since up to 30–40% of MSI-H/dMMR mCRC patients do not benefit and progress. This may be caused by different reasons, such as the misdiagnosis of the actual dMMR status [68], microenvironment characteristics and the composition of the gut microbiome [69], as well as the presence of ascites and peritoneal involvement [70]. Nevertheless, the benefit for the majority of MSI-H/dMMR mCRC patients treated with CPI is unprecedented, with one-third of patients who could achieve a complete response. This makes MMR status mandatory and extremely useful in clinical practice.
To underscore the revolution in the management of patients with MSI-H/dMMR, it is noteworthy that neoadjuvant CPI also proved to be a promising new approach for the management of MSI-H/dMMR non-metastatic CRC [71,72,73,74].

2.3. RAS Mutations

The RAS oncogene family consists of three oncogenes in humans, located on chromosome 12, namely Kirsten (KRAS), Neuroblastoma (NRAS) and Harvey rat sarcoma viral oncogene homolog (HRAS). The RAS family is one of the most frequently mutated genes across all malignancies, including CRC [75], and functions as regulators of the intracellular signaling transduction cascades involved in cell growth, differentiation and survival [76]. RAS stimulates various downstream signaling pathways, including the RAS-RAF-MEK-ERK and the phosphatidylinositol 3-kinase (PI3K) pathways [77].
Approximately 40–50% of CRC carry KRAS or NRAS mutations. The majority of them are found in KRAS G12, G13 or Q61 codons. Of these, G12 variants are the most frequent ones (around 70%) [78].
RAS (and BRAF) mutations confer more aggressive tumor biology and are negative prognostic factors in particular in MSS mCRC. Moreover, these genetic alterations are negative predictive factors for a response to milestone anti-EGFR therapy (cetuximab or panitumumab) [79,80,81].
For a long time, RAS mutations have been deemed ‘undruggable’ [82], as many attempts targeting RAS mutations failed in the past. However, the recent development of KRASG12C-selective inhibitors established a foundation for the development of inhibitors suitable for clinical testing and opened new therapeutic strategies for this historically undruggable target [83,84].
Determination of primary tumor location, MMR status and RAS/BRAF mutational status is mandatory to assess the optimal therapeutic strategy in the first-line setting. As mentioned above, patients with MSS, RAS and BRAF wild-type mCRC and a primary tumor located in the left colon are considered suitable candidates for first-line anti-EGFR treatment in combination with chemotherapy [4,31,32,33,85,86,87].
Despite this selection of patients, primary resistance to anti-EGFR agents still exists, and more studies are requested to dig deep into the mechanisms of resistance. For these reasons, Cremolini et al. demonstrated a promising negative predictive impact of the PRESSING panel: uncommon molecular alterations linked to primary resistance to EGFR inhibition, including HER2 amplification/activating mutations, MET amplification, NTRK/ROS1/ALK/RET rearrangements, PIK3CA exon 20, PTEN and AKT1 mutations [88]. This negative molecular hyperselection of patients, added to the initial assessment of sidedness and RAS/BRAF mutational status, may help identify a subgroup of patients who will exceptionally benefit from anti-EGFR–based initial therapy [89].

KRASG12C Mutation

The specific KRASG12C mutation is detectable in 1–3% of CRCs [83,90,91,92]. Only recently, two oral inhibitors (sotorasib, adagrasib) demonstrated clinical activity in mCRC patients harboring a KRASG12C mutation [93,94]. In a phase I trial, sotorasib yielded a DCR of 73.8% and a PFS of 4.0 months [95]. These results have been confirmed by the subsequent phase II CodeBreak trial (ORR: 9.7%, PFS: 4.0 months) [96]. Furthermore, the KRYSTAL-1 phase I/II trial investigated the clinical activity of adagrasib in pretreated mCRCs. These promising findings revealed an ORR of 22%, DCR of 87% and a PFS of 5.6 months [13]. Additionally, preliminary results of a combined treatment with adagrasib and cetuximab demonstrated an ORR of 43% and a stable disease in 57% [13]. Further trials exploring the combination of anti-EGFR and anti-KRAS inhibitors are currently under clinical investigation with the aim of improving the efficacy of KRAS inhibitors [97].

2.4. BRAFV600E Mutation

The RAS/MEK/ERK and PI3K pathways play a major role in cancer development and progression [98]. Among solid tumors, the prevalence of activating somatic missense BRAF mutations, with the V600E mutational variant accounting for about 80% of mutations, occurs in malignant melanomas (60–70%), papillary and anaplastic thyroid carcinomas (40–50%) and ovarian cancers (30%). All mutations in BRAF confer increased kinase activity compared with the wild-type protein and thereby stimulate MAPK/ERK activity in a RAS-independent manner. BRAF mutation occurs in about 10–20% of CRCs, and 90% of these mutations occur in V600E. BRAF-mutated CRCs patients show distinct clinico-pathological and molecular features identifying a subset with an aggressive phenotype and poor outcome [99]. More specifically, BRAF-mutated tumors are more frequently observed in elderly patients, females and in right-sided tumors, show more aggressive pathological features such as mucinous features, serrated architecture, poor differentiation, as well as peritoneal dissemination, and they present in an advanced stage at the time of the initial diagnosis [100]. Finally, the vast majority of patients with BRAF-mutated mCRC experience early disease progression [101].
BRAFV600E mutation is strongly associated with MSI-H/dMMR status (20–60%) [102]. Indeed, in sporadic CRCs, BRAF mutation is seen in approximately 60% of MSI-H tumors and only in 5–10% in MSS tumors [103]. This association is crucial also to distinguish sporadic MSI-H/dMMR from Lynch syndrome, since the BRAFV600E mutation excludes Lynch syndrome while being related to sporadic CRC patients [104].
The BRAFV600E mutation has been widely investigated, and its negative prognostic impact on stage II and III CRC has been observed in numerous studies [105,106]. Similarly, in advanced-stage patients with BRAF mutant CRC have low response rates to conventional therapies and poor OS [103].
Selective BRAF inhibitors are very effective as monotherapy in other malignancies, such as melanoma. However, disappointing results were observed in pretreated BRAF mutant mCRC patients with vemurafenib [107], suggesting that combination treatment could be more efficious to overcome primary resistance due to adaptive feedback, resulting in upstream activation of EGFR and subsequent treatment resistance [108].
The phase III BEACON trial was the first trial to show a substantial benefit both in survival and in response rates in pretreated BRAFV600E mCRCs [109]. This trial randomized 665 patients to receive triplet-therapy (encorafenib + binimetinib + cetuximab) or doublet-therapy (encorafenib + cetuximab) compared to the control arm (cetuximab + irinotecan or FOLFIRI). The results showed a clear advantage for the experimental arms: the doublet reported benefit in OS compared to control (9.3 months vs. 5.9 months, HR 0.61), in PFS and RR [110]. Results were almost identical with the triplet, yet with different and more frequent side effects. Based on these results, the doublet (encorafenib + cetuximab) was determined to be sufficient for OS and received FDA approval in April 2020.
Of note, the results of this combination of drugs showed disappointing results in first-line BRAFV600E mCRC patients in the single-arm phase II trial (ANCHOR CRC) with a PFS of 4.9 months [111]. For this reason, the phase III BREAKWATER trial (NCT04607421) is currently ongoing and is comparing encorafenib + cetuximab alone or in combination with a chemotherapy doublet versus the doublet or triplet chemotherapy +/− bevacizumab in first-line BRAFV600E mutated mCRC [12].
Just recently, encouraging results of a phase I/II trial exploring the efficacy of encorafenib and cetuximab plus nivolumab in 26 patients with MSS/BRAFV600E-mutated mCRC were presented at the 2022 Gastrointestinal Cancers Symposium [112]. The ORR and DCR were 50% and 96%, and mPFS and mOS were 7.4 and 15.1 months, respectively.
Based on data available and due to the strong association between MSI-H and BRAF mutations, we believe that patients with MSI-H/BRAFV600E-mutated mCRC should be treated with CPI in the first-line setting, followed by a combined targeted treatment consisting of encorafenib and cetuximab in case of disease progression.

2.5. HER2 Amplification

Amplification in the HER2/Erbb2 oncogene or overexpression of its protein produces a hyperactivation of mitogenic signals, leading to uncontrolled cell proliferation and tumorigenesis [113]. HER2 amplification has been reported in about 2–5% of all CRCs [114].
The role of HER2 amplification as a prognostic biomarker is still uncertain [115], while its role as a negative predictive factor of resistance to anti-EGFR agents is more and more established [116].
More importantly, HER2 amplification is a well-known druggable target in other settings, such as in breast and gastric cancers, in which approved treatments are already available.
In mCRC, the proof-of-concept multicenter, open-label, phase II trial HERACLES reported promising results with the combination of trastuzumab and lapatinib in heavily pretreated mCRC harboring a HER2 amplification [117], although in a small population (n = 27), with an ORR of 30%. On the other hand, the HERACLES-B did not reach its primary endpoint of ORR. The HERACLES-B was a single-arm, phase II trial, in patients with histologically confirmed RAS/BRAF wild-type and HER2+ mCRC refractory to standard treatments [118].
Two further international phase II studies investigated the role of pertuzumab and trastuzumab combination in heavily pretreated patients: the MyPathway trial [119] and the TRIUMPH trial [120], with similar promising results.
The ongoing phase II MOUNTAINEER trial is exploring the efficacy of tucatinib and trastuzumab in treatment-resistant mCRC [121]. Trastuzumab–deruxtecan (T-DXd) is an antibody–drug conjugate consisting of a humanized anti-HER2 monoclonal specifically targeting HER2, with the same amino acid sequence as trastuzumab, a cleavable tetrapeptide-based linker and a potent topoisomerase I inhibitor as the cytotoxic drug (payload), who demonstrated revolutionizing and astonishing results in different malignancies [122]. The DESTINY-CRC01 was an open-label, phase II trial investigating the efficacy of T-DXd single agent in pretreated HER2-overexpressing mCRC patients [123]. In the HER2-positive cohort (defined as IHC3+ or IHC2+ and in situ hybridization (ISH)-positive), the ORR was 45.3%, and the mOS was 15.5 months. In addition, T-DXd seems to overcome resistance to previous HER2-targeted treatment, as no differences in outcome could be observed between patients who received HER2-targeted treatment in earlier lines and those being anti-HER2 treatment naïve [124].
Based on these results, the multicenter, randomized, double-blind, 2-arm, parallel phase II study DESTINY-CRC02 (NCT04744831) is currently ongoing [125]. Of note, in this trial KRAS mutant mCRC patients will also be enrolled, while in previous trials only RAS wild-type tumor patients were recruited.

3. Beyond Classical Biomarkers in CRC

3.1. NTRK Fusions

The neurotrophic tropomyosin receptor kinase genes (NTRK1, NTRK2, NTRK3) encode for tropomyosin receptor kinase proteins (TRK1, TRK2, TRK3) that are involved in embryonal neural development and in cell homeostasis [126,127]. Chromosomal fusions involving NTRK (e.g., ETV6-NTRK3, CD74-NRTK1) have been detected in a subset of cancer patients [128,129]. After promising results of preclinical experiments [129], clinical trials using two TRK inhibitors have been conducted. In a phase I/II trial, the first-generation TRK inhibitor larotrectinib was analysed for efficacy in tumor patients harboring a NTRK fusion [130]. An impressive ORR of 75% and long-lasting responses were observed. Not surprisingly, larotrectinib has been approved for the treatment of NTRK-rearranged malignancies, irrespective of tumor histology [131]. Similarly, treatment with entrectinib, an inhibitor targeting TRK, ROS1 and ALK, was associated with clinically meaningful and durable responses in NTRK-fusion-positive tumors [15]. To overcome secondary resistance mechanisms, further second-generation TRK inhibitors are currently under clinical evaluation (i.e., repotrectinib [132] and taletrectinib [133]).
In CRC, NTRK fusions are detectable in <1% of CRCs [134]. Molecular profiling data revealed that NTRK fusions are associated with APC and TP53 mutations and are mutually exclusive of RAS/RAF alterations [134]. Furthermore, NTRK-rearranged tumors occur more frequently in MSI-H/dMMR CRCs [135]. Four CRC patients were treated with entrectinib within a clinical trial. Of them, one patient (25%) showed a partial response [15]. The ongoing phase II basket trial (NAVIGATE) investigates the effect of larotrectinib in patients with NTRK fusion-positive tumors. Preliminary data demonstrated an ORR of 50% and an mOS of 29.4 months in 10 patients with refractory NTRK fusion-positive mCRC [28].
Although NTRK fusions occur only in an extremely small subset of CRCs (<1%) and limited data exist in terms of the clinical efficacy of NTRK inhibitors in these tumors, larotrectinib and entrectinib are possible therapeutic options for NTRK fusion CRCs. Further research is needed to clarify the biological function and role of NTRK in CRC, especially in the subgroup of MSI-H/dMMR, and how this might affect response rates on anti-TRK inhibitors.

3.1.1. FGFR

Only recently, gene alterations within the fibroblast-growth factor receptor (FGFR) family have gained attention, since several different targeted agents showed clinically meaningful activity [136]. FGFR signaling is involved in numerous different pathways, including the MAPK and mTOR pathway [137,138]. The FGFR family includes four members: FGFR1, FGFR2, FGFR3 and FGFR4. Gene fusions, mutations, and amplifications of the FGFR gene have all been reported in gastrointestinal cancers. In CRC, mainly amplifications in FGFR1 and FGFR2 are observed with an incidence of approximately 4% and 3%, respectively [139]. While in other FGFR-altered tumors, including cholangiocarcinomas [140] and bladder cancers [141], specific FGFR inhibitors yielded impressive response, in CRC data on FGFR1 and FGFR2 amplifications as novel targets are limited. In a retrospective study, investigators found that three of three patients with a FGFR1-amplified CRC showed a partial response upon regorafenib therapy [139]. Only recently, the activity of the FGFR1-4 inhibitor futibatinib was assessed in a clinical phase I trial including five CRC patients in which only a modest activity could be described [142].

3.1.2. DNA Damage Repair Genes

DNA damage repair (DDR) genes are essential for preserving the function of cells [143]. Several genes are involved in maintaining the stability of the DDR system, including BRCA1, BRCA2 and PALB2 [144]. Deficiencies in DDR genes via homologous recombination (HR) can cause genetic instability leading to increased rates of somatic genetic alterations [145,146]. Not surprisingly, for decades researchers tried to target these respective genes. Recently, poly(ADP-ribose)polymerase (PARP) inhibitors have been described to induce synthetic lethality in BRCA-mutated cancer cells in vitro [147] and are now increasingly used in BRCA-mutated tumors, such as pancreatic cancer [148]. Alterations in BRCA and in other DDR genes are found in a significant subset of gastrointestinal cancers (15–20%) [149]. Moreover, mutated DDR genes are detectable in approximately 22% of CRCs [144]. While the results of a first clinical trial investigating the efficacy of a monotherapy with the PARP inhibitor olaparib were disappointing [150], combining a PARP inhibitor with classical cytotoxic regimens yielded promising response rates [151,152]. Further agents beyond PARP inhibitors are currently under clinical investigation in several cancers. Of them, inhibitors targeting ATR, CHK1 and WEE1 seem to be very promising [153].
Since DDR gene mutations are detectable in a significant subset of CRC and several targeted agents currently being tested in clinical trials, these mutations represent a clinical meaningful target and will change the diagnostic and therapeutic management of CRCs in the near future.

3.1.3. POLE

DNA polymerase epsilon (POLE) encodes for the catalytic subunit of the DNA polymerase epsilon, which is involved in DNA replication and repair [154]. Mutations in POLE are observed in approximately 1–2% of CRC [155,156]. Interestingly, similarly to MSI-H tumors, POLE-mutated CRCs are characterized by the high infiltration of CD8+ T- cells [157,158] and a high TMB [159]. For this reason, researchers investigated the efficacy of the CPI nivolumab in mCRC patients harboring a POLE mutation. Five out of seven patients recruited in this study yielded a clinical response upon nivolumab monotherapy [159]. In a phase II trial, another CPI (durvalumab) was tested in MSI-H/dMMR or POLE-mutated mCRCs. Three patients with a POLE mutation were included. The efficacy of durvalumab could be observed in one patient [160]. Thus, POLE might serve as a potential predictive biomarker for CPI in patients with a MSS mCRC [161]. However, more research and clinical data are still needed to confirm this hypothesis.

3.1.4. RET

Rearranged-during-transfection (RET) fusions occur in a subset of cancer patients, particularly in thyroid [162] and lung cancers [163]. RET rearrangements are detectable in 0.2–1.6% of CRCs [164,165]. RET-fused CRCs are more commonly detected in right-sided primaries, are associated with MSI-H/dMMR and with non-mutated RAS/RAF status. Regarding prognosis, they are linked to a shorter survival [166]. Interestingly, a negative predictive role of RET fusions upon anti-EGFR inhibitors were noted [89,167].
Even if the incidence of RET fusions in CRCs are rare, several approved multi-tyrosine kinase inhibitors (i.e., vandetanib, lenvatinib, ponatinib) are available that inhibit this specific pathway [168,169,170]. Just recently, Subbiah et al. presented preliminary data from the ongoing phase I/II LIBRETTO-001 trial (NCT03157128) [171]. Patients with mCRC harboring RET fusions and treated with selpercatinib achieved an ORR of 44% [16]. Another phase I/II trial is currently ongoing aiming to investigate the efficacy of pralsetinib (NCT03037385) in RET-rearranged tumors [172].

3.1.5. RSPO Fusions and RNF43 Mutations

WNT/β-catenin signaling represents the most important altered pathway in the tumorigenesis of CRCs mainly induced by mutations in APC [173,174]. Many efforts were made to therapeutically inhibit WNT/β-catenin signaling. However, until now all studies failed to show any efficacy [175]. Interestingly, a subset of patients with CRC, pancreatic cancer and small bowel cancer harbor mutations in RNF43 [176] or harbor an R-spondin (RSPO) fusion [177]. These genetic alterations are observed in a significant subset of CRC (8%) [178] and are mutually exclusive of mutations in APC. Currently, several early clinical trials are aiming to test the efficacy of various therapeutic agents, including LRP5/6 inhibitors (NCT03604445) [179].

3.1.6. Other Promising Biomarkers

There are several post hoc translational studies from phase III randomized trials, such as FIRE-3 and TRIBE, demonstrating that variations in the RSPO2, MKNK1 or GC genes involved in the MAPK and WNT signaling pathways predict outcome in patients with mCRC treated with FOLFIRI and bevacizumab [174,180,181]. These translational studies are critical to identify potential biomarkers in mCRC patients enabling us to better tailor treatment.

3.2. A Selection of Emerging Biomarkers in the TME

The TME consists of various cell types such as cytotoxic and regulatory T-cells (CTL, Tregs), helper (Th) cells, natural killer (NK) cells, B-cells, myeloid-derived suppressor cells (MDSC), tumor-associated macrophages (TAM), cancer-associated fibroblasts (CAF) and endothelial cells [182,183,184]. These cells interact closely with cancer cells by promoting anti- and pro-tumorigenic effects and thus play a crucial role in modulating tumor growth, invasion and progression [17]. Pagès et al. could demonstrate in a large cohort of stage I–III colon cancer patients that an increased infiltration of CD3+ and cytotoxic CD8+ T-cells (Immunoscore high) is associated with a lower risk of disease recurrence and longer overall survival compared to those patients whose tumors exhibit a decreased CD3+/CD8+ density Immunoscore low) independent of age, T or N stages and MSI status. These results could be confirmed in further validation sets [185]. Additionally, the clinical utility of the Immunoscore could also be shown in mCRC patients [186,187]. Therefore, we can conclude that the CD3+/CD8+ immune infiltration within the TME may serve as a prognostic biomarker. However, whether the Immunoscore is predictive of response to CPI in MSS mCRC patients has to be further explored in prospective clinical trials. Guinney et al. categorized CRC into four molecular subgroups and created the consensus molecular subtypes (CMS) based on gene expression profiles [188]. The CMS1 group (MSI-like) is distinguished by a certain gene expression pattern being representative of activated cytotoxic T-cells. Thus, the CMS1 subtype represents an immunogenic TME and is in general associated with a favorable outcome [189]. In contrast, the CMS4 subtype (mesenchymal) is characterized by a stroma-rich and immunosuppressive TME and mainly associated with a poor outcome [189]. While the CMS2 subtype (canonical) comprises CRC with predominantly activated WNT and Myc signaling pathways, the CMS3 subgroup (metabolic) is enriched by KRAS mutations and activated metabolic pathways. Both of them exhibit a decreased immune-related gene expression profile and are associated with an intermediate prognosis [189]. Although the prognostic impact of the CMS classification could have been shown and retrospective translational analysis of phase III clinical trials [190,191] demonstrated an added predictive value, its implementation into the daily diagnostic algorithm has not been established yet. This is mainly due to the labor-intensive, complex and costly analyses preventing a translation into the daily diagnostic workflow.

3.3. Circulating Tumor DNA (ctDNA)

Tumor cells shed ctDNA into the bloodstream. These ctDNA fragments possess the same genetic information as the primary tumor or the metastases [18]. The fraction of ctDNA is highly variable, ranging from <0.1% up to 10% depending on tumor load, tumor stage, tumor shedding and disease site [192,193]. In CRC, the use of ctDNA is not yet implemented in clinical practice. However, findings from recent studies and ongoing trials indicate that ctDNA may serve as both prognostic and predictive biomarkers in the near future. For a more comprehensive overview about ctDNA in colorectal cancer, we suggest further literature [194].
Briefly, ctDNA can be used with different aims in the adjuvant and metastatic setting.
In early-stage patients ctDNA may be implemented at diagnosis for molecular profiling, especially if tumor tissue is not available. Moreover, ctDNA may be used as a biomarker for response to neoadjuvant and adjuvant therapies to detect minimal residual disease (MRD) after surgery and to guide treatment selection. For instance, the concentration of ctDNA in pretreatment plasma is significantly lower in stage I patients compared with stage II–III patients [195].
Recently, Tie et al. demonstrated that a ctDNA-guided treatment approach in stage II colon cancer patients reduced the use of adjuvant chemotherapy without compromising RFS [196]. Although other studies are needed, this study opens new avenues for the best selection of patients who are candidates for adjuvant treatment.
On the other hand, in the metastatic setting, ctDNA holds many promises in the clinic: molecular profiling at diagnosis, targeted therapy selection, treatment response monitoring, post-treatment tumor surveillance to detect recurrence, and monitoring treatment resistance [197,198].
Several trials are ongoing to investigate the clinical utility of ctDNA in both early-stage and advanced CRC patients, and the results derived from these studies will potentially change our clinical practice soon.

4. Preclinical Models for Target Discovery

4.1. Patient Derived Organoids

Given the high costs and the long timeline of new drug development, repurposing of already approved drugs used in other malignancies is a promising, cost-effective and efficient way to rapidly implement drugs with a known safety profile in the treatment algorithm of mCRC. A promising approach to simultaneously test multiple different single drugs or drug combinations and to assess their cytotoxic effect on tumor cells are patient-derived organoids (PDO) from patients with mCRC [199]. PDO are three-dimensional ex vivo cultured cancer cells that derive directly from the patient’s tumor. PDO reflect the in vivo heterogeneity and complexity of the tumor while retaining the accessibility of in vitro technologies. Preliminary studies could demonstrate that organoids exhibited similar molecular profiles as those observed in the patient’s tumor and may help unraveling resistance mechanisms to certain drugs during the course of the disease [200]. Additionally, there is evidence that PDO drug screens have the potential to predict therapeutic response in mCRC patients. Currently, several trials are ongoing to test organoid-based treatment prediction using already established standard of care regimens. However, the clinical utility of prospective PDO-based drug screening that goes beyond testing for standard of care options in patients with mCRC has not been largely explored yet. The APOLLO trial demonstrated that PDO-guided treatment might be promising to expand therapeutic options in patients with treatment-refractory peritoneal mCRC. However, the small number of patients included in this trial precludes drawing any definite conclusions [201]. An obvious limitation of classical PDO is that they do not mirror the complexity of the TME. However, further development of PDO and adding of co-cultures containing compounds of the extracellular matrix, such as endothelial cells, fibroblasts and immune cells, are highly warranted to accurately predict response to treatment that targets TME, including the immune system (e.g., CPI) [202]. Another issue is to obtain enough fresh tumor tissue for culturing, as sufficient tissue should also be available for routine diagnostic procedures at the same time. A further challenge in the clinical translation of PDO is to reduce the turnaround time, that means to minimize the time from obtaining tumor tissue for generating PDOs until the clinician receives the PDO drug screen results. In case of successful identification of potential effective compounds, further hurdles have to be overcome such as access to off-label drugs. Such a process involves a request for cost reimbursement from the health insurance company or the willingness of the pharmaceutic company to provide the drug for free. This approach is inevitably accompanied by the uncertainties of obtaining (or not) off-label compounds to treat such patients.
In conclusion, there is an unmet need to further explore the promising use of patient avatars such as PDO to move the field forward and to find new ways to optimize precision medicine and to individualize further-line treatment in mCRC patients. Further alternative models are described below.

4.2. Patient-Derived Xenograft Models (PDX)

Various murine models have been developed in the past to better understand tumorigenesis, tumor cell migration, invasion, metastasis and response to treatment [203]. A widely used model is the patient-derived xenograft (PDX), where human tumor cells are directly injected or transplanted into immunocompromised mice [203]. Whereas this model has the potential to examine response to therapy in vivo, several limitations do exist. First, the establishment and maintenance of PDX models is labor-intensive and associated with high costs. Second, tumor growth can last several months and may not guarantee efficient drug testing that can be rapidly translated into the real-life situation in the clinic, when the patient is faced with tumor progression and a further-line treatment has to be initiated within a reasonable time frame. Third, immunocompromised mice do not mirror the conditions in human cancers and may not serve as an optimal model to study response to CPI or interactions between the host’s immunity and the tumor.
As our understanding of the significance of the TME and the host’s immune system is evolving, adapted models are eagerly needed to further advance in the field of precision medicine.

4.3. Patient-Derived Tumor Fragment Platform (PDTF)

Just recently, Voabil et al. developed an ex vivo tumor fragment culture that preserves the cellular composition and the architecture of the tumor. This platform maintains the characteristics of the TME and allows for example to study ex vivo CPI, mechanisms of resistance and various interactions between the tumor and its surrounding microenvironment. Moreover, Voabil et al. could demonstrate that there is a high correlation between clinical and ex vivo responses to CPI. This promising observation may lead us to further explore whether a PDTF platform helps to predict outcomes in cancer patients treated with CPI [204].

5. Challenges in Biomarker Research and Future Perspective

The dream of precision oncology is to individualize the diagnostic and therapeutic management of cancer patients according to their genetic profile. The increasing use of high-throughput techniques, such as next-generation sequencing (NGS), helped to pave the way for the implementation of precision oncology in our daily routine. The turn-around time of NGS results for established predictive biomarkers in the first-line setting (MSI, RAS, BRAF) could be significantly shortened and is currently about 5–7 days, enabling a timely start of biomarker-driven therapy. For these biomarkers, corresponding drugs are available and reimbursed by health insurance companies. Regarding the therapeutically relevant assessment of MSI/MMRd for first-line treatment, IHC testing for MMR status is even faster than NGS and allows a very early initiation of CPI in case of MMRd mCRC. The NGS results report not only contains informations on MSI, RAS and BRAF status but also includes comprehensive details on further druggable genetic alterations, such as HER2 amplifications and NTRK fusions, that may be important in the further-line setting [117,131]. Although HER2 amplification or overexpression of its protein is considered an established predictive biomarker in the further-line treatment of mCRC patients [117], anti-HER2 drugs are not yet approved in this setting and not reimbursed and only available within clinical trials or upon off-label request. Despite the low prevalence of NTRK fusions in mCRC [134], response rates to targeted treatment are encouraging [131,154], and drugs such as larotrectinib and entrectinib are available and reimbursed by the National Health System. However, while the clinical utility of single biomarkers, such as KRAS [205] and MSI-H/dMMR [10], have been proved to extend survival of CRC patients, the role of comprehensive molecular profiling remains largely questionable. Moreover, only a limited number of studies have investigated the cost-effectiveness of molecular profiling in cancer patients [206,207,208,209,210]. For instance, a study conducted in NSCLC patients showed that NGS-based parallel testing was more cost-effective than single-gene-based testing [207]. To the best of our knowledge, no similar study exists for CRC patients. For this reason, a health–economic analysis investigating the clinical utility, in terms of survival benefit, and the cost-effectiveness of comprehensive molecular profiling would be highly desirable. Additionally, the evidence of emerging biomarkers in patients with mCRC is mainly based on post-hoc, retrospective translational work and unplanned subgroup analysis from large clinical trials. Due to the low prevalence of potentially druggable oncogenic drivers in mCRC, biomarker-driven clinical studies focusing on evaluating targeted drugs in a single tumor entity are challenging, labor-intensive and costly. With the introduction of basket trials exploring new drugs that target a distinct genetic alteration irrespective of the type of cancer, these hurdles could be at least partly overcome [211].
Emerging biomarkers in the TME such as the Immunoscore or the CMS classification have proven their prognostic impact [185,188,189]. However, their predictive value in mCRC has still to be proven in prospective trials. One of the reasons why the CMS classification did not find its way into the clinic so far are the resource-intensive and costly analyses impeding its clinical implementation. PDX models or ex vivo platforms such as PDO or PDTF might be promising translational tools for biomarker development and drug testing in the near future. However, their role as patient avatars has to be further developed and optimized before an implementation into the daily clinical practice can be realized.
With the introduction of new therapeutic approaches, the need for biomarkers will steadily increase in the future to identify subgroups of patients who may derive the most benefit from a specific treatment. While immunotherapies, targeted and cellular-based therapies have already found their way into the clinic for several malignancies, further innovative treatment approaches are emerging, such as cellular therapies, combined therapy using oncolytic viruses or genetically modified attenuated bacteria with immune-checkpoint inhibitors (NCT03256344, NCT05120596) [212,213]. Additionally, repurposing of drugs will be crucial to enlarge the treatment armamentarium against colorectal cancer. However, it is still debated whether ex vivo models such as PDX, PDO or PDTF may help us to accelerate this process.
In the future, to improve the selection of CRC patients for individualized therapies, we will need more informative profiling. However, we are still at the beginning of comprehensive molecular profiling, since we are still focusing (mostly) only on genetic alterations. Thus, to better depict the unique properties of cancer, we will need to include more information concerning the tumor’s biology. For instance, gene expression analyses might help to better characterize the link between genetic landscape and the cancer’s behavior [214,215]. Currently, understanding the complex interplay between CRC cells and the surrounding TME (e.g., immune cells, fibroblasts, healthy enterocytes and the gut microbiome) is a main focus in cancer research [216,217]. Findings from these analyses might help to establish a “real” comprehensive molecular profile that might serve as an imperative tool for precise therapies in CRC.
Therefore, future development of precision medicine in metastatic colorectal cancer will not only focus on tumor cells but rather on implementing the tumor microenvironment in clinical decision-making. Notably, recent advances have elucidated that gut microbiota has different and complex roles in cancer development, as well as in treatment response, that must be comprehensively addressed from a clinically translational angle [218]. Various studies demonstrated that the composition of intestinal bacteria differs between responders and non-responders to immune checkpoint inhibitors [219] and also to chemotherapy. Several studies are ongoing to investigate the potential of utilizing gut microbiome as CRC biomarkers and also to enhance treatment efficacy and reduce adverse effects of CRC treatments [220].
Furthermore, combining information coming from genomics, transcriptomics, epigenomics, metabolomics, microbiomics and proteomics might help to establish a “real” comprehensive molecular profile that might serve as an imperative tool for precise therapies in CRC.
Finally, artificial intelligence and digital pathology will help us to define nomograms integrating clinical, molecular and histopathological factors, while we are moving forward in the field of precision medicine.

6. Conclusions

A biomarker-driven treatment algorithm allows to identify those mCRC patients who derive the most benefit from a specific therapeutic approach, while we are further pursuing the path of personalized therapy.

Author Contributions

Conceptualization, M.D.B.; writing—original draft preparation, A.P., A.S. and M.D.B.; writing—review and editing, A.P., A.S. and M.D.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest regarding the content of this manuscript.

References

  1. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
  2. Xi, Y.; Xu, P. Global colorectal cancer burden in 2020 and projections to 2040. Transl. Oncol. 2021, 14, 101174. [Google Scholar] [CrossRef] [PubMed]
  3. Lavin, P.; Mittelman, A.; Douglass, H.; Engstrom, P.; Klaassen, D. Survival and response to chemotherapy for advanced colorectal adenocarcinoma. An eastern cooperative oncology group report. Cancer 1980, 46, 1536–1543. [Google Scholar] [CrossRef]
  4. Venook, A.P.; Niedzwiecki, D.; Lenz, H.J.; Innocenti, F.; Fruth, B.; Meyerhardt, J.A.; Schrag, D.; Greene, C.; O’Neil, B.H.; Atkins, J.N.; et al. Effect of First-Line Chemotherapy Combined With Cetuximab or Bevacizumab on Overall Survival in Patients With KRAS Wild-Type Advanced or Metastatic Colorectal Cancer: A Randomized Clinical Trial. JAMA 2017, 317, 2392–2401. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Berger, M.D.; Lenz, H.-J. The safety of monoclonal antibodies for treatment of colorectal cancer. Expert Opin. Drug Saf. 2016, 15, 799–808. [Google Scholar] [CrossRef]
  6. Grothey, A.; Van Cutsem, E.; Sobrero, A.; Siena, S.; Falcone, A.; Ychou, M.; Humblet, Y.; Bouché, O.; Mineur, L.; Barone, C.; et al. Regorafenib monotherapy for previously treated metastatic colorectal cancer (CORRECT): An international, multicentre, randomised, placebo-controlled, phase 3 trial. Lancet 2013, 381, 303–312. [Google Scholar] [CrossRef]
  7. Mayer, R.J.; Van Cutsem, E.; Falcone, A.; Yoshino, T.; Garcia-Carbonero, R.; Mizunuma, N.; Yamazaki, K.; Shimada, Y.; Tabernero, J.; Komatsu, Y.; et al. Randomized Trial of TAS-102 for Refractory Metastatic Colorectal Cancer. N. Engl. J. Med. 2015, 372, 1909–1919. [Google Scholar] [CrossRef] [Green Version]
  8. Holch, J.W.; Ricard, I.; Stintzing, S.; Modest, D.P.; Heinemann, V. The relevance of primary tumour location in patients with metastatic colorectal cancer: A meta-analysis of first-line clinical trials. Eur. J. Cancer 2017, 70, 87–98. [Google Scholar] [CrossRef]
  9. Yoshino, T.; Arnold, D.; Taniguchi, H.; Pentheroudakis, G.; Yamazaki, K.; Xu, R.-H.; Kim, T.; Ismail, F.; Tan, I.; Yeh, K.-H.; et al. Pan-Asian adapted ESMO consensus guidelines for the management of patients with metastatic colorectal cancer: A JSMO–ESMO initiative endorsed by CSCO, KACO, MOS, SSO and TOS. Ann. Oncol. 2017, 29, 44–70. [Google Scholar] [CrossRef]
  10. Andre, T.; Shiu, K.K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab in Microsatellite-Instability-High Advanced Colorectal Cancer. N. Engl. J. Med. 2020, 383, 2207–2218. [Google Scholar] [CrossRef]
  11. Kopetz, S.; Grothey, A.; Yaeger, R.; Van Cutsem, E.; Desai, J.; Yoshino, T.; Wasan, H.; Ciardiello, F.; Loupakis, F.; Hong, Y.S.; et al. Encorafenib, Binimetinib, and Cetuximab in BRAF V600E-Mutated Colorectal Cancer. N. Engl. J. Med. 2019, 381, 1632–1643. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Kopetz, S.; Grothey, A.; Yaeger, R.; Ciardiello, F.; Desai, J.; Kim, T.W.; Maughan, T.; Cutsem, E.V.; Wasan, H.S.; Yoshino, T.; et al. BREAKWATER: Randomized phase 3 study of encorafenib (enco) + cetuximab (cet) ± chemotherapy for first-line treatment (tx) of BRAF V600E-mutant (BRAFV600) metastatic colorectal cancer (mCRC). J. Clin. Oncol. 2022, 40, TPS211. [Google Scholar] [CrossRef]
  13. Weiss, J.; Yaeger, R.D.; Johnson, M.L.; Spira, A.; Klempner, S.J.; Barve, M.A.; Christensen, J.G.; Chi, A.; Der-Torossian, H.; Velastegui, K.; et al. KRYSTAL-1: Adagrasib (MRTX849) as monotherapy or combined with cetuximab (cetux) in patients (pts) with colorectal cancer (CRC) harboring a KRASG12C mutation. Ann. Oncol. 2021, 32, 1283–1346. [Google Scholar] [CrossRef]
  14. Hong, D.S.; DuBois, S.G.; Kummar, S.; Farago, A.F.; Albert, C.M.; Rohrberg, K.S.; van Tilburg, C.M.; Nagasubramanian, R.; Berlin, J.D.; Federman, N.; et al. Larotrectinib in patients with TRK fusion-positive solid tumours: A pooled analysis of three phase 1/2 clinical trials. Lancet Oncol. 2020, 21, 531–540. [Google Scholar] [CrossRef]
  15. Doebele, R.C.; Drilon, A.; Paz-Ares, L.; Siena, S.; Shaw, A.T.; Farago, A.F.; Blakely, C.M.; Seto, T.; Cho, B.C.; Tosi, D.; et al. Entrectinib in patients with advanced or metastatic NTRK fusion-positive solid tumours: Integrated analysis of three phase 1–2 trials. Lancet Oncol. 2020, 21, 271–282. [Google Scholar] [CrossRef]
  16. Subbiah, V.; Konda, B.; Bauer, T.; McCoach, C.; Falchook, G.; Takeda, M.; Patel, J.; Weiss, J.; Peled, N.; Bazhenova, L.; et al. Abstract CT011: Efficacy and safety of selpercatinib in RET fusion-positive cancers other than lung or thyroid cancers. Cancer Res. 2021, 81, CT011. [Google Scholar] [CrossRef]
  17. Hemmatazad, H.; Berger, M.D. CCR5 is a potential therapeutic target for cancer. Expert Opin. Ther. Targets 2021, 25, 311–327. [Google Scholar] [CrossRef] [PubMed]
  18. Rhyner Agocs, G.; Assarzadegan, N.; Kirsch, R.; Dawson, H.; Galván, J.A.; Lugli, A.; Zlobec, I.; Berger, M.D. LAG-3 Expression Predicts Outcome in Stage II Colon Cancer. J. Pers. Med. 2021, 11, 749. [Google Scholar] [CrossRef]
  19. Califf, R.M. Biomarker definitions and their applications. Exp. Biol. Med. 2018, 243, 213–221. [Google Scholar] [CrossRef]
  20. Strimbu, K.; Tavel, J.A. What are biomarkers? Curr. Opin. HIV AIDS 2010, 5, 463–466. [Google Scholar] [CrossRef]
  21. Mayeux, R. Biomarkers: Potential uses and limitations. NeuroRx 2004, 1, 182–188. [Google Scholar] [CrossRef] [PubMed]
  22. Raskin, W.; Cheema, P.; Perdrizet, K.; Iafolla, M.; Dudani, S.; Sheffield, B. Rapid point of care NGS in colorectal cancer. J. Clin. Oncol. 2022, 40, 172. [Google Scholar] [CrossRef]
  23. Raza, A.; Khan, A.Q.; Inchakalody, V.P.; Mestiri, S.; Yoosuf, Z.S.K.M.; Bedhiafi, T.; El-Ella, D.M.A.; Taib, N.; Hydrose, S.; Akbar, S.; et al. Dynamic liquid biopsy components as predictive and prognostic biomarkers in colorectal cancer. J. Exp. Clin. Cancer Res. 2022, 41, 99. [Google Scholar] [CrossRef] [PubMed]
  24. Ballman, K.V. Biomarker: Predictive or Prognostic? J. Clin. Oncol. 2015, 33, 3968–3971. [Google Scholar] [CrossRef]
  25. Salem, M.E.; Puccini, A.; Tie, J. Redefining Colorectal Cancer by Tumor Biology. Am. Soc. Clin. Oncol. Educ. Book 2020, 40, 147–159. [Google Scholar] [CrossRef]
  26. Martelli, V.; Pastorino, A.; Sobrero, A.F. Prognostic and predictive molecular biomarkers in advanced colorectal cancer. Pharmacol. Ther. 2022, 236, 108239. [Google Scholar] [CrossRef]
  27. Kim, S.Y.; Kim, T.W. Current challenges in the implementation of precision oncology for the management of metastatic colorectal cancer. ESMO Open 2020, 5, e000634. [Google Scholar] [CrossRef] [Green Version]
  28. Boni, V.; Drilon, A.; Deeken, J.; Garralda, E.; Chung, H.; Kinoshita, I.; Oh, D.; Patel, J.; Xu, R.; Norenberg, R.; et al. SO-29 Efficacy and safety of larotrectinib in patients with tropomyosin receptor kinase fusion-positive gastrointestinal cancer: An expanded dataset. Ann. Oncol. 2021, 32, S214–S215. [Google Scholar] [CrossRef]
  29. Solomon, J.P.; Benayed, R.; Hechtman, J.F.; Ladanyi, M. Identifying patients with NTRK fusion cancer. Ann. Oncol. 2019, 30 (Suppl. 8), viii16–viii22. [Google Scholar] [CrossRef] [Green Version]
  30. Di Nicolantonio, F.; Vitiello, P.P.; Marsoni, S.; Siena, S.; Tabernero, J.; Trusolino, L.; Bernards, R.; Bardelli, A. Precision oncology in metastatic colorectal cancer—From biology to medicine. Nat. Rev. Clin. Oncol. 2021, 18, 506–525. [Google Scholar] [CrossRef]
  31. Tejpar, S.; Stintzing, S.; Ciardiello, F.; Tabernero, J.; Van Cutsem, E.; Beier, F.; Esser, R.; Lenz, H.J.; Heinemann, V. Prognostic and Predictive Relevance of Primary Tumor Location in Patients With RAS Wild-Type Metastatic Colorectal Cancer: Retrospective Analyses of the CRYSTAL and FIRE-3 Trials. JAMA Oncol. 2017, 3, 194–201. [Google Scholar] [CrossRef] [PubMed]
  32. Aljehani, M.A.; Morgan, J.W.; Guthrie, L.A.; Jabo, B.; Ramadan, M.; Bahjri, K.; Lum, S.S.; Selleck, M.; Reeves, M.E.; Garberoglio, C.; et al. Association of Primary Tumor Site With Mortality in Patients Receiving Bevacizumab and Cetuximab for Metastatic Colorectal Cancer. JAMA Surg. 2018, 153, 60–67. [Google Scholar] [CrossRef] [PubMed]
  33. Arnold, D.; Lueza, B.; Douillard, J.Y.; Peeters, M.; Lenz, H.J.; Venook, A.; Heinemann, V.; Van Cutsem, E.; Pignon, J.P.; Tabernero, J.; et al. Prognostic and predictive value of primary tumour side in patients with RAS wild-type metastatic colorectal cancer treated with chemotherapy and EGFR directed antibodies in six randomized trials. Ann. Oncol. 2017, 28, 1713–1729. [Google Scholar] [CrossRef] [PubMed]
  34. Puccini, A.; Lenz, H.J. Colorectal cancer in 2017: Practice-changing updates in the adjuvant and metastatic setting. Nat. Rev. Clin. Oncol. 2018, 15, 77–78. [Google Scholar] [CrossRef]
  35. Nawa, T.; Kato, J.; Kawamoto, H.; Okada, H.; Yamamoto, H.; Kohno, H.; Endo, H.; Shiratori, Y. Differences between right- and left-sided colon cancer in patient characteristics, cancer morphology and histology. J. Gastroenterol. Hepatol. 2008, 23, 418–423. [Google Scholar] [CrossRef]
  36. Salem, M.E.; Weinberg, B.A.; Xiu, J.; El-Deiry, W.S.; Hwang, J.J.; Gatalica, Z.; Philip, P.A.; Shields, A.F.; Lenz, H.J.; Marshall, J.L. Comparative molecular analyses of left-sided colon, right-sided colon, and rectal cancers. Oncotarget 2017, 8, 86356–86368. [Google Scholar] [CrossRef] [Green Version]
  37. Hu, W.; Yang, Y.; Li, X.; Huang, M.; Xu, F.; Ge, W.; Zhang, S.; Zheng, S. Multi-omics Approach Reveals Distinct Differences in Left- and Right-Sided Colon Cancer. Mol. Cancer Res. 2018, 16, 476–485. [Google Scholar] [CrossRef] [Green Version]
  38. Lee, M.S.; Menter, D.G.; Kopetz, S. Right Versus Left Colon Cancer Biology: Integrating the Consensus Molecular Subtypes. J. Natl. Compr. Canc. Netw. 2017, 15, 411–419. [Google Scholar] [CrossRef] [Green Version]
  39. Schrag, D.; Weng, S.; Brooks, G.; Meyerhardt, J.A.; Venook, A.P. The relationship between primary tumor sidedness and prognosis in colorectal cancer. J. Clin. Oncol. 2016, 34, 3505. [Google Scholar] [CrossRef]
  40. Lee, M.S.; Advani, S.M.; Morris, J.; Jiang, Z.-Q.; Manyam, G.C.; Menter, D.; Broom, B.M.; Eng, C.; Overman, M.J.; Maru, D.M. Association of primary (1°) site and molecular features with progression-free survival (PFS) and overall survival (OS) of metastatic colorectal cancer (mCRC) after anti-epidermal growth factor receptor (αEGFR) therapy. J. Clin. Oncol. 2016, 34, 3506. [Google Scholar] [CrossRef]
  41. Stintzing, S.; Tejpar, S.; Gibbs, P.; Thiebach, L.; Lenz, H.J. Understanding the role of primary tumour localisation in colorectal cancer treatment and outcomes. Eur. J. Cancer 2017, 84, 69–80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Boeckx, N.; Koukakis, R.; Op de Beeck, K.; Rolfo, C.; Van Camp, G.; Siena, S.; Tabernero, J.; Douillard, J.Y.; Andre, T.; Peeters, M. Effect of Primary Tumor Location on Second- or Later-line Treatment Outcomes in Patients With RAS Wild-type Metastatic Colorectal Cancer and All Treatment Lines in Patients With RAS Mutations in Four Randomized Panitumumab Studies. Clin. Colorectal. Cancer 2018, 17, 170–178.e173. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Salem, M.E.; Battaglin, F.; Goldberg, R.M.; Puccini, A.; Shields, A.F.; Arguello, D.; Korn, W.M.; Marshall, J.L.; Grothey, A.; Lenz, H.J. Molecular Analyses of Left- and Right-Sided Tumors in Adolescents and Young Adults with Colorectal Cancer. Oncologist 2020, 25, 404–413. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Yoshino, T.; Uetake, H.; Tsuchihara, K.; Shitara, K.; Yamazaki, K.; Watanabe, J.; Oki, E.; Sato, T.; Naitoh, T.; Komatsu, Y.; et al. PARADIGM study: A multicenter, randomized, phase III study of mFOLFOX6 plus panitumumab or bevacizumab as first-line treatment in patients with RAS (KRAS/NRAS) wild-type metastatic colorectal cancer. J. Clin. Oncol. 2021, 39, 85. [Google Scholar] [CrossRef]
  45. Yoshino, T.; Watanabe, J.; Shitara, K.; Yasui, H.; Ohori, H.; Shiozawa, M.; Yamazaki, K.; Oki, E.; Sato, T.; Naitoh, T.; et al. Panitumumab (PAN) plus mFOLFOX6 versus bevacizumab (BEV) plus mFOLFOX6 as first-line treatment in patients with RAS wild-type (WT) metastatic colorectal cancer (mCRC): Results from the phase 3 PARADIGM trial. J. Clin. Oncol. 2022, 40, LBA1. [Google Scholar] [CrossRef]
  46. Cremolini, C.; Antoniotti, C.; Moretto, R.; Masi, G.; Falcone, A. First-line therapy for mCRC—The influence of primary tumour location on the therapeutic algorithm. Nat. Rev. Clin. Oncol. 2017, 14, 113. [Google Scholar] [CrossRef] [Green Version]
  47. Kawakami, H.; Zaanan, A.; Sinicrope, F.A. Microsatellite instability testing and its role in the management of colorectal cancer. Curr. Treat. Options. Oncol. 2015, 16, 30. [Google Scholar] [CrossRef]
  48. Puccini, A.; Berger, M.D.; Zhang, W.; Lenz, H.J. What We Know About Stage II and III Colon Cancer: It’s Still Not Enough. Target Oncol. 2017, 12, 265–275. [Google Scholar] [CrossRef]
  49. Boland, C.R.; Goel, A. Microsatellite instability in colorectal cancer. Gastroenterology 2010, 138, 2073–2087.e2073. [Google Scholar] [CrossRef]
  50. Koopman, M.; Kortman, G.A.M.; Mekenkamp, L.; Ligtenberg, M.J.L.; Hoogerbrugge, N.; Antonini, N.F.; Punt, C.J.A.; van Krieken, J.H.J.M. Deficient mismatch repair system in patients with sporadic advanced colorectal cancer. Br. J. Cancer 2009, 100, 266–273. [Google Scholar] [CrossRef]
  51. Guyot D’Asnières De Salins, A.; Tachon, G.; Cohen, R.; Karayan-Tapon, L.; Junca, A.; Frouin, E.; Godet, J.; Evrard, C.; Randrian, V.; Duval, A.; et al. Discordance between immunochemistry of mismatch repair proteins and molecular testing of microsatellite instability in colorectal cancer. ESMO Open 2021, 6, 100120. [Google Scholar] [CrossRef] [PubMed]
  52. Luchini, C.; Bibeau, F.; Ligtenberg, M.J.L.; Singh, N.; Nottegar, A.; Bosse, T.; Miller, R.; Riaz, N.; Douillard, J.Y.; Andre, F.; et al. ESMO recommendations on microsatellite instability testing for immunotherapy in cancer, and its relationship with PD-1/PD-L1 expression and tumour mutational burden: A systematic review-based approach. Ann. Oncol. 2019, 30, 1232–1243. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Sinicrope, F.A. Lynch Syndrome-Associated Colorectal Cancer. N. Engl. J. Med. 2018, 379, 764–773. [Google Scholar] [CrossRef] [PubMed]
  54. NICE|The National Institute for Health and Care Excellence. Molecular Testing Strategies for Lynch Syndrome in People with Colorectal Cancer. Diagnostics Guidance. Available online: www.nice.org.uk/guidance/dg27 (accessed on 22 February 2017).
  55. Taieb, J.; Karoui, M.; Basile, D. How I treat stage II colon cancer patients. ESMO Open 2021, 6, 100184. [Google Scholar] [CrossRef]
  56. Koenig, J.L.; Toesca, D.A.S.; Harris, J.P.; Tsai, C.J.; Haraldsdottir, S.; Lin, A.Y.; Pollom, E.L.; Chang, D.T. Microsatellite Instability and Adjuvant Chemotherapy in Stage II Colon Cancer. Am. J. Clin. Oncol. 2019, 42, 573–580. [Google Scholar] [CrossRef] [PubMed]
  57. Sargent, D.J.; Marsoni, S.; Monges, G.; Thibodeau, S.N.; Labianca, R.; Hamilton, S.R.; French, A.J.; Kabat, B.; Foster, N.R.; Torri, V.; et al. Defective mismatch repair as a predictive marker for lack of efficacy of fluorouracil-based adjuvant therapy in colon cancer. J. Clin. Oncol. 2010, 28, 3219–3226. [Google Scholar] [CrossRef] [Green Version]
  58. Le, D.T.; Uram, J.N.; Wang, H.; Bartlett, B.R.; Kemberling, H.; Eyring, A.D.; Skora, A.D.; Luber, B.S.; Azad, N.S.; Laheru, D.; et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N. Engl. J. Med. 2015, 372, 2509–2520. [Google Scholar] [CrossRef] [Green Version]
  59. Le, D.T.; Durham, J.N.; Smith, K.N.; Wang, H.; Bartlett, B.R.; Aulakh, L.K.; Lu, S.; Kemberling, H.; Wilt, C.; Luber, B.S.; et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science 2017, 357, 409–413. [Google Scholar] [CrossRef] [Green Version]
  60. Le, D.T.; Diaz, L.; Kim, T.W.; Van Cutsem, E.; Geva, R.; Jäger, D.; Hara, H.; Burge, M.; O’Neil, B.; Kavan, P.; et al. 432P Pembrolizumab (pembro) for previously treated, microsatellite instability–high (MSI-H)/mismatch repair–deficient (dMMR) metastatic colorectal cancer (mCRC): Final analysis of KEYNOTE-164. Ann. Oncol. 2021, 32, S550. [Google Scholar] [CrossRef]
  61. Battaglin, F.; Naseem, M.; Lenz, H.J.; Salem, M.E. Microsatellite instability in colorectal cancer: Overview of its clinical significance and novel perspectives. Clin. Adv. Hematol. Oncol. 2018, 16, 735–745. [Google Scholar]
  62. Overman, M.J.; Lonardi, S.; Wong, K.Y.M.; Lenz, H.J.; Gelsomino, F.; Aglietta, M.; Morse, M.A.; Van Cutsem, E.; McDermott, R.; Hill, A.; et al. Durable Clinical Benefit With Nivolumab Plus Ipilimumab in DNA Mismatch Repair-Deficient/Microsatellite Instability-High Metastatic Colorectal Cancer. J. Clin. Oncol. 2018, 36, 773–779. [Google Scholar] [CrossRef] [PubMed]
  63. Overman, M.J.; Lenz, H.J.; Andre, T.; Aglietta, M.; Wong, M.K.; Luppi, G.; Van Cutsem, E.; McDermott, R.S.; Hendlisz, A.; Cardin, D.B.; et al. Nivolumab (NIVO) +/- ipilimumab (IPI) in patients (pts) with microsatellite instability-high/mismatch repair-deficient (MSI-H/dMMR) metastatic colorectal cancer (mCRC): Five-year follow-up from CheckMate 142. J. Clin. Oncol. 2022, 40. no. 16_suppl:3510-3510. [Google Scholar] [CrossRef]
  64. Andre, T.; Lonardi, S.; Wong, K.Y.M.; Lenz, H.J.; Gelsomino, F.; Aglietta, M.; Morse, M.A.; Van Cutsem, E.; McDermott, R.; Hill, A.; et al. Nivolumab + low-dose ipilimumab in previously treated patients with microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer: 4-year follow-up from CheckMate 142. Ann. Oncol. 2022. [Google Scholar] [CrossRef]
  65. Lenz, H.-J.; Cutsem, E.V.; Limon, M.L.; Wong, K.Y.M.; Hendlisz, A.; Aglietta, M.; García-Alfonso, P.; Neyns, B.; Luppi, G.; Cardin, D.B.; et al. First-Line Nivolumab Plus Low-Dose Ipilimumab for Microsatellite Instability-High/Mismatch Repair-Deficient Metastatic Colorectal Cancer: The Phase II CheckMate 142 Study. J. Clin. Oncol. 2022, 40, 161–170. [Google Scholar] [CrossRef]
  66. Diaz, L.A.; Shiu, K.-K.; Kim, T.-W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab versus chemotherapy for microsatellite instability-high or mismatch repair-deficient metastatic colorectal cancer (KEYNOTE-177): Final analysis of a randomised, open-label, phase 3 study. Lancet Oncol. 2022, 23, 659–670. [Google Scholar] [CrossRef]
  67. André, T.; Cohen, R.; Salem, M.E. Immune Checkpoint Blockade Therapy in Patients With Colorectal Cancer Harboring Microsatellite Instability/Mismatch Repair Deficiency in 2022. Am. Soc. Clin. Oncol. Educ. Book 2022, 42, 1–9. [Google Scholar] [CrossRef] [PubMed]
  68. Cohen, R.; Hain, E.; Buhard, O.; Guilloux, A.; Bardier, A.; Kaci, R.; Bertheau, P.; Renaud, F.; Bibeau, F.; Flejou, J.F.; et al. Association of Primary Resistance to Immune Checkpoint Inhibitors in Metastatic Colorectal Cancer With Misdiagnosis of Microsatellite Instability or Mismatch Repair Deficiency Status. JAMA Oncol. 2019, 5, 551–555. [Google Scholar] [CrossRef] [Green Version]
  69. Puccini, A.; Battaglin, F.; Iaia, M.L.; Lenz, H.J.; Salem, M.E. Overcoming resistance to anti-PD1 and anti-PD-L1 treatment in gastrointestinal malignancies. J. Immunother. Cancer 2020, 8, e000404. [Google Scholar] [CrossRef]
  70. Fuca, G.; Cohen, R.; Lonardi, S.; Shitara, K.; Elez, M.E.; Fakih, M.; Chao, J.; Klempner, S.J.; Emmett, M.; Jayachandran, P.; et al. Ascites and resistance to immune checkpoint inhibition in dMMR/MSI-H metastatic colorectal and gastric cancers. J. Immunother. Cancer 2022, 10, e004001. [Google Scholar] [CrossRef]
  71. Cercek, A.; Lumish, M.; Sinopoli, J.; Weiss, J.; Shia, J.; Lamendola-Essel, M.; El Dika, I.H.; Segal, N.; Shcherba, M.; Sugarman, R.; et al. PD-1 Blockade in Mismatch Repair-Deficient, Locally Advanced Rectal Cancer. N. Engl. J. Med. 2022, 386, 2363–2376. [Google Scholar] [CrossRef]
  72. Cercek, A.; Lumish, M.A.; Sinopoli, J.C.; Weiss, J.A.; Shia, J.; Stadler, Z.K.; Yaeger, R.; Smith, J.J.; Saltz, L.B.; El Dika, I.H.; et al. Single agent PD-1 blockade as curative-intent treatment in mismatch repair deficient locally advanced rectal cancer. J. Clin. Oncol. 2022, 40, LBA5. [Google Scholar] [CrossRef]
  73. Chalabi, M.; Fanchi, L.F.; Dijkstra, K.K.; Van Den Berg, J.G.; Aalbers, A.G.; Sikorska, K.; Lopez-Yurda, M.; Grootscholten, C.; Beets, G.L.; Snaebjornsson, P.; et al. Neoadjuvant immunotherapy leads to pathological responses in MMR-proficient and MMR-deficient early-stage colon cancers. Nat. Med. 2020, 26, 566–576. [Google Scholar] [CrossRef] [PubMed]
  74. Chalabi, M.; Verschoor, Y.; Berg, J.V.D.; Sikorska, K.; Beets, G.; Lent, A.; Grootscholten, M.; Aalbers, A.; Buller, N.; Marsman, H.; et al. LBA7 Neoadjuvant immune checkpoint inhibition in locally advanced MMR-deficient colon cancer: The NICHE-2 study. Ann. Oncol. 2022, 33, S1389. [Google Scholar] [CrossRef]
  75. Prior, I.A.; Lewis, P.D.; Mattos, C. A comprehensive survey of Ras mutations in cancer. Cancer Res. 2012, 72, 2457–2467. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Malumbres, M.; Barbacid, M. RAS oncogenes: The first 30 years. Nat. Rev. Cancer 2003, 3, 459–465. [Google Scholar] [CrossRef]
  77. Simanshu, D.K.; Nissley, D.V.; McCormick, F. RAS Proteins and Their Regulators in Human Disease. Cell 2017, 170, 17–33. [Google Scholar] [CrossRef] [Green Version]
  78. Patelli, G.; Tosi, F.; Amatu, A.; Mauri, G.; Curaba, A.; Patane, D.A.; Pani, A.; Scaglione, F.; Siena, S.; Sartore-Bianchi, A. Strategies to tackle RAS-mutated metastatic colorectal cancer. ESMO Open 2021, 6, 100156. [Google Scholar] [CrossRef]
  79. Benvenuti, S.; Sartore-Bianchi, A.; Di Nicolantonio, F.; Zanon, C.; Moroni, M.; Veronese, S.; Siena, S.; Bardelli, A. Oncogenic activation of the RAS/RAF signaling pathway impairs the response of metastatic colorectal cancers to anti-epidermal growth factor receptor antibody therapies. Cancer Res. 2007, 67, 2643–2648. [Google Scholar] [CrossRef] [Green Version]
  80. Waring, P.; Tie, J.; Maru, D.; Karapetis, C.S. RAS Mutations as Predictive Biomarkers in Clinical Management of Metastatic Colorectal Cancer. Clin. Color. Cancer 2016, 15, 95–103. [Google Scholar] [CrossRef]
  81. Stintzing, S.; Miller-Phillips, L.; Modest, D.P.; Fischer von Weikersthal, L.; Decker, T.; Kiani, A.; Vehling-Kaiser, U.; Al-Batran, S.E.; Heintges, T.; Kahl, C.; et al. Impact of BRAF and RAS mutations on first-line efficacy of FOLFIRI plus cetuximab versus FOLFIRI plus bevacizumab: Analysis of the FIRE-3 (AIO KRK-0306) study. Eur. J. Cancer 2017, 79, 50–60. [Google Scholar] [CrossRef]
  82. Cox, A.D.; Fesik, S.W.; Kimmelman, A.C.; Luo, J.; Der, C.J. Drugging the undruggable RAS: Mission possible? Nat. Rev. Drug. Discov. 2014, 13, 828–851. [Google Scholar] [CrossRef] [PubMed]
  83. Salem, M.E.; El-Refai, S.M.; Sha, W.; Puccini, A.; Grothey, A.; George, T.J.; Hwang, J.J.; O’Neil, B.; Barrett, A.S.; Kadakia, K.C.; et al. Landscape of KRAS(G12C), Associated Genomic Alterations, and Interrelation With Immuno-Oncology Biomarkers in KRAS-Mutated Cancers. JCO Precis. Oncol. 2022, 6, e2100245. [Google Scholar] [CrossRef] [PubMed]
  84. Negri, F.; Bottarelli, L.; de’Angelis, G.L.; Gnetti, L. KRAS: A Druggable Target in Colon Cancer Patients. Int. J. Mol. Sci. 2022, 23, 4120. [Google Scholar] [CrossRef] [PubMed]
  85. Van Cutsem, E.; Lenz, H.J.; Köhne, C.H.; Heinemann, V.; Tejpar, S.; Beier, I.M.; Stroh, C.; Rougier, P.; van Krieken, J.H.; Ciardiello, F. Fluorouracil, leucovorin, and irinotecan plus cetuximab treatment and RAS mutations in colorectal cancer. J. Clin. Oncol. 2015, 33, 692–700. [Google Scholar] [CrossRef] [Green Version]
  86. Heinemann, V.; von Weikersthal, L.F.; Decker, T.; Kiani, A.; Vehling-Kaiser, U.; Al-Batran, S.E.; Heintges, T.; Lerchenmuller, C.; Kahl, C.; Seipelt, G.; et al. FOLFIRI plus cetuximab versus FOLFIRI plus bevacizumab as first-line treatment for patients with metastatic colorectal cancer (FIRE-3): A randomised, open-label, phase 3 trial. Lancet Oncol. 2014, 15, 1065–1075. [Google Scholar] [CrossRef]
  87. Douillard, J.Y.; Oliner, K.S.; Siena, S.; Tabernero, J.; Burkes, R.; Barugel, M.; Humblet, Y.; Bodoky, G.; Cunningham, D.; Jassem, J.; et al. Panitumumab-FOLFOX4 treatment and RAS mutations in colorectal cancer. N. Engl. J. Med. 2013, 369, 1023–1034. [Google Scholar] [CrossRef] [Green Version]
  88. Cremolini, C.; Morano, F.; Moretto, R.; Berenato, R.; Tamborini, E.; Perrone, F.; Rossini, D.; Gloghini, A.; Busico, A.; Zucchelli, G.; et al. Negative hyper-selection of metastatic colorectal cancer patients for anti-EGFR monoclonal antibodies: The PRESSING case-control study. Ann. Oncol. 2017, 28, 3009–3014. [Google Scholar] [CrossRef] [PubMed]
  89. Morano, F.; Corallo, S.; Lonardi, S.; Raimondi, A.; Cremolini, C.; Rimassa, L.; Murialdo, R.; Zaniboni, A.; Sartore-Bianchi, A.; Tomasello, G.; et al. Negative Hyperselection of Patients With RAS and BRAF Wild-Type Metastatic Colorectal Cancer Who Received Panitumumab-Based Maintenance Therapy. J. Clin. Oncol. 2019, 37, 3099–3110. [Google Scholar] [CrossRef]
  90. Neumann, J.; Zeindl-Eberhart, E.; Kirchner, T.; Jung, A. Frequency and type of KRAS mutations in routine diagnostic analysis of metastatic colorectal cancer. Pathol. Res. Pract. 2009, 205, 858–862. [Google Scholar] [CrossRef]
  91. Araujo, L.H.; Souza, B.M.; Leite, L.R.; Parma, S.A.F.; Lopes, N.P.; Malta, F.S.V.; Freire, M.C.M. Molecular profile of KRAS G12C-mutant colorectal and non-small-cell lung cancer. BMC Cancer 2021, 21, 193. [Google Scholar] [CrossRef]
  92. Henry, J.T.; Coker, O.; Chowdhury, S.; Shen, J.P.; van Morris, K.; Dasari, A.; Raghav, K.; Nusrat, M.; Kee, B.; Parseghian, C.; et al. Comprehensive Clinical and Molecular Characterization of KRASG12C-Mutant Colorectal Cancer. JCO Precis. Oncol. 2021, 5, PO.20.00256. [Google Scholar]
  93. Canon, J.; Rex, K.; Saiki, A.Y.; Mohr, C.; Cooke, K.; Bagal, D.; Gaida, K.; Holt, T.; Knutson, C.G.; Koppada, N.; et al. The clinical KRAS(G12C) inhibitor AMG 510 drives anti-tumour immunity. Nature 2019, 575, 217–223. [Google Scholar] [CrossRef] [PubMed]
  94. Hallin, J.; Engstrom, L.D.; Hargis, L.; Calinisan, A.; Aranda, R.; Briere, D.M.; Sudhakar, N.; Bowcut, V.; Baer, B.R.; Ballard, J.A.; et al. The KRASG12C Inhibitor MRTX849 Provides Insight toward Therapeutic Susceptibility of KRAS-Mutant Cancers in Mouse Models and Patients. Cancer Discov. 2020, 10, 54–71. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Hong, D.S.; Fakih, M.G.; Strickler, J.H.; Desai, J.; Durm, G.A.; Shapiro, G.I.; Falchook, G.S.; Price, T.J.; Sacher, A.; Denlinger, C.S.; et al. KRASG12C Inhibition with Sotorasib in Advanced Solid Tumors. N. Engl. J. Med. 2020, 383, 1207–1217. [Google Scholar] [CrossRef] [PubMed]
  96. Fakih, M.G.; Kopetz, S.; Kuboki, Y.; Kim, T.W.; Munster, P.N.; Krauss, J.C.; Falchook, G.S.; Han, S.; Heinemann, V.; Muro, K.; et al. Sotorasib for previously treated colorectal cancers with KRASG12C mutation (CodeBreaK100): A prespecified analysis of a single-arm, phase 2 trial. Lancet Oncol. 2022, 23, 115–124. [Google Scholar] [PubMed]
  97. Ji, J.; Wang, C.; Fakih, M. Targeting KRASG12C-Mutated Advanced Colorectal Cancer: Research and Clinical Developments. Onco Targets Ther. 2022, 15, 747–756. [Google Scholar] [CrossRef]
  98. Taieb, J.; Lapeyre-Prost, A.; Laurent Puig, P.; Zaanan, A. Exploring the best treatment options for BRAF-mutant metastatic colon cancer. Br. J. Cancer 2019, 121, 434–442. [Google Scholar] [CrossRef]
  99. Fanelli, G.N.; Dal Pozzo, C.A.; Depetris, I.; Schirripa, M.; Brignola, S.; Biason, P.; Balistreri, M.; Dal Santo, L.; Lonardi, S.; Munari, G.; et al. The heterogeneous clinical and pathological landscapes of metastatic Braf-mutated colorectal cancer. Cancer Cell Int. 2020, 20, 30. [Google Scholar] [CrossRef]
  100. Sanz-Garcia, E.; Argiles, G.; Elez, E.; Tabernero, J. BRAF mutant colorectal cancer: Prognosis, treatment, and new perspectives. Ann. Oncol. 2017, 28, 2648–2657. [Google Scholar] [CrossRef]
  101. Eng, C. BRAF Mutation in Colorectal Cancer: An Enigmatic Target. J. Clin. Oncol. 2021, 39, 259–261. [Google Scholar] [CrossRef]
  102. Goel, A.; Boland, C.R. Epigenetics of colorectal cancer. Gastroenterology 2012, 143, 1442–1460 e1441. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Clarke, C.N.; Kopetz, E.S. BRAF mutant colorectal cancer as a distinct subset of colorectal cancer: Clinical characteristics, clinical behavior, and response to targeted therapies. J. Gastrointest. Oncol. 2015, 6, 660–667. [Google Scholar] [CrossRef] [PubMed]
  104. Leclerc, J.; Vermaut, C.; Buisine, M.-P. Diagnosis of lynch syndrome and strategies to distinguish lynch-related tumors from sporadic MSI/dMMR tumors. Cancers 2021, 13, 467. [Google Scholar] [CrossRef] [PubMed]
  105. Zhu, L.; Dong, C.; Cao, Y.; Fang, X.; Zhong, C.; Li, D.; Yuan, Y. Prognostic Role of BRAF Mutation in Stage II/III Colorectal Cancer Receiving Curative Resection and Adjuvant Chemotherapy: A Meta-Analysis Based on Randomized Clinical Trials. PLoS ONE 2016, 11, e0154795. [Google Scholar] [CrossRef] [Green Version]
  106. Farina-Sarasqueta, A.; van Lijnschoten, G.; Moerland, E.; Creemers, G.J.; Lemmens, V.; Rutten, H.J.T.; van den Brule, A.J.C. The BRAF V600E mutation is an independent prognostic factor for survival in stage II and stage III colon cancer patients. Ann. Oncol. 2010, 21, 2396–2402. [Google Scholar] [CrossRef]
  107. Kopetz, S.; Desai, J.; Chan, E.; Hecht, J.R.; O’Dwyer, P.J.; Maru, D.; Morris, V.; Janku, F.; Dasari, A.; Chung, W.; et al. Phase II Pilot Study of Vemurafenib in Patients With Metastatic BRAF-Mutated Colorectal Cancer. J. Clin. Oncol. 2015, 33, 4032–4038. [Google Scholar] [CrossRef]
  108. Corcoran, R.B.; Ebi, H.; Turke, A.B.; Coffee, E.M.; Nishino, M.; Cogdill, A.P.; Brown, R.D.; Della Pelle, P.; Dias-Santagata, D.; Hung, K.E.; et al. EGFR-mediated re-activation of MAPK signaling contributes to insensitivity of BRAF mutant colorectal cancers to RAF inhibition with vemurafenib. Cancer Discov. 2012, 2, 227–235. [Google Scholar] [CrossRef] [Green Version]
  109. Kopetz, S.; Guthrie, K.A.; Morris, V.K.; Lenz, H.J.; Magliocco, A.M.; Maru, D.; Yan, Y.; Lanman, R.; Manyam, G.; Hong, D.S.; et al. Randomized Trial of Irinotecan and Cetuximab With or Without Vemurafenib in BRAF-Mutant Metastatic Colorectal Cancer (SWOG S1406). J. Clin. Oncol. 2021, 39, 285–294. [Google Scholar] [CrossRef]
  110. Tabernero, J.; Grothey, A.; Van Cutsem, E.; Yaeger, R.; Wasan, H.; Yoshino, T.; Desai, J.; Ciardiello, F.; Loupakis, F.; Hong, Y.S. Encorafenib plus cetuximab as a new standard of care for previously treated BRAF V600E-mutant metastatic colorectal cancer: Updated survival results and subgroup analyses from the BEACON study. J. Clin. Oncol. 2021, 39, 273–284. [Google Scholar] [CrossRef]
  111. Grothey, A.; Yaeger, R.; Paez, D.; Tabernero, J.; Taïeb, J.; Yoshino, T.; Groc, M.; Vedovato, J.; Chetaille, E.; Van Cutsem, E. ANCHOR CRC: A phase 2, open-label, single arm, multicenter study of encorafenib (ENCO), binimetinib (BINI), plus cetuximab (CETUX) in patients with previously untreated BRAF V600E-mutant metastatic colorectal cancer (mCRC). Ann. Oncol. 2019, 30, iv109. [Google Scholar] [CrossRef]
  112. Morris, V.K.; Parseghian, C.M.; Escano, M.; Johnson, B.; Raghav, K.P.S.; Dasari, A.; Huey, R.; Overman, M.J.; Willis, J.; Lee, M.S.; et al. Phase I/II trial of encorafenib, cetuximab, and nivolumab in patients with microsatellite stable, BRAFV600E metastatic colorectal cancer. J. Clin. Oncol. 2022, 40, 12. [Google Scholar] [CrossRef]
  113. Djaballah, S.A.; Daniel, F.; Milani, A.; Ricagno, G.; Lonardi, S. HER2 in Colorectal Cancer: The Long and Winding Road From Negative Predictive Factor to Positive Actionable Target. Am. Soc. Clin. Oncol. Educ. Book 2022, 42, 1–14. [Google Scholar] [CrossRef]
  114. Siena, S.; Sartore-Bianchi, A.; Marsoni, S.; Hurwitz, H.I.; McCall, S.J.; Penault-Llorca, F.; Srock, S.; Bardelli, A.; Trusolino, L. Targeting the human epidermal growth factor receptor 2 (HER2) oncogene in colorectal cancer. Ann. Oncol. 2018, 29, 1108–1119. [Google Scholar] [CrossRef] [PubMed]
  115. Richman, S.D.; Southward, K.; Chambers, P.; Cross, D.; Barrett, J.; Hemmings, G.; Taylor, M.; Wood, H.; Hutchins, G.; Foster, J.M.; et al. HER2 overexpression and amplification as a potential therapeutic target in colorectal cancer: Analysis of 3256 patients enrolled in the QUASAR, FOCUS and PICCOLO colorectal cancer trials. J. Pathol. 2016, 238, 562–570. [Google Scholar] [CrossRef] [Green Version]
  116. Baraibar, I.; Ros, J.; Mulet, N.; Salvà, F.; Argilés, G.; Martini, G.; Cuadra, J.L.; Sardo, E.; Ciardiello, D.; Tabernero, J.; et al. Incorporating traditional and emerging biomarkers in the clinical management of metastatic colorectal cancer: An update. Expert Rev. Mol. Diagn. 2020, 20, 653–664. [Google Scholar] [CrossRef] [PubMed]
  117. Sartore-Bianchi, A.; Trusolino, L.; Martino, C.; Bencardino, K.; Lonardi, S.; Bergamo, F.; Zagonel, V.; Leone, F.; Depetris, I.; Martinelli, E.; et al. Dual-targeted therapy with trastuzumab and lapatinib in treatment-refractory, KRAS codon 12/13 wild-type, HER2-positive metastatic colorectal cancer (HERACLES): A proof-of-concept, multicentre, open-label, phase 2 trial. Lancet Oncol. 2016, 17, 738–746. [Google Scholar] [CrossRef]
  118. Sartore-Bianchi, A.; Lonardi, S.; Martino, C.; Fenocchio, E.; Tosi, F.; Ghezzi, S.; Leone, F.; Bergamo, F.; Zagonel, V.; Ciardiello, F.; et al. Pertuzumab and trastuzumab emtansine in patients with HER2-amplified metastatic colorectal cancer: The phase II HERACLES-B trial. ESMO Open 2020, 5, e000911. [Google Scholar] [CrossRef]
  119. Meric-Bernstam, F.; Hurwitz, H.; Raghav, K.P.S.; McWilliams, R.R.; Fakih, M.; VanderWalde, A.; Swanton, C.; Kurzrock, R.; Burris, H.; Sweeney, C.; et al. Pertuzumab plus trastuzumab for HER2-amplified metastatic colorectal cancer (MyPathway): An updated report from a multicentre, open-label, phase 2a, multiple basket study. Lancet Oncol. 2019, 20, 518–530. [Google Scholar] [CrossRef]
  120. Okamoto, W.; Nakamura, Y.; Kato, T.; Esaki, T.; Komoda, M.; Kato, K.; Komatsu, Y.; Masuishi, T.; Nishina, T.; Sawada, K.; et al. Pertuzumab plus trastuzumab and real-world standard of care (SOC) for patients (pts) with treatment refractory metastatic colorectal cancer (mCRC) with HER2 (ERBB2) amplification (amp) confirmed by tumor tissue or ctDNA analysis (TRIUMPH, EPOC1602). J. Clin. Oncol. 2021, 39, 3555. [Google Scholar] [CrossRef]
  121. Strickler, J.; Zemla, T.; Ou, F.-S.; Cercek, A.; Wu, C.; Sanchez, F.; Hubbard, J.; Jaszewski, B.; Bandel, L.; Schweitzer, B. Trastuzumab and tucatinib for the treatment of HER2 amplified metastatic colorectal cancer (mCRC): Initial results from the MOUNTAINEER trial. Ann. Oncol. 2019, 30, v200. [Google Scholar] [CrossRef]
  122. Modi, S.; Saura, C.; Yamashita, T.; Park, Y.H.; Kim, S.B.; Tamura, K.; Andre, F.; Iwata, H.; Ito, Y.; Tsurutani, J.; et al. Trastuzumab Deruxtecan in Previously Treated HER2-Positive Breast Cancer. N. Engl. J. Med. 2020, 382, 610–621. [Google Scholar] [CrossRef] [PubMed]
  123. Siena, S.; Di Bartolomeo, M.; Raghav, K.; Masuishi, T.; Loupakis, F.; Kawakami, H.; Yamaguchi, K.; Nishina, T.; Fakih, M.; Elez, E.; et al. Trastuzumab deruxtecan (DS-8201) in patients with HER2-expressing metastatic colorectal cancer (DESTINY-CRC01): A multicentre, open-label, phase 2 trial. Lancet Oncol. 2021, 22, 779–789. [Google Scholar] [CrossRef]
  124. Yoshino, T.; Bartolomeo, M.D.; Raghav, K.P.S.; Masuishi, T.; Kawakami, H.; Yamaguchi, K.; Nishina, T.; Wainberg, Z.A.; Elez, E.; Rodriguez, J.; et al. Trastuzumab deruxtecan (T-DXd; DS-8201) in patients (pts) with HER2-expressing metastatic colorectal cancer (mCRC): Final results from a phase 2, multicenter, open-label study (DESTINY-CRC01). J. Clin. Oncol. 2022, 40, 119. [Google Scholar] [CrossRef]
  125. Raghav, K.P.S.; Yoshino, T.; Guimbaud, R.; Chau, I.; Eynde, M.V.D.; Maurel, J.; Tie, J.; Kim, T.W.; Yeh, K.-H.; Barrios, D.; et al. Trastuzumab deruxtecan in patients with HER2-overexpressing locally advanced, unresectable, or metastatic colorectal cancer (mCRC): A randomized, multicenter, phase 2 study (DESTINY-CRC02). J. Clin. Oncol. 2022, 40, TPS224. [Google Scholar] [CrossRef]
  126. Nakagawara, A. Trk receptor tyrosine kinases: A bridge between cancer and neural development. Cancer Lett. 2001, 169, 107–114. [Google Scholar] [CrossRef]
  127. Chao, M.V. Neurotrophins and their receptors: A convergence point for many signalling pathways. Nat. Rev. Neurosci. 2003, 4, 299–309. [Google Scholar] [CrossRef]
  128. Tognon, C.; Knezevich, S.R.; Huntsman, D.; Roskelley, C.D.; Melnyk, N.; Mathers, J.A.; Becker, L.; Carneiro, F.; MacPherson, N.; Horsman, D.; et al. Expression of the ETV6-NTRK3 gene fusion as a primary event in human secretory breast carcinoma. Cancer Cell 2002, 2, 367–376. [Google Scholar] [CrossRef] [Green Version]
  129. Vaishnavi, A.; Capelletti, M.; Le, A.T.; Kako, S.; Butaney, M.; Ercan, D.; Mahale, S.; Davies, K.D.; Aisner, D.L.; Pilling, A.B.; et al. Oncogenic and drug-sensitive NTRK1 rearrangements in lung cancer. Nat. Med. 2013, 19, 1469–1472. [Google Scholar] [CrossRef] [Green Version]
  130. Drilon, A.; Laetsch, T.W.; Kummar, S.; DuBois, S.G.; Lassen, U.N.; Demetri, G.D.; Nathenson, M.; Doebele, R.C.; Farago, A.F.; Pappo, A.S.; et al. Efficacy of Larotrectinib in TRK Fusion-Positive Cancers in Adults and Children. N. Engl. J. Med. 2018, 378, 731–739. [Google Scholar] [CrossRef]
  131. Scott, L.J. Larotrectinib: First Global Approval. Drugs 2019, 79, 201–206. [Google Scholar] [CrossRef]
  132. Drilon, A.; Ou, S.I.; Cho, B.C.; Kim, D.; Lee, J.; Lin, J.J.; Zhu, V.W.; Ahn, M.; Camidge, D.R.; Nguyen, J.; et al. Repotrectinib (TPX-0005) Is a Next-Generation ROS1/TRK/ALK Inhibitor That Potently Inhibits ROS1/TRK/ALK Solvent- Front Mutations. Cancer Discov. 2018, 8, 1227–1236. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  133. Papadopoulos, K.P.; Borazanci, E.; Shaw, A.T.; Katayama, R.; Shimizu, Y.; Zhu, V.W.; Sun, T.Y.; Wakelee, H.A.; Madison, R.; Schrock, A.B.; et al. U.S. Phase I First-in-human Study of Taletrectinib (DS-6051b/AB-106), a ROS1/TRK Inhibitor, in Patients with Advanced Solid Tumors. Clin. Cancer Res. 2020, 26, 4785–4794. [Google Scholar] [CrossRef]
  134. Wang, H.; Li, Z.W.; Ou, Q.; Wu, X.; Nagasaka, M.; Shao, Y.; Ou, S.I.; Yang, Y. NTRK fusion positive colorectal cancer is a unique subset of CRC with high TMB and microsatellite instability. Cancer Med. 2022, 11, 2541–2549. [Google Scholar] [CrossRef]
  135. Guo, Y.; Guo, X.-L.; Wang, S.; Chen, X.; Shi, J.; Wang, J.; Wang, K.; Klempner, S.J.; Wang, W.; Xiao, M. Genomic Alterations of NTRK, POLE, ERBB2, and Microsatellite Instability Status in Chinese Patients with Colorectal Cancer. Oncologist 2020, 25, e1671–e1680. [Google Scholar] [CrossRef]
  136. Lengyel, C.G.; Hussain, S.; Seeber, A.; Nidhamalddin, S.J.; Trapani, D.; Habeeb, B.S.; Elfaham, E.; Mazher, S.A.; Seid, F.; Khan, S.Z.; et al. FGFR Pathway Inhibition in Gastric Cancer: The Golden Era of an Old Target? Life 2022, 12, 81. [Google Scholar] [CrossRef] [PubMed]
  137. Lonic, A.; Barry, E.F.; Quach, C.; Kobe, B.; Saunders, N.; Guthridge, M.A. Fibroblast Growth Factor Receptor 2 Phosphorylation on Serine 779 Couples to 14-3-3 and Regulates Cell Survival and Proliferation. Mol. Cell. Biol. 2008, 28, 3372–3385. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  138. Mandal, S.; Bandyopadhyay, S.; Tyagi, K.; Roy, A. Recent advances in understanding the molecular role of phosphoinositide-specific phospholipase C gamma 1 as an emerging onco-driver and novel therapeutic target in human carcinogenesis. Biochim. Biophys. Acta Rev. Cancer 2021, 1876, 188619. [Google Scholar] [CrossRef]
  139. Lee, M.-S.; Cho, H.J.; Hong, J.Y.; Lee, J.; Park, S.H.; Park, J.O.; Park, Y.S.; Lim, H.Y.; Kang, W.K.; Cho, Y.B.; et al. Clinical and molecular distinctions in patients with refractory colon cancer who benefit from regorafenib treatment. Ther. Adv. Med. Oncol. 2020, 12, 1758835920965842. [Google Scholar] [CrossRef]
  140. Javle, M.; Roychowdhury, S.; Kelley, R.K.; Sadeghi, S.; Macarulla, T.; Weiss, K.H.; Waldschmidt, D.-T.; Goyal, L.; Borbath, I.; El-Khoueiry, A.; et al. Infigratinib (BGJ398) in previously treated patients with advanced or metastatic cholangiocarcinoma with FGFR2 fusions or rearrangements: Mature results from a multicentre, open-label, single-arm, phase 2 study. Lancet Gastroenterol. Hepatol. 2021, 6, 803–815. [Google Scholar] [CrossRef]
  141. Siefker-Radtke, A.O.; Necchi, A.; Park, S.H.; García-Donas, J.; A Huddart, R.; Burgess, E.F.; Fleming, M.T.; Kalebasty, A.R.; Mellado, B.; Varlamov, S.; et al. Efficacy and safety of erdafitinib in patients with locally advanced or metastatic urothelial carcinoma: Long-term follow-up of a phase 2 study. Lancet Oncol. 2022, 23, 248–258. [Google Scholar] [CrossRef]
  142. Meric-Bernstam, F.; Bahleda, R.; Hierro, C.; Sanson, M.; Bridgewater, J.; Arkenau, H.; Tran, B.; Kelley, R.K.; Park, J.O.; Javle, M.; et al. Futibatinib, an Irreversible FGFR1-4 Inhibitor, in Patients with Advanced Solid Tumors Harboring FGF/FGFR Aberrations: A Phase I Dose-Expansion Study. Cancer Discov. 2022, 12, 402–415. [Google Scholar] [CrossRef] [PubMed]
  143. Lord, C.J.; Ashworth, A. The DNA damage response and cancer therapy. Nature 2012, 481, 287–294. [Google Scholar] [CrossRef] [PubMed]
  144. Zimmer, K.; Kocher, F.; Puccini, A.; Seeber, A. Targeting BRCA and DNA Damage Repair Genes in GI Cancers: Pathophysiology and Clinical Perspectives. Front. Oncol. 2021, 11, 662055. [Google Scholar] [CrossRef] [PubMed]
  145. Naccarati, A.; Rosa, F.; Vymetalkova, V.; Barone, E.; Jiraskova, K.; Di Gaetano, C.; Novotny, J.; Levy, M.; Vodickova, L.; Gemignani, F.; et al. Double-strand break repair and colorectal cancer: Gene variants within 3′ UTRs and microRNAs binding as modulators of cancer risk and clinical outcome. Oncotarget 2015, 7, 23156–23169. [Google Scholar] [CrossRef] [Green Version]
  146. Venkitaraman, A.R. Cancer Susceptibility and the Functions of BRCA1 and BRCA2. Cell 2002, 108, 171–182. [Google Scholar] [CrossRef] [Green Version]
  147. Bryant, H.E.; Schultz, N.; Thomas, H.D.; Parker, K.M.; Flower, D.; Lopez, E.; Kyle, S.; Meuth, M.; Curtin, N.J.; Helleday, T. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature 2005, 434, 913–917. [Google Scholar] [CrossRef]
  148. Golan, T.; Hammel, P.; Reni, M.; Van Cutsem, E.; Macarulla, T.; Hall, M.J.; Park, J.O.; Hochhauser, D.; Arnold, D.; Oh, D.Y.; et al. Maintenance Olaparib for Germline BRCA-Mutated Metastatic Pancreatic Cancer. N. Engl. J. Med. 2019, 38, 317–327. [Google Scholar] [CrossRef] [PubMed]
  149. Knijnenburg, T.A.; Wang, L.; Zimmermann, M.T.; van Cutsem, E.; Macarulla, T.; Hall, M.J.; Park, J.; Hochhauser, D.; Arnold, D.; Oh, D.; et al. Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas. Cell Rep. 2018, 23, 239–254.e6. [Google Scholar] [CrossRef] [Green Version]
  150. Leichman, L.; Groshen, S.; O’Neil, B.H.; Messersmith, W.; Berlin, J.; Chan, E.; Leichman, C.G.; Cohen, S.J.; Cohen, D.; Lenz, H.; et al. Phase II Study of Olaparib (AZD-2281) After Standard Systemic Therapies for Disseminated Colorectal Cancer. Oncologist 2016, 21, 172–177. [Google Scholar] [CrossRef] [Green Version]
  151. Gorbunova, V.; Beck, J.T.; Hofheinz, R.D.; Garcia-Alfonso, P.; Nechaeva, M.; Gracian, A.C.; Mangel, L.; Fernandez, E.E.; Deming, D.A.; Ramanathan, R.K.; et al. A phase 2 randomised study of veliparib plus FOLFIRI±bevacizumab versus placebo plus FOLFIRI±bevacizumab in metastatic colorectal cancer. Br. J. Cancer 2019, 120, 183–189. [Google Scholar] [CrossRef] [Green Version]
  152. Pishvaian, M.J.; Slack, R.S.; Jiang, W.; He, A.R.; Hwang, J.J.; Hankin, A.; Dorsch-Vogel, K.; Kukadiya, D.; Weiner, L.M.; Marshall, J.L.; et al. A phase 2 study of the PARP inhibitor veliparib plus temozolomide in patients with heavily pretreated metastatic colorectal cancer. Cancer 2018, 124, 2337–2346. [Google Scholar] [CrossRef]
  153. Reilly, N.M.; Novara, L.; Di Nicolantonio, F.; Bardelli, A. Exploiting DNA repair defects in colorectal cancer. Mol. Oncol. 2019, 13, 681–700. [Google Scholar] [CrossRef]
  154. Pursell, Z.F.; Isoz, I.; Lundström, E.; Johansson, E.; Kunkel, T.A. Yeast DNA polymerase epsilon participates in leading-strand DNA replication. Science 2007, 317, 127–133. [Google Scholar] [CrossRef] [Green Version]
  155. Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature 2012, 487, 330–337. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  156. Hino, H.; Shiomi, A.; Kusuhara, M.; Kagawa, H.; Yamakawa, Y.; Hatakeyama, K.; Kawabata, T.; Oishi, T.; Urakami, K.; Nagashima, T.; et al. Clinicopathological and mutational analyses of colorectal cancer with mutations in the POLE gene. Cancer Med. 2019, 8, 4587–4597. [Google Scholar] [CrossRef] [Green Version]
  157. Mo, S.; Ma, X.; Li, Y.; Zhang, L.; Hou, T.; Han-Zhang, H.; Qian, J.; Cai, S.; Huang, D.; Peng, J. Somatic POLE exonuclease domain mutations elicit enhanced intratumoral immune responses in stage II colorectal cancer. J. Immunother. Cancer 2020, 8, e000881. [Google Scholar] [CrossRef] [PubMed]
  158. Domingo, E.; Freeman-Mills, L.; Rayner, E.; Glaire, M.; Briggs, S.; Vermeulen, L.; Fessler, E.; Medema, J.P.; Boot, A.; Morreau, H.; et al. Somatic POLE proofreading domain mutation, immune response, and prognosis in colorectal cancer: A retrospective, pooled biomarker study. Lancet Gastroenterol. Hepatol. 2016, 1, 207–216. [Google Scholar] [CrossRef] [Green Version]
  159. Rousseau, B.-C.; Bieche, I.; Pasmant, E.; Simmet, V.; Hamzaoui, N.; Masliah-Planchon, J.; Pouessel, D.; Bruyas, A.; Augereau, P.; Grob, J.-J.; et al. 526O High activity of nivolumab in patients with pathogenic exonucleasic domain POLE (edPOLE) mutated Mismatch Repair proficient (MMRp) advanced tumours. Ann. Oncol. 2020, 31, S463. [Google Scholar] [CrossRef]
  160. Oh, C.R.; Kim, J.E.; Hong, Y.S.; Kim, S.Y.; Ahn, J.B.; Baek, J.Y.; Lee, M.; Kang, M.J.; Cho, S.H.; Beom, S.; et al. Phase II study of durvalumab monotherapy in patients with previously treated microsatellite instability-high/mismatch repair-deficient or POLE -mutated metastatic or unresectable colorectal cancer. Int. J. Cancer 2022, 150, 2038–2045. [Google Scholar] [CrossRef]
  161. Huyghe, N.; Benidovskaya, E.; Stevens, P.; Van den Eynde, M. Biomarkers of Response and Resistance to Immunotherapy in Microsatellite Stable Colorectal Cancer: Toward a New Personalized Medicine. Cancers 2022, 14, 2241. [Google Scholar] [CrossRef]
  162. Romei, C.; Ciampi, R.; Elisei, R. A comprehensive overview of the role of the RET proto-oncogene in thyroid carcinoma. Nat. Rev. Endocrinol. 2016, 12, 192–202. [Google Scholar] [CrossRef] [PubMed]
  163. Kohno, T.; Ichikawa, H.; Totoki, Y.; Yasuda, K.; Hiramoto, M.; Nammo, T.; Sakamoto, H.; Tsuta, K.; Furuta, K.; Shimada, Y.; et al. KIF5B-RET fusions in lung adenocarcinoma. Nat. Med. 2012, 18, 375–377. [Google Scholar] [CrossRef] [PubMed]
  164. Le Rolle, A.F.; Klempner, S.J.; Garrett, C.R.; Seery, T.; Sanford, E.M.; Balasubramanian, S.; Ross, J.S.; Stephens, P.J.; Miller, V.A.; Ali, S.M.; et al. Identification and characterization of RET fusions in advanced colorectal cancer. Oncotarget 2015, 6, 28929–28937. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  165. Kim, S.Y.; Oh, S.O.; Kim, K.; Lee, J.; Kang, S.; Kim, K.; Lee, W.; Kim, S.T.; Nam, D.N. NCOA4-RET fusion in colorectal cancer: Therapeutic challenge using patient-derived tumor cell lines. J. Cancer 2018, 9, 3032–3037. [Google Scholar] [CrossRef] [Green Version]
  166. Pietrantonio, F.; Di Nicolantonio, F.; Schrock, A.; Lee, J.; Morano, F.; Fucà, G.; Nikolinakos, P.; Drilon, A.; Hechtman, J.; Christiansen, J.; et al. RET fusions in a small subset of advanced colorectal cancers at risk of being neglected. Ann. Oncol. 2018, 29, 1394–1401. [Google Scholar] [CrossRef]
  167. Randon, G.; Maddalena, G.; Germani, M.M.; Pircher, C.C.; Manca, P.; Bergamo, F.; Giordano, M.; Sposetti, C.; Montagna, A.; Vetere, G.; et al. Negative Ultraselection of Patients With RAS/BRAF Wild-Type, Microsatellite-Stable Metastatic Colorectal Cancer Receiving Anti-EGFR-Based Therapy. JCO Precis. Oncol. 2022, 6, e2200037. [Google Scholar] [CrossRef]
  168. Michael, M.; Gibbs, P.; Smith, R.; Godwood, A.; Oliver, S.; Tebbutt, N. Open-label phase I trial of vandetanib in combination with mFOLFOX6 in patients with advanced colorectal cancer. Investig. New Drugs 2008, 27, 253–261. [Google Scholar] [CrossRef]
  169. Iwasa, S.; Okita, N.; Kuchiba, A.; Ogawa, G.; Kawasaki, M.; Nakamura, K.; Shoji, H.; Honma, Y.; Takashima, A.; Kato, K.; et al. Phase II study of lenvatinib for metastatic colorectal cancer refractory to standard chemotherapy: The LEMON study (NCCH1503). ESMO Open 2020, 5, e000776. [Google Scholar] [CrossRef] [PubMed]
  170. Gozgit, J.M.; Chen, T.-H.; Song, Y.; Wardwell, S.; Wang, F.; Cai, J.; Li, H.; Edgren, H.; Rivera, V.M.; Pritchard, J. RET fusions observed in lung and colorectal cancers are sensitive to ponatinib. Oncotarget 2018, 9, 29654–29664. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  171. NCT03157128: A Study of Selpercatinib (LOXO-292) in Participants with Advanced Solid Tumors, RET Fusion-Positive Solid Tumors, and Medullary Thyroid Cancer (LIBRETTO-001). Available online: https://clinicaltrials.gov/ct2/show/NCT03157128 (accessed on 14 July 2022).
  172. NCT03037385: Phase 1/2 Study of the Highly-selective RET Inhibitor, Pralsetinib (BLU-667), in Participants With Thyroid Cancer, Non-Small Cell Lung Cancer, and Other Advanced Solid Tumors (ARROW). Available online: https://clinicaltrials.gov/ct2/show/NCT03037385 (accessed on 14 July 2022).
  173. Sansom, O.J.; Reed, K.R.; Hayes, A.J.; Ireland, H.; Brinkmann, H.; Newton, I.P.; Batlle, E.; Simon-Assmann, P.; Clevers, H.; Nathke, I.S.; et al. Loss of Apc in vivo immediately perturbs Wnt signaling, differentiation, and migration. Genes Dev. 2004, 18, 1385–1390. [Google Scholar] [CrossRef] [Green Version]
  174. Berger, M.D.; Ning, Y.; Stintzing, S.; Heinemann, V.; Cao, S.; Zhang, W.; Yang, D.; Miyamoto, Y.; Suenaga, M.; Schirripa, M.; et al. A polymorphism within the R-spondin 2 gene predicts outcome in metastatic colorectal cancer patients treated with FOLFIRI/bevacizumab: Data from FIRE-3 and TRIBE trials. Eur. J. Cancer 2020, 131, 89–97. [Google Scholar] [CrossRef]
  175. Cheng, X.; Xu, X.; Chen, D.; Zhao, F.; Wang, W. Therapeutic potential of targeting the Wnt/β-catenin signaling pathway in colorectal cancer. Biomed. Pharmacother. 2018, 110, 473–481. [Google Scholar] [CrossRef] [PubMed]
  176. Giannakis, M.; Hodis, E.; Mu, X.J.; Yamauchi, M.; Rosenbluh, J.; Cibulskis, K.; Saksena, G.; Lawrence, M.S.; Qian, Z.R.; Nishihara, R.; et al. RNF43 is frequently mutated in colorectal and endometrial cancers. Nat. Genet. 2014, 46, 1264–1266. [Google Scholar] [CrossRef] [PubMed]
  177. Seshagiri, S.; Stawiski, E.W.; Durinck, S.; Modrusan, Z.; Storm, E.E.; Conboy, C.B.; Chaudhuri, S.; Guan, Y.; Janakiraman, V.; Jaiswal, B.S.; et al. Recurrent R-spondin fusions in colon cancer. Nature 2012, 488, 660–664. [Google Scholar] [CrossRef] [Green Version]
  178. Seeber, A.; Battaglin, F.; Zimmer, K.; Kocher, F.; Baca, Y.; Xiu, J.; Spizzo, G.; Novotny-Diermayr, V.; Rieder, D.; Puccini, A.; et al. Comprehensive analysis of R-spondin fusions and RNF43 mutations implicate novel therapeutic options in colorectal cancer. Clin. Cancer Res. 2022, 28, 1863–1870. [Google Scholar] [CrossRef]
  179. NCT03604445: This Study Aims to Find and Test a Safe Dose of BI 905677 in Patients with Different Types of Cancer (Solid Tumors). Available online: https://clinicaltrials.gov/ct2/show/NCT03604445 (accessed on 14 July 2022).
  180. Berger, M.D.; Stintzing, S.; Heinemann, V.; Yang, D.; Cao, S.; Sunakawa, Y.; Ning, Y.; Matsusaka, S.; Okazaki, S.; Miyamoto, Y.; et al. Impact of genetic variations in the MAPK signaling pathway on outcome in metastatic colorectal cancer patients treated with first-line FOLFIRI and bevacizumab: Data from FIRE-3 and TRIBE trials. Ann. Oncol. 2017, 28, 2780–2785. [Google Scholar] [CrossRef]
  181. Berger, M.D.; Stintzing, S.; Heinemann, V.; Cao, S.; Yang, D.; Sunakawa, Y.; Matsusaka, S.; Ning, Y.; Okazaki, S.; Miyamoto, Y.; et al. A Polymorphism within the Vitamin D Transporter Gene Predicts Outcome in Metastatic Colorectal Cancer Patients Treated with FOLFIRI/Bevacizumab or FOLFIRI/Cetuximab. Clin. Cancer Res. 2018, 24, 784–793. [Google Scholar] [CrossRef] [Green Version]
  182. Anderson, N.M.; Simon, M.C. The tumor microenvironment. Curr. Biol. 2020, 30, R921–R925. [Google Scholar] [CrossRef] [PubMed]
  183. Kumar, V.; Patel, S.; Tcyganov, E.; Gabrilovich, D.I. The Nature of Myeloid-Derived Suppressor Cells in the Tumor Microenvironment. Trends Immunol. 2016, 37, 208–220. [Google Scholar] [CrossRef] [Green Version]
  184. Zhou, J.; Tang, Z.; Gao, S.; Li, C.; Feng, Y.; Zhou, X. Tumor-Associated Macrophages: Recent Insights and Therapies. Front. Oncol. 2020, 10, 188. [Google Scholar] [CrossRef]
  185. Pagès, F.; Mlecnik, B.; Marliot, F.; Bindea, G.; Ou, F.; Bifulco, C.; Lugli, A.; Zlobec, I.; Rau, T.T.; Berger, M.D.; et al. International validation of the consensus Immunoscore for the classification of colon cancer: A prognostic and accuracy study. Lancet 2018, 391, 2128–2139. [Google Scholar] [CrossRef]
  186. Galon, J.; Mlecnik, B.; Hermitte, F.; Bifulco, C.; Lugli, A.; Nagtegaal, I.D.; Hartmann, A.; van den Eynde, M.; Roehrl, M.; Ohashi, P.; et al. MSI status plus immunoscore to select metastatic colorectal cancer patients for immunotherapies. Ann. Oncol. 2018, 29 (Suppl. 10), X4. [Google Scholar] [CrossRef]
  187. Baldin, P.; Eynde, M.V.D.; Mlecnik, B.; Galon, J. Immunity to live: An immunopathoscore using the consensus Immunoscore to best define the risk of recurrence and death in stage IV metastatic patients. OncoImmunology 2020, 9, 1826133. [Google Scholar] [CrossRef]
  188. Guinney, J.; Dienstmann, R.; Wang, X.; De Reyniès, A.; Schlicker, A.; Soneson, C.; Marisa, L.; Roepman, P.; Nyamundanda, G.; Angelino, P.; et al. The consensus molecular subtypes of colorectal cancer. Nat. Med. 2015, 21, 1350–1356. [Google Scholar] [CrossRef]
  189. Becht, E.; de Reyniès, A.; Giraldo, N.A.; Pilati, C.; Buttard, B.; Lacroix, L.; Selves, J.; Sautès-Fridman, C.; Laurent-Puig, P.; Fridman, W.H.; et al. Immune and stromal classification of colorectal cancer is associated with molecular subtypes and relevant for precision Immunotherapy. Clin. Cancer Res. 2016, 22, 4057. [Google Scholar] [CrossRef] [Green Version]
  190. Lenz, H.-J.; Ou, F.-S.; Venook, A.P.; Hochster, H.S.; Niedzwiecki, D.; Goldberg, R.M.; Mayer, R.J.; Bertagnolli, M.M.; Blanke, C.D.; Zemla, T.; et al. Impact of Consensus Molecular Subtype on Survival in Patients With Metastatic Colorectal Cancer: Results From CALGB/SWOG 80405 (Alliance). J. Clin. Oncol. 2019, 37, 1876–1885. [Google Scholar] [CrossRef] [PubMed]
  191. Stintzing, S.; Wirapati, P.; Lenz, H.J.; Neureiter, D.; von Weikersthal, L.F.; Decker, T.; Kiani, A.; Kaiser, F.; Al-Batran, S.; Heintges, T.; et al. Consensus molecular subgroups (CMS) of colorectal cancer (CRC) and first-line efficacy of FOLFIRI plus cetuximab or bevacizumab in the FIRE-3 (AIO KRK-0306) trial. Ann. Oncol. 2019, 30, 1796–1803. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  192. Tie, J.; Kinde, I.; Wang, Y.; Wong, H.L.; Roebert, J.; Christie, M.; Tacey, M.; Wong, R.; Singh, M.; Karapetis, C.S.; et al. Circulating tumor DNA as an early marker of therapeutic response in patients with metastatic colorectal cancer. Ann. Oncol. 2015, 26, 1715–1722. [Google Scholar] [CrossRef]
  193. Bettegowda, C.; Sausen, M.; Leary, R.J.; Kinde, I.; Wang, Y.; Agrawal, N.; Bartlett, B.R.; Wang, H.; Luber, B.; Alani, R.M.; et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 2014, 6, 224ra224. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  194. Arisi, M.F.; Dotan, E.; Fernandez, S.V. Circulating Tumor DNA in Precision Oncology and Its Applications in Colorectal Cancer. Int. J. Mol. Sci. 2022, 23, 4441. [Google Scholar] [CrossRef]
  195. Tarazona, N.; Gimeno-Valiente, F.; Gambardella, V.; Zuniga, S.; Rentero-Garrido, P.; Huerta, M.; Rosello, S.; Martinez-Ciarpaglini, C.; Carbonell-Asins, J.A.; Carrasco, F.; et al. Targeted next-generation sequencing of circulating-tumor DNA for tracking minimal residual disease in localized colon cancer. Ann. Oncol. 2019, 30, 1804–1812. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  196. Tie, J.; Cohen, J.D.; Lahouel, K.; Lo, S.N.; Wang, Y.; Kosmider, S.; Wong, R.; Shapiro, J.; Lee, M.; Harris, S.; et al. Circulating Tumor DNA Analysis Guiding Adjuvant Therapy in Stage II Colon Cancer. N. Engl. J. Med. 2022, 386, 2261–2272. [Google Scholar] [CrossRef] [PubMed]
  197. Chin, R.I.; Chen, K.; Usmani, A.; Chua, C.; Harris, P.K.; Binkley, M.S.; Azad, T.D.; Dudley, J.C.; Chaudhuri, A.A. Detection of Solid Tumor Molecular Residual Disease (MRD) Using Circulating Tumor DNA (ctDNA). Mol. Diagn. Ther. 2019, 23, 311–331. [Google Scholar] [CrossRef] [PubMed]
  198. Siravegna, G.; Mussolin, B.; Buscarino, M.; Corti, G.; Cassingena, A.; Crisafulli, G.; Ponzetti, A.; Cremolini, C.; Amatu, A.; Lauricella, C.; et al. Clonal evolution and resistance to EGFR blockade in the blood of colorectal cancer patients. Nat. Med. 2015, 21, 827. [Google Scholar] [CrossRef]
  199. Ooft, S.; Weeber, F.; Schipper, L.; Dijkstra, K.; McLean, C.; Kaing, S.; van de Haar, J.; Prevoo, W.; van Werkhoven, E.; Snaebjornsson, P.; et al. Prospective experimental treatment of colorectal cancer patients based on organoid drug responses. ESMO Open 2021, 6, 100103. [Google Scholar] [CrossRef]
  200. Vlachogiannis, G.; Hedayat, S.; Vatsiou, A.; Jamin, Y.; Fernández-Mateos, J.; Khan, K.; Lampis, A.; Eason, K.; Huntingford, I.; Burke, R.; et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science 2018, 359, 920–926. [Google Scholar] [CrossRef] [Green Version]
  201. Narasimhan, V.; Wright, J.A.; Churchill, M.; Wang, T.; Rosati, R.; Lannagan, T.R.M.; Vrbanac, L.; Richardson, A.B.; Kobayashi, H.; Price, T.; et al. Medium-throughput Drug Screening of Patient-derived Organoids from Colorectal Peritoneal Metastases to Direct Personalized Therapy. Clin. Cancer Res. 2020, 26, 3662–3670. [Google Scholar] [CrossRef]
  202. Wensink, G.E.; Elias, S.G.; Mullenders, J.; Koopman, M.; Boj, S.F.; Kranenburg, O.W.; Roodhart, J.M.L. Patient-derived organoids as a predictive biomarker for treatment response in cancer patients. NPJ Precis. Oncol. 2021, 5, 30. [Google Scholar] [CrossRef]
  203. Rizzo, G.; Bertotti, A.; Leto, S.M.; Vetrano, S. Patient-derived tumor models: A more suitable tool for pre-clinical studies in colorectal cancer. J. Exp. Clin. Cancer Res. 2021, 40, 178. [Google Scholar] [CrossRef]
  204. Voabil, P.; de Bruijn, M.; Roelofsen, L.M.; Hendriks, S.H.; Brokamp, S.; van den Braber, M.; Broeks, A.; Sanders, J.; Herzig, P.; Zippelius, A.; et al. An ex vivo tumor fragment platform to dissect response to PD-1 blockade in cancer. Nat. Med. 2021, 27, 1250–1261. [Google Scholar] [CrossRef]
  205. Stintzing, S.; Modest, D.P.; Rossius, L.; Lerch, M.M.; von Weikersthal, L.F.; Decker, T.; Kiani, A.; Vehling-Kaiser, U.; Al-Batran, S.; Heintges, T.; et al. FOLFIRI plus cetuximab versus FOLFIRI plus bevacizumab for metastatic colorectal cancer (FIRE-3): A post-hoc analysis of tumour dynamics in the final RAS wild-type subgroup of this randomised open-label phase 3 trial. Lancet Oncol. 2016, 17, 1426–1434. [Google Scholar] [CrossRef]
  206. Spizzo, G.; Siebert, U.; Gastl, G.; Voss, A.; Schuster, K.; Leonard, R.; Seeber, A. Cost-comparison analysis of a multiplatform tumour profiling service to guide advanced cancer treatment. Cost Eff. Resour. Alloc. 2019, 17, 23. [Google Scholar] [CrossRef] [PubMed]
  207. Wolff, H.B.; Steeghs, E.M.; Mfumbilwa, Z.A.; Groen, H.J.; Adang, E.M.; Willems, S.M.; Grünberg, K.; Schuuring, E.; Ligtenberg, M.J.; Tops, B.B.; et al. Cost-Effectiveness of Parallel Versus Sequential Testing of Genetic Aberrations for Stage IV Non–Small-Cell Lung Cancer in the Netherlands. JCO Precis. Oncol. 2022, 6, e2200201. [Google Scholar] [CrossRef]
  208. Banerjee, S.; Kumar, A.; Lopez, N.; Zhao, B.; Tang, C.; Yebra, M.; Yoon, H.; Murphy, J.D.; Sicklick, J.K. Cost-effectiveness Analysis of Genetic Testing and Tailored First-Line Therapy for Patients With Metastatic Gastrointestinal Stromal Tumors. JAMA Netw Open 2020, 3, e2013565. [Google Scholar] [CrossRef]
  209. Doble, B.; John, T.; Thomas, D.; Fellowes, A.; Fox, S.; Lorgelly, P. Cost-effectiveness of precision medicine in the fourth-line treatment of metastatic lung adenocarcinoma: An early decision analytic model of multiplex targeted sequencing. Lung Cancer 2017, 107, 22–35. [Google Scholar] [CrossRef]
  210. Schwarze, K.; Buchanan, J.; Taylor, J.C.; Wordsworth, S. Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature. Genet. Med. 2018, 20, 1122–1130. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  211. Park, J.J.H.; Hsu, G.; Siden, E.G.; Thorlund, K.; Mills, E.J. An overview of precision oncology basket and umbrella trials for clinicians. CA Cancer J. Clin. 2020, 70, 125–137. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  212. NCT03256344. Study of Talimogene Laherparepvec with Atezolizumab for Triple Negative Breast Cancer and Colorectal Cancer with Liver Metastases. Available online: https://clinicaltrials.gov/ct2/show/NCT03256344 (accessed on 6 August 2022).
  213. NCT05120596. First in Human Study of T3P-Y058-739 (T3P). Available online: https://clinicaltrials.gov/ct2/show/NCT05120596 (accessed on 6 August 2022).
  214. Budinska, E.; Popovici, V.; Tejpar, S.; D’Ario, G.; Lapique, N.; Sikora, K.O.; Di Narzo, A.F.; Yan, P.; Hodgson, J.G.; Weinrich, S.; et al. Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer. J. Pathol. 2013, 231, 63–76. [Google Scholar] [CrossRef]
  215. Sadanandam, A.; Lyssiotis, C.A.; Homicsko, K.; Collisson, E.A.; Gibb, W.J.; Wullschleger, S.; Ostos, L.C.G.; Lannon, W.A.; Grötzinger, C.; Del Rio, M.; et al. A colorectal cancer classification system that associates cellular phenotype and responses to therapy. Nat. Med. 2013, 19, 619–625. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  216. Overacre-Delgoffe, A.E.; Bumgarner, H.J.; Cillo, A.R.; Burr, A.H.; Tometich, J.T.; Bhattacharjee, A.; Bruno, T.C.; Vignali, D.A.; Hand, T.W. Microbiota-specific T follicular helper cells drive tertiary lymphoid structures and anti-tumor immunity against colorectal cancer. Immunity 2021, 54, 2812–2824.e4. [Google Scholar] [CrossRef]
  217. Kadosh, E.; Snir-Alkalay, I.; Venkatachalam, A.; May, S.; Lasry, A.; Elyada, E.; Zinger, A.; Shaham, M.; Vaalani, G.; Mernberger, M.; et al. The gut microbiome switches mutant p53 from tumour-suppressive to oncogenic. Nature 2020, 586, 133–138. [Google Scholar] [CrossRef] [PubMed]
  218. Liu, L.; Shah, K. The Potential of the Gut Microbiome to Reshape the Cancer Therapy Paradigm: A Review. JAMA Oncol. 2022, 8, 1059–1067. [Google Scholar] [CrossRef] [PubMed]
  219. Sivan, A.; Corrales, L.; Hubert, N.; Williams, J.B.; Aquino-Michaels, K.; Earley, Z.M.; Benyamin, F.W.; Lei, Y.M.; Jabri, B.; Alegre, M.L.; et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science 2015, 350, 1084–1089. [Google Scholar] [CrossRef] [Green Version]
  220. Wong, S.H.; Yu, J. Gut microbiota in colorectal cancer: Mechanisms of action and clinical applications. Nat. Rev. Gastroenterol. Hepatol. 2019, 16, 690–704. [Google Scholar] [CrossRef] [PubMed]
Table 1. Selection of requirements for an effective prognostic or predictive biomarker *.
Table 1. Selection of requirements for an effective prognostic or predictive biomarker *.
Prediction with high accuracy [19,20]
Cost effective [19,21]
Easy to assess [20,21]
Reproducible/Reliable [19,21]
Consistent and rapid turnaround time [22]
Prognostic/predictive impact confirmed in validation sets [19,20,21]
Proven useful in a given clinical context [19,20]
Longitudinal and non-invasive measurements [23]
* This selection reflects the authors’ opinions and is not intended to be exhaustive.
Table 2. Evidence of established biomarkers in metastatic colorectal cancer patients in selected clinical trials.
Table 2. Evidence of established biomarkers in metastatic colorectal cancer patients in selected clinical trials.
BiomarkerTrialPhaseNSettingTreatmentOutcomes
Sidedness
(retrospective analyses, except PARADIGM)
CALGB/SWOG 80405III476First-line mCRCFOLFOX/FOLFIRI + cetuximab vs.
FOLFOX/FOLFIRI + bevacizumab
mOS right 16.4 vs. 24.5 months
mOS left 37.5 vs. 32.1 months
FIRE-3III394First-line mCRCFOLFIRI + cetuximab vs. FOLFIRI + bevacizumabmOS right 18.3 vs. 23.0 months
mOS left 38.3 vs. 28.0 months
PEAKII143First-line mCRCFOLFOX + panitumumab vs.
FOLFOX + bevacizumab
mOS right 17.5 vs. 21.0 months
mOS left 43.4 vs. 32.0 months
PARADIGMIII802First-line mCRCFOLFOX + panitumumab vs.
FOLFOX + bevacizumab
mOS right 20.2 vs. 23.2 months
mOS left 37.9 vs. 34.3 months
CRYSTALIII364First-line mCRCFOLFIRI + cetuximab vs. FOLFIRImOS right 18.5 vs. 15.0 months
mOS left 28.7 vs. 21.7 months
PRIMEIII408First-line mCRCFOLFOX + panitumumab vs. FOLFOXmOS right 11.1 vs. 15.4 months
mOS left 30.3 vs. 23.6 months
dMMR/MSI-HKEYNOTE-164II124MSI-H/dMMR
mCRC treated with ≥2 prior lines of standard
therapy
PembrolizumabPFS 31% at 24 months
OS 55% at 24 months
CheckMate-142II74MSI-H/dMMR
mCRC who had ≥ 1 prior treatment
NivolumabPFS 36% at 48 months
OS 49% at 48 months
CheckMate-142II119MSI-H/dMMR mCRC who had ≥1 prior treatmentNivolumab 3 mg/kg + ipilimumab
1 mg/kg q3w × 4 followed by nivolumab 3 mg/kg q2w
PFS 53% at 48 months
OS 71% at 48 months
KEYNOTE-177III307First-line MSI-H/dMMRmCRCPembrolizumabmPFS 16.5 months
mOS not reached
RASCRYSTALIII retrospective analysis of 827 pts evaluable for RAS mutational status First-line mCRCFOLFIRI vs. FOLFIRI + cetuximabRAS wild-type
mOS 20.2 vs. 28.4 months, HR 0.69
RAS mutant
mOS 17.7 vs. 16.4 months, HR 1.05
PRIMEIII656 First-line mCRC KRAS wild-typeFOLFOX vs. FOLFOX + panitumumab mOS 19.4 vs. 23.8 months, HR 0.83
PARADIGMIII604First-line mCRC RAS wild-type left-sidedFOLFOX + bevacizumab vs. FOLFOX + panitumumabmOS 34.3 vs. 37.9 months, HR 0.82
KRASG12CCodeBreak 100II62Refractory mCRCSotorasibORR 9.7%, DCR 82.3%
KRYSTAL-1I/II46Refractory mCRCAdagrasibORR 22%, DCR 87%
BRAFV600EBEACONIII665Refractory mCRCEncorafenib + binimetinib +
cetuximab vs. encorafenib +
cetuximab vs. FOLFIRI or cetuximab + irinotecan
mPFS 4.5 vs. 4.3 vs. 1.5 months
mOS 9.3 vs. 9.3 vs. 5.9 months
HER2HERACLESII27Refractory mCRCLapatinib + trastuzumabORR 30%
HERACLES-BII31Refractory mCRCPertuzumab + trastuzumab-emtansineORR 9.7%
MyPathwayII43Refractory mCRC
KRAS wild-type
Pertuzumab + trastuzumabmPFS 5.3 months
mOS 14.0 months
ORR 40%
TRIUMPHII27Refractory mCRCPertuzumab + trastuzumabmPFS 4.0 months
mOS 10.1 months
ORR 30%
MOUNTAINEERII26Refractory mCRCTucatinib + trastuzumabmPFS 6.2 months
mOS 17.3 months
ORR 55%
DESTINY-CRC01II53Refractory mCRCTrastuzumab-deruxtecanmPFS 6.9 months
mOS 15.5 months
ORR 45.3%
NTRKNAVIGATEII10Refractory mCRC NTRK fusion-positiveLarotrectinibmPFS 5.5 months
mOS 29.4 months
ORR 50%
ALKA-372-001, STARTRK-1, and STARTRK-2I/II4mCRC NTRK fusion-positiveEntrectinibORR 25%
DCR, disease control rate; FOLFIRI, 5-fluorouracil + irinotecan; FOLFOX, 5-fluorouracil + oxaliplatin; dMMR, DNA mismatch repair deficiency; mCRC, metastatic colorectal cancer; MSI-H, microsatellite instability high; OS, overall survival; ORR, objective response rate; PFS, progression-free survival.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Puccini, A.; Seeber, A.; Berger, M.D. Biomarkers in Metastatic Colorectal Cancer: Status Quo and Future Perspective. Cancers 2022, 14, 4828. https://doi.org/10.3390/cancers14194828

AMA Style

Puccini A, Seeber A, Berger MD. Biomarkers in Metastatic Colorectal Cancer: Status Quo and Future Perspective. Cancers. 2022; 14(19):4828. https://doi.org/10.3390/cancers14194828

Chicago/Turabian Style

Puccini, Alberto, Andreas Seeber, and Martin D. Berger. 2022. "Biomarkers in Metastatic Colorectal Cancer: Status Quo and Future Perspective" Cancers 14, no. 19: 4828. https://doi.org/10.3390/cancers14194828

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop