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Review

Current Applications of Liquid Biopsy in Gastrointestinal Cancer Disease—From Early Cancer Detection to Individualized Cancer Treatment

by
Paul David
1,
Anke Mittelstädt
1,
Dina Kouhestani
1,
Anna Anthuber
1,
Christoph Kahlert
2,
Kai Sohn
3 and
Georg F. Weber
1,4,*
1
Department of Surgery, University Hospital of Erlangen, Friedrich-Alexander University (FAU) Erlangen-Nürnberg, 91054 Erlangen, Germany
2
Department of Surgery, Carl Gustav Carus University Hospital, 01307 Dresden, Germany
3
Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB, 70569 Stuttgart, Germany
4
Deutsches Zentrum für Immuntherapie, University Hospital of Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, 91054 Erlangen, Germany
*
Author to whom correspondence should be addressed.
Cancers 2023, 15(7), 1924; https://doi.org/10.3390/cancers15071924
Submission received: 21 February 2023 / Revised: 20 March 2023 / Accepted: 21 March 2023 / Published: 23 March 2023
(This article belongs to the Special Issue Liquid Biopsy in Gastrointestinal Cancer Disease—from Bench to Beside)
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Abstract

:

Simple Summary

Gastrointestinal (GI) cancers are a common cancer, affecting both men and women, normally diagnosed through tissue biopsies in combination with imaging techniques and standardized biomarkers leading to patient selection for local or systemic therapies. Liquid biopsies (LBs)—due to their non-invasive nature as well as low risk—are the current focus of cancer research and could be a promising tool for early cancer detection and treatment surveillance, thus leading to better patient outcomes. In this review, we provide an overview of different types of LBs enabling early detection and monitoring of GI cancers and their clinical application.

Abstract

Worldwide, gastrointestinal (GI) cancers account for a significant amount of cancer-related mortality. Tests that allow an early diagnosis could lead to an improvement in patient survival. Liquid biopsies (LBs) due to their non-invasive nature as well as low risk are the current focus of cancer research and could be a promising tool for early cancer detection. LB involves the sampling of any biological fluid (e.g., blood, urine, saliva) to enrich and analyze the tumor’s biological material. LBs can detect tumor-associated components such as circulating tumor DNA (ctDNA), extracellular vesicles (EVs), and circulating tumor cells (CTCs). These components can reflect the status of the disease and can facilitate clinical decisions. LBs offer a unique and new way to assess cancers at all stages of treatment, from cancer screenings to prognosis to management of multidisciplinary therapies. In this review, we will provide insights into the current status of the various types of LBs enabling early detection and monitoring of GI cancers and their use in in vitro diagnostics.

1. Introduction

Gastrointestinal (GI) cancers are responsible for more cancer-related deaths than lung and breast cancer. Colorectal cancer (CRC) is the major type of GI cancer, with 1.9 million new cases diagnosed worldwide in 2020, making it after lung and breast cancer the third most common cancer of all organs. According to the International Agency for Research on Cancer, in the same year, 1.1 million new cases of gastric cancer, 900,000 new cases of liver cancer, 600,000 new cases of esophageal cancer, and 500,000 new cases of pancreatic cancer were diagnosed across the globe [1].
Although the prognosis of many GI cancers has improved over the past decades [2,3], a late cancer diagnosis is still the leading reason for cancer-related deaths among all GI cancers [4]. Current research focuses therefore on improving early cancer diagnosis, possibly leading to better outcomes among all GI cancers [5,6]. So far, endoscopic or CT-guided solid biopsies in combination with so-called serum-based tumor biomarkers are primary methods for the diagnosis of GI cancers [7]. Thereby, solid biopsies are considered the gold standard strategy capable of classifying tumors, identifying the mutational status, and providing prognostic information. However, these methods have some limitations, e.g., obtaining insufficient or inaccurate tissue samples possibly leading to false-positive or false-negative results. In addition, tissue biopsies might cause harm to the patient. However, recent studies suggest tissue biopsies taken from a single cancer nodule or single metastatic lesion may fail to represent the entire tumor heterogeneity within the patient, possibly being one of the main reasons for the failure of current targeted therapies [8,9,10,11,12,13]. To date, several serum-based biomarkers such as carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4), carbohydrate antigen 125 (CA125), and alpha-feto protein (AFP) have been identified and widely used for diagnosis, prognosis, and monitoring of potential recurrence of GI cancers [14,15]. Although, due to the limit of specificity and sensitivity most of these biomarkers are not useful for early cancer detection [16]. Therefore, LB emerged as a promising tool for early detection, treatment selection, and real-time prognosis.
In contrast to solid biopsy, LB is a minimally invasive approach enabling the real-time monitoring and early uncovering of alterations in cells or cell products shed from malignant lesions into the body fluids (Figure 1). LB analysis can identify multiple heterogeneous resistance mechanisms in single patients compared to solid biopsy. Furthermore, LB facilitates the choice of the right treatment and observation of the treatment response. Due to the minimally invasive nature of LB, the resulting complications from obtaining solid biopsies could be prevented. A typical LB sample is taken from any biological fluid such as blood, saliva, cerebrospinal fluid, or urine. LB materials derived from peripheral blood have been investigated extensively. LB analysis from blood contains enrichment and isolation of CTCs, circulating blood platelets, ctDNA, and other tumor genetic material such as extracellular vesicles. As of today, several LB technologies have been approved by the United States Food and Drug Administration (FDA) for malignancies such as metastatic lung, breast, prostate, or colorectal cancer: CELLSEARCH CTC test using circulating tumor cells from Veridex, Guardant360 CDx, and FoundationOne Liquid CDx using circulating cell-free DNA (cfDNA) and next-generation sequencing to detect tumor-specific mutations.
Due to the crucial role of LB markers, our main focus is on research findings and clinical applications in gastrointestinal cancers.

2. Overview of Different Methodologies and Their Current Clinical Application

2.1. Circulating Tumor Cells (CTCs)

CTCs are tumor cells, shed from a primary tumor. They can enter the bloodstream or lymphatic system, potentially spreading into distant organs possibly leading to metastases [17,18]. Nevertheless, only a minority of CTCs become solid metastatic lesions because of a complex sequence of events needed, i.e., the detachment from the primary tumor, migration through the circulating blood, immune escape, and survival. It remains unclear how the detachment process from the primary tumor tissue takes place. Evidence supports the involvement of epithelial to mesenchymal transition, by which transformed epithelial cells can acquire the ability to invade, resist apoptosis, and disseminate. This could be the main driver for the detachment of tumor cells from the primary tumor [19,20,21,22,23,24]. Other reports hypothesize that cells split into different clusters [25]. It is noteworthy that gastrointestinal cancers compared to breast cancer have lower numbers of CTCs in peripheral blood due to portal vein circulations and a steady ‘first-pass effect’ in the liver [26]. Therefore, portal vein blood might be a unique sample site to isolate CTCs from gastrointestinal cancers. It has already been shown that the number of enriched CTCs from portal vein blood is higher than in the systemic circulation [27,28]. Portal vein blood can be collected intraoperatively or even by endoscopic ultrasound (EUS)-guided sampling [29].
In addition to the number of CTCs, the analysis of physical (size, density, and electric charge) and biological (cell surface expression) properties could play a crucial role in future clinical use [30].

2.1.1. Isolation and Enrichment of CTCs

The isolation and enrichment of CTCs are technically challenging because of their low numbers and elimination by the body’s immune system. The sensitivity of capture methods has improved in the last few years. First, based on cancer-specific characteristics, the cancer cells are separated from other blood components followed by enrichment procedures. There are two main techniques for isolating CTCs, one based on immunoaffinity properties, and the other based on biophysical properties. The immunoaffinity-based technology, including positive or negative selection assays, isolates CTCs with an antibody-immobilized inert surface combined with magnetic beads [31] (Figure 2a). The epithelial cell adhesion molecule (EpCAM) is a commonly used cell surface marker for positive CTC selection and an immunomagnetic assay called CELLSEARCH®. To date, CELLSEARCH® is the only CTC technology that has gained FDA approval enabling the direct visualization and quantification of CTCs and the identification of living cells without the need for cell lysis. The functionality of CELLSEARCH® for the detection of CTCs in GI cancer was confirmed by different studies [32,33]. In another approach, CTCs from blood samples of patients with CRC were pre-enriched through binding to VAR2CSA protein-coupled magnetic beads, and finally the colon-related mRNA transcripts USH1C and CKMT1A were detected by RT-qPCR [34]. Microfluidic chips as an immunoaffinity technology allow the selection of CTCs from small volumes of fluid under laminar flow, eliminating the need for sample processing. In a study by Lim et al. [35], single CTCs and CTC clusters were captured on the membrane of a centrifugal microfluidic device, picked without fixation, and used for further molecular analysis. Researchers began to develop CTC isolation technologies based on the biophysical properties of CTCs to overcome the bias and narrow spectrum of immunoaffinity-based approaches for CTC isolation. These methods are characterized as label-free and isolate CTCs from the blood based on biophysical properties, such as density, size, deformability, and electrical charge [36]. In order to confirm that the enriched cells consist only of CTCs, the cells must undergo characterization. Currently, this is achieved by immunocytochemistry-based assays, including immunofluorescence and immunohistochemistry, and molecular approaches, including RT-qPCR, FISH, and next-generation sequencing [37]. Using GILUPI Cell Collector (CC), a novel in vivo CTC detection device, researchers reported overcoming the limitations of small blood sample volumes. However, the clinical relevance of the CTCs detected was inferior to the CTCs identified by Cell Search [38].

2.1.2. Clinical Application/Relevance of CTCs

Several studies have observed the prognostic value of CTCs for overall survival (OS) in localized colorectal cancer (CRC) [39,40]. In a series of 287 patients, a group demonstrated that preoperative CTC detection with a ≥ 1 CTC/7.5 mL proved to be an independent prognostic marker, whereas another group with 519 patients stated no association after surgery [39,41]. In high-risk CRC patients requiring adjuvant chemotherapy, CTC detection in the blood was correlated with worse outcomes [41,42,43]. A meta-analysis containing 1847 patients (11 studies) indicated that the detection of CTCs in the peripheral blood with CELLSEARCH® has predictive utility for patients with CRC [44]. VISNÚ-1, a multicentre, randomized phase III trial with 349 patients, indicated that the first-line FOLFOXIRI-bevacizumab chemotherapy regimen significantly improved progression-free survival (PFS) in comparison to the FOLFOX-bevacizumab chemotherapy regimen in patients with metastatic CRC. This trial revealed that the CTC count might be a valuable non-invasive biomarker to aid in decision-making for patients undergoing intensive first-line therapy [45]. In a series of studies performed in metastatic CRC, patients with high baseline CTC count (≥3 CTCs/7.5 mL) could benefit from intensive chemotherapy regimens (four drugs), unlike patients with low CTC counts [44,46,47,48]. The PRODIGE 17 trial, conducted in 106 untreated patients with advanced gastric and esophageal cancer, reported that dynamic changes in CTC counts between baseline and 28 days after treatment were significantly associated with PFS and OS and could help in tailoring treatment regimens to each individual patient [49]. The above-mentioned findings might therefore help in the development of individualized treatment approaches in gastrointestinal cancer patients. In Table 1, a broad application of CTCs and its clinical relevance in GICs is mentioned.

2.2. Circulating Tumor DNA (ctDNA)

A group of French scientists detected cfDNA fragments in the circulating plasma of patients with autoimmune disorders in 1948 [73]. Later it became clear that the release of cfDNA is not restricted to autoimmune disorders, but was also found amongst others in pregnant women [74], septic patients [75], people suffering from different types of cancers, and even in healthy individuals [76]. Numerous studies have been conducted to uncover the mechanisms by which DNA fragments are released from cells into the plasma or serum. Major mechanisms involve apoptosis, necrosis, phagocytosis, NETosis, or active secretion [77]. Basically, every cell and tissue type is able to release cfDNA into circulation. Consequently, based on cell and tissue-specific methylation patterns from comprehensive databases including the Cancer Genome Atlas (TCGA) an assignment of cfDNA to different origins became possible [78]. Accordingly, the major source of cfDNA in blood results from hematopoietic cells, followed by vascular endothelial cells (up to 10%). However, cfDNA from liver tissue can also frequently be detected at low levels in circulation (up to 1%) in healthy people [78]. CtDNA is a fraction of cfDNA that originates from primary tumors, metastases, or from CTCs. Additionally, some findings are suggestive of an active release of ctDNA from living tumor cells involving exosomes [79]. CtDNA is characterized by small 70–200 base pair fragments circulating freely within the blood [73] showing a major fragment size of around 170 base pairs, which corresponds to nucleosomal fragments resulting from apoptosis [80]. The half-life of ctDNA is very short ranging from 15 min to 2.5 h before it is finally cleared by the liver and/or kidneys which is a prerequisite for a precise biomarker [81]. Concentrations of ctDNA in the blood of patients with a malignant tumor are significantly increased compared to healthy individuals [82]; however, levels of released ctDNA significantly vary between different tumor types and tumor stages. Furthermore, the match of cancer-specific alterations in the genome of solid tumors to those of ctDNA is a major discriminator between ctDNA and physiological cell-free DNA at steady state [83,84,85].

2.2.1. Detection and Analysis of ctDNA

There are a number of technical challenges associated with the analysis of ctDNA. First, total cfDNA itself is present only at comparably low concentrations in the nanogram per ml range. Second, the fraction of ctDNA among total cfDNA in many cases is also relatively low. This becomes especially evident in the early stages of cancer development or for tumors that release only low amounts of DNA [76]. Therefore, an urgent need for enrichment approaches of ctDNA over total cfDNA still exists. In this context, it has been reported that ctDNA to some extent might be enriched in cfDNA fractions of smaller size (90–150 base pairs (bp)) separated from the major fraction of 170 bp fragments [86] (Figure 2b). Although a tendency to higher ctDNA content in the 90–150 bp fraction could be found, enrichment factors of twofold in more than 95% of cases were still not satisfying [86]. In principle, a plethora of downstream analyses has been established for the diagnosis, prognosis, monitoring, and prediction of treatment response for all major cancer diseases. Among them are single nucleotide polymorphism (SNP) as well as copy number variation (CNV) analyses. When sufficient amounts of ctDNA templates (at least one genome equivalent per assay) are available in patient specimens, targeted assays based on PCR, for example, represent powerful approaches. Such PCR-based techniques which are characterized by high sensitivity showed the ability to identify relevant alterations in genes including RAS, HER2/NEU, BRAF, MET, BRCA2, APC, TP53, ALK, ROS1, PTEN, and NF1. However, when ctDNA content drops below one tumor genome equivalent per assay multi-target approaches become mandatory. Multi-gene panels are well established to similarly test for hundreds of targets. However, when it comes to early detection of cancer for screening purposes ctDNA contents of less than 0.01% represent a serious technical challenge to robustly assure high sensitivity and specificity. Cancer-specific methylomes in ctDNA were therefore proposed as a promising alternative [87]. In combination with next-generation sequencing (NGS), thousands of differential hyper-/hypo-methylated regions (DMRs) have been determined for a variety of cancers in addition to chromosomal and copy number changes or point mutations [88,89]. Accordingly, complex signatures of DMRs, for example, allow for early diagnosis with higher reliability. In general, it has been suggested that even for only as low as 0.01% ctDNA content prediction of cancer disease should be possible with 100–1000 DMRs when sequencing coverage of at least 100–1000x is given [87].

2.2.2. Clinical Application/Relevance of ctDNA

Analysis of tumor-linked genetic alterations and DNA methylation profiling has been recognized as a method for detecting potential biomarkers for disease diagnosis and prognosis [90]. In a study by Tam et al. [91] the levels of TAC1 and SEPT9 methylation detected in postoperative sera of patients with CRC were independent predictors for tumor recurrence and unfavorable cancer-specific survival. Findings from several studies showed that high ctDNA levels combined with an increased number of mutations detected in the ctDNA were linked to poor survival and multi-site metastasis [92]. However, when the amount of ctDNA was <1 mutant template molecule per milliliter of plasma, tests fail to detect early-stage cancer [93]. Therefore, methylome analyses of cfDNA with thousands of cancer-specific DMRs might overcome such limitations. In 2019, the ‘Galleri test’ or the ‘Galleri multicancer early detection (MCED) test’ developed by GRAIL Inc. (Menlo Park, CA, USA) achieved Breakthrough Device designation. The Galleri test detects cancer- and tissue-specific alterations in the methylation patterns of cfDNA in a blood sample via NGS, which should allow early pan-cancer detection even for cancers with unknown primary. GRAIL’s clinical trial includes three studies: the Circulating Cell-free Genome Atlas (CCGA) Study (Clinical Trial NCT02889978) [94], the STRIVE Study (Clinical Trial NCT03085888), and the SUMMIT Study (Clinical Trial NCT03934866). In these studies including 2482 cancer patients covering approximately 50 different cancer types, sensitivities and specificities were tested by using a target hybridization capture approach for the analyses of 100,000 differentially methylated regions [95]. In a predefined subset of 12 cancer types which comprised roughly 63% of all US cancer cases average sensitivity was 67.3% accumulated for stage I–III at a very high specificity of 99.3% [95]. Sensitivity for all 50 cancer types accumulated for stage I–III dropped to 43.9% with 18% sensitivity for stage I and 43% in stage II. Remarkably, sensitivities for pancreatic cancer were significantly higher even at early stages with 63% and 83% in stage I and II, respectively. Although high specificities might predestine this test for negative prediction in screening approaches, moderate sensitivities still require improvements, especially for early diagnosis. Another FDA-approved LB-based test is Epi proColon® (Epigenomics AG, Berlin, Germany) targeting methylation changes used to screen for CRC. The test is based on a real-time PCR with a fluorescent hydrolysis probe and targets the methylation changes of the SEPT9 gene promoter in cfDNA isolated from plasma. To evaluate the clinical assessment, Epi proColon® was involved in a prospective multicenter study (Clinical Trial NCT00855348) [96,97,98].
A ctDNA-guided approach has been used by numerous clinical trials (DYNAMIC, CIRCULATE-Japan, CIRCULATE-trial, CIRCULATE-PRODIGE, and IMPROVE-IT2), all focused towards precise adjuvant therapy for stage II colon cancer patients [99,100,101,102,103]. According to DYNMAIC-trial, a ctDNA-guided approach led to a reduction in the number of patients who received adjuvant therapy, and furthermore, ctDNA-positive patients appeared to benefit from adjuvant treatment. The other trials (CIRCULATE-trial, IMPROVE-IT2) mentioned above could help in decision-making before adjuvant treatment in stage II colon cancer. The outcome of these trials proposes that a survival benefit from adjuvant chemotherapy may be obtained in a well-defined subgroup of patients with stage II colon cancer—especially those with detectable ctDNA post-surgery. In the case of pancreatic cancer, ctDNA might be used as a marker for monitoring treatment efficacy and disease progression [104]. To prove the feasibility of a non-invasive detection in plasma, Liu et al. developed a pancreatic cancer detection assay (PANDA) for screening and validation of PDAC-specific DNA methylation in tissues and plasmas of PDAC patients [105]. In combination with age and CA19-9 plasma serum level, this assay showed encouraging results to discriminate PDAC plasma from non-malignant disease, showing its capability to be amended into a non-invasive diagnostics method for PDAC screening. In Table 2, a broad application of ctDNA/cfDNA and its clinical relevance in GICs is mentioned.

2.3. Circulating Extracellular Vesicles (Tumor Exosomes)

Exosomes are a subpopulation of extracellular vesicles (EVs), ranging in size from 30–150 nm. They are derived from the endosomal pathway via the formation of late endosomes or multivesicular bodies (MVBs). As an important mediator of intracellular communication, exosomes transmit various biological molecules including proteins, lipids, and nucleic acids over distances within the protection of a lipidic bilayer-enclosed structure. Nearly all types of cells and all body fluids contain exosomes [124,125]. Cancer cells and other stromal cells in the tumor microenvironment (TME) also release exosomes and control tumor development through molecular exchanges mediated by exosomes [126,127]. Circulating extracellular vesicles (cEVs) are implied to be more stable in comparison to serological proteins as the lipidic bilayers defend the content from proteases and other enzymes [128].

2.3.1. Isolation of Tumor Exosomes

Exosomes can be isolated using various methodologies. Ultracentrifugation (UC) is the most widely used technique. Other techniques include differential centrifugation (DC), density gradient ultrafiltration (DG), size exclusion chromatography (SEC), precipitation, immunoaffinity capture based on the expression of endosomal surface proteins such as CD81, CD63, and CD9, and microfluidic-based assays [129] (Figure 2d).

2.3.2. Clinical Application/Relevance of Tumor Exosomes

Exosomes demonstrate significant advantages over other sources of LBs. First, exosomes exist in almost all body fluids and are characterized by highly stable lipidic bilayers. Second, living cells secret exosomes. They thus contain biological information from the parental cells and are more representative than cell-free DNA secreted during necrosis or apoptosis [130]. Third, exosomes express specific proteins such as CD63, ALIX, TS101, and HSP70, 20 which can be used as markers to discriminate exosomes from other vesicles making their identification clear and simple [131]. Fourth, as exosomes can present specific surface proteins from parental cells or target cells, they can help in the prediction of organ-specific metastasis [132]. Fifth, compared to CTCs, they can be isolated using classic methods such as ultracentrifugation [133].
Circulating exosomal PD-L1 was shown to contribute to immunosuppression, to reflect the immune status, and to better predict survival in patients with GICs, thereby making it a potential prognostic biomarker [134]. Additionally, EV proteins such as carcinoembryonic antigen-related cell adhesion molecules (CEACAMs), Tenascin C, Glypican-1, and ZIP-4 have been recognized as diagnostic biomarkers in GICs [135,136,137]. The EV-Glypican-1 (GPC-1) derived from plasma has been described as a potential marker of early pancreatic ductal adenocarcinoma (PDAC) with higher diagnostic accuracy than CA19-9 [137]. A clinical trial (NCT03032913) performed by Etienne BUSCAIL involved 20 PDAC patients and 20 non-cancer patients, whose blood samples were collected to detect CTCs and GPC1+ exosomes for diagnostic accuracy assessment of CTCs and Onco-exosome Quantification. Very recently, Lin et al. presented the development of a signature of four EV-proteins—monocyte marker CD14, Serpin A4 (a regulator of angiogenesis), CFP (a positive regulator of the complement system), and LBP (lipopolysaccharide binding protein)—as prognostic biomarkers in colorectal liver metastases (CRLM). Thereby, they used matching pre- and post-operative serum samples of patients undergoing CRLM surgery and finally validated the discovered proteins in three independent cohorts. Additionally, they showed that EV-bound CXCL7 could serve as a biomarker of early response in CRML patients undergoing systemic chemotherapy [138]. Furthermore, three cancer-specific phospholipids were found in a study that analyzed 20 dysregulated phospholipids in pancreatic cancer compared to controls. Among them, LysoPC 22:0 was linked with tumor stage, whereas CA19-9 and CA242 were associated with tumor diameter and positive lymph node count [139]. Finally, diagnostic accuracy for WASF2, ARF6 mRNAs, SNORA74A, and SNORA25snoRNAs in circulating exosomes was greater than for CA19-9 in discriminating PC patients from controls [140]. Even though a limited number of studies on the application of exosome-based drug delivery vectors in the treatment of GICs exist, some of them report intriguing advancements in the field. Using an in vitro model Pascucci L. et al. demonstrated the role of exosomal-mesenchymal stromal cells (exo-MSCs) in the packaging and delivery of active drugs, suggesting a possible option of using the MSCs as a warehouse to develop drugs with a better specificity [141]. Another study showed the application of milk-derived exosomes for the oral delivery of PAC in early-stage and advanced-stage pancreatic and other cancers. It also evaluated the anti-tumor potency of the milk-derived exosomes loaded with PAC [142]. Furthermore, studies have verified the link between cancer-derived exosomes and the modulation of immune response in pancreatic cancer and have also indicated the application of these cargo carriers in targeting pancreatic cancer cells, whether as anti-tumor drugs and other molecules, such as RNAi against mutant KRAS [143]. More applications and the clinical relevance of exosomes are summarized in Table 3.

2.4. Tumor-Educated Blood Platelets (TEPs)

Platelets play a central role in blood coagulation and in the healing of wounds, and their relationship with cancer has been extensively investigated [156,157,158,159,160,161,162,163,164]. There are two major studies that indicated the involvement of platelets during tumor progression. These studies contributed to the development of the concept of tumor-educated platelets (TEPs). The first study by Trousseau (1868) observed spontaneous coagulation being common in cancerous patients, stating that circulating platelets were affected by cancer [165]. The second study (Billroth T, 1877) described ‘’ thrombi filled with specific tumor elements’’ as part of metastasis, pointing out a direct interaction of cancer cells and platelets [166,167]. In recent years, several studies have focused on the impact of platelets during cancer progression, and some of them showed that platelet dysfunction and thrombotic disorders are important key factors in cancer development. By now it is well known that tumor-educated platelets (TEPs) are educated when they interact with the tumor cells in such a way as to lead to the detachment of biomolecules, such as proteins and RNA, tumor-specific splice events, and finally to megakaryocyte alteration [168]. Through this interaction, the RNA profile of blood platelets changes. This change has been used as an independent diagnostic marker for detecting TEPs in various solid tumors [169]. The RNA biomarkers of the directly transferred transcripts are EGFRvIII, PCA3, EML4-ALK, KRAS, EGFR, PIK3CA mutants, FOLH1, KLK2, KLK3, and NPY [170]. Here, we describe the isolation, detection, and clinical relevance of TEPsin GICs.

2.4.1. Isolation and Detection of Tumor-Educated Platelets

Tumor-educated platelets can be separated from peripheral blood by using a two-step centrifugation approach [171]. The first step separates the platelet-rich plasma (PRP) from the red blood and white blood cells, whereas the second centrifugation step yields the platelet pellet [172]. For the detection of the TEPs in the human plasma, the plasma pellets are dissolved in 1ml TRIZOL reagent. RNA is extracted from the plasma platelet pellet and the suboptimal quality of the platelet RNA is characterized by an absence of ribosomal 18S and 28S peaks and measured in a Bioanalyzer Picochip. Preferably, platelet mRNAs are measured by other methods, such as Fragment analyzer (Advanced Analytical Technologies, Ankeny, IA, USA) or Qubit Fluorometric Quantification (Thermo Fisher, Waltham, MA, USA) analysis (Figure 2c).

2.4.2. Clinical Application/Relevance of Tumor-Educated Blood Platelets

Platelet-related measures are considered important in anticipating long-term results in patients with GI cancer. A study distinguished 228 patients with localized and metastasized tumors from 55 healthy donors using the genetic profile of mRNA from TEPs. Additionally, mRNA sequencing of TEPs could accurately recognize MET or ERBB2-positive and mutant KRAS, EGFGR, or PIK3CA tumors. Moreover, TEPs have the ability to identify the location of primary tumors including colorectal cancer, non-small lung carcinoma, glioblastoma, pancreatic cancer, hepatobiliary cancer, and breast cancer [169]. Yang et al. showed that TIMP metallopeptidase inhibitor 1 (TIMP1) mRNA levels were higher in platelets from patients with CRC compared to those from healthy donors or patients with inflammatory bowel diseases, which could be another promising diagnostic signature [173]. A study in patients with hepatocellular carcinoma (HCC) conducted by Asghar et al. showed that the expression of TGF-β, NF-κβ, and VEGF was increased in TEPs of HCC patients compared to that from controls and thereby they suggested that these RNA based biomarkers could be used as a promising tool for early detection of HCC [174]. Furthermore, the alterations of platelet counts as a prognostic marker were studied in a clinical trial (NCT03717519) conducted by Corrado Pedrazzani. The study recruited 196 patients with synchronous colorectal liver metastases. In esophageal squamous cell carcinoma (ESCC), Ishibashi et al. performed a meta-analysis evaluating the prognostic values of platelet-related measures. The analysis revealed that a high platelet-to-lymphocyte ratio (PLR) was significantly correlated with poor OS [175]. A dual-center retrospective study performed by Yang et al. showed a standardized indicator of platelet counts was used to forecast the prognosis of 586 CRC patients by using a development-validation cohort. In the development cohort, postoperative platelet count and postoperative/preoperative platelet ratio (PPR) were independent predictors of prognosis in CRC patients. In the validation cohort, the platelet/lymphocyte ratio and PPR were used to test the OS of CRC patients and showed the largest AUC in reviewing 1-year and 3-year OS (AUC: 0.663 and 0.673) [176]. Based on the studies above, we summarize that PLR and PPR could serve as reliable and economic indicators to evaluate the prognosis of GI cancer. Interestingly, many new approaches have been utilized to explore the clinical relevance of TEPs in GICs. We have summarized some of them in Table 4 below. TEPs have advantages over other blood-based sources due to their abundance in the blood, the ease with which they can be isolated, their high-quality RNA, and their ability to process RNA in response to foreign signals.

3. Conclusions

Due to the limitations of conventional tissue biopsies, there is an urgent need for new tumor biomarkers. As reviewed here, LBs have been well-evaluated and show promising results as an alternative clinical tool for the detection and treatment of gastrointestinal cancers, many of those currently being intensively investigated in various observational and interventional clinical trials (Table 5 and Table 6). Multiple longitudinal biopsies allow for real-time monitoring of the tumor. This approach may facilitate the prediction of the possible treatment outcome and may help in choosing the optimal individualized therapeutic strategy. Therefore, the analysis of LB markers (TEPs, CTCs, ctDNA/cfDNA, and exosomes), in combination with modern imaging techniques and already existing protein markers might help to create an optimal clinical synergy that might be used as a standard procedure in the near future for early cancer detection and individualized cancer treatment.

Author Contributions

Conception and design: P.D., A.M., D.K. and G.F.W.; Collection and assembly of data: P.D., A.M., D.K., A.A. and G.F.W.; Methodology: P.D., A.M., D.K. and A.A.; Writing and editing: P.D., A.M., D.K., A.A., C.K., K.S. and G.F.W.; Administrative support: G.F.W.; Final approval of manuscript: All authors. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Das Bundesministerium für Bildung und Forschung (BMBF, 03INT506CA).

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

AdSCsadult stem cells
ALIair-liquid-interface
CA19-9carbohydrate Antigen 19-9
CEACAMscarcinoembryonic antigen-related cell adhesion molecules
cfDNAcell-free DNA
ctDNAcirculating tumor DNA
CRCcolorectal cancer
CRMLcolorectal liver metastases
circRNAcircular RNA
CTCscirculating tumor cells
ctDNAcirculating tumor DNA
DCdifferential centrifugation
ddPCRdroplet digital PCR
DGdensity gradient ultracentrifugation
ECMextracellular matrix
EpCAMepithelial cell adhesion molecule
EUSendoscopic ultrasound
EVsextracellular vesicles
FDAthe United States Food and Drug Administration
FISHfluorescence in situ hybridization
GPC-1glypican 1
GIgastrointestinal
LBliquid biopsy
LncRNAlong non-coding RNA
mRNAmessenger RNA
MVBsmultivesicular bodies
miRNAmicroRNAs
NGSnext generation sequencing
PCpancreatic cancer
PDACpancreatic ductal adenocarcinoma
PDOpatient-derived cancer organoid
PSCspluripotent stem cells
RT-qPCRreal-time quantitative polymerase chain reaction
SECsize exclusion chromatography
TEPstumor-educated blood platelets
TMEtumor microenvironment
UCultracentrifugation

References

  1. International Agency for Research on Cancer. Estimated Number of New Cases and Deaths of Cancer in 2020. 2020. Available online: https://gco.iarc.fr/today/home (accessed on 15 February 2022).
  2. Le, Q.; Wang, C.; Shi, Q. Meta-Analysis on the Improvement of Symptoms and Prognosis of Gastrointestinal Tumors Based on Medical Care and Exercise Intervention. J. Healthc. Eng. 2021, 2021, 5407664. [Google Scholar] [CrossRef] [PubMed]
  3. Chen, Z.-D.; Zhang, P.-F.; Xi, H.-Q.; Wei, B.; Chen, L.; Tang, Y. Recent Advances in the Diagnosis, Staging, Treatment, and Prognosis of Advanced Gastric Cancer: A Literature Review. Front. Med. 2021, 8, 744839. [Google Scholar] [CrossRef] [PubMed]
  4. Arnold, M.; Abnet, C.C.; Neale, R.E.; Vignat, J.; Giovannucci, E.L.; McGlynn, K.A.; Bray, F. Global Burden of 5 Major Types of Gastrointestinal Cancer. Gastroenterology 2020, 159, 335–349.e15. [Google Scholar] [CrossRef]
  5. Saini, A.; Pershad, Y.; Albadawi, H.; Kuo, M.; Alzubaidi, S.; Naidu, S.; Knuttinen, M.-G.; Oklu, R. Liquid Biopsy in Gastrointestinal Cancers. Diagnostics 2018, 8, 75. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Siravegna, G.; Marsoni, S.; Siena, S.; Bardelli, A. Integrating liquid biopsies into the management of cancer. Nat. Rev. Clin. Oncol. 2017, 14, 531–548. [Google Scholar] [CrossRef] [PubMed]
  7. Niimi, K.; Ishibashi, R.; Mitsui, T.; Aikou, S.; Kodashima, S.; Yamashita, H.; Yamamichi, N.; Hirata, Y.; Fujishiro, M.; Seto, Y.; et al. Laparoscopic and endoscopic cooperative surgery for gastrointestinal tumor. Ann. Transl. Med. 2017, 5, 187. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Garraway, L.A.; Jänne, P.A. Circumventing Cancer Drug Resistance in the Era of Personalized Medicine. Cancer Discov. 2012, 2, 214–226. [Google Scholar] [CrossRef] [Green Version]
  9. Goyal, L.; Saha, S.K.; Liu, L.Y.; Siravegna, G.; Leshchiner, I.; Ahronian, L.G.; Lennerz, J.K.; Vu, P.; Deshpande, V.; Kambadakone, A.; et al. Polyclonal Secondary FGFR2 Mutations Drive Acquired Resistance to FGFR Inhibition in Patients with FGFR2 Fusion–Positive Cholangiocarcinoma. Cancer Discov. 2017, 7, 252–263. [Google Scholar] [CrossRef] [Green Version]
  10. Russo, M.; Siravegna, G.; Blaszkowsky, L.S.; Corti, G.; Crisafulli, G.; Ahronian, L.G.; Mussolin, B.; Kwak, E.L.; Buscarino, M.; Lazzari, L.; et al. Tumor Heterogeneity and Lesion-Specific Response to Targeted Therapy in Colorectal Cancer. Cancer Discov. 2016, 6, 147–153. [Google Scholar] [CrossRef] [Green Version]
  11. Gerlinger, M.; Rowan, A.J.; Horswell, S.; Math, M.; Larkin, J.; Endesfelder, D.; Gronroos, E.; Martinez, P.; Matthews, N.; Stewart, A.; et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 2012, 366, 883–892. [Google Scholar] [CrossRef] [Green Version]
  12. Hazar-Rethinam, M.; Kleyman, M.; Han, G.C.; Liu, D.; Ahronian, L.G.; Shahzade, H.A.; Chen, L.; Parikh, A.R.; Allen, J.N.; Clark, J.W.; et al. Convergent Therapeutic Strategies to Overcome the Heterogeneity of Acquired Resistance in BRAF(V600E) Colorectal Cancer. Cancer Discov. 2018, 8, 417–427. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Morelli, M.; Overman, M.; Dasari, A.; Kazmi, S.; Mazard, T.; Vilar, E.; Morris, V.; Lee, M.; Herron, D.; Eng, C.; et al. Characterizing the patterns of clonal selection in circulating tumor DNA from patients with colorectal cancer refractory to anti-EGFR treatment. Ann. Oncol. 2015, 26, 731–736. [Google Scholar] [CrossRef] [PubMed]
  14. Emoto, S.; Ishigami, H.; Yamashita, H.; Yamaguchi, H.; Kaisaki, S.; Kitayama, J. Clinical significance of CA125 and CA72-4 in gastric cancer with peritoneal dissemination. Gastric Cancer 2011, 15, 154–161. [Google Scholar] [CrossRef]
  15. Li, Y.; Yang, Y.; Lu, M.; Shen, L. Predictive value of serum CEA, CA19-9 and CA72.4 in early diagnosis of recurrence after radical resection of gastric cancer. Hepatogastroenterology 2011, 58, 2166–2170. [Google Scholar] [PubMed]
  16. Shimada, H.; Noie, T.; Ohashi, M.; Oba, K.; Takahashi, Y. Clinical significance of serum tumor markers for gastric cancer: A systematic review of literature by the Task Force of the Japanese Gastric Cancer Association. Gastric Cancer 2013, 17, 26–33. [Google Scholar] [CrossRef]
  17. Williams, S.C. Circulating tumor cells. Proc. Natl. Acad. Sci. USA 2013, 110, 4861. [Google Scholar] [CrossRef] [Green Version]
  18. Nel, I.; David, P.; Gerken, G.G.H.; Schlaak, J.F.; Hoffmann, A.-C. Role of circulating tumor cells and cancer stem cells in hepatocellular carcinoma. Hepatol. Int. 2014, 8, 321–329. [Google Scholar] [CrossRef]
  19. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [Green Version]
  20. Klymkowsky, M.W.; Savagner, P. Epithelial-mesenchymal transition: A cancer researcher’s conceptual friend and foe. Am. J. Pathol. 2009, 174, 1588–1593. [Google Scholar] [CrossRef] [Green Version]
  21. Polyak, K.; Weinberg, R.A. Transitions between epithelial and mesenchymal states: Acquisition of malignant and stem cell traits. Nat. Rev. Cancer 2009, 9, 265–273. [Google Scholar] [CrossRef]
  22. Thiery, J.P.; Acloque, H.; Huang, R.Y.J.; Nieto, M.A. Epithelial-Mesenchymal Transitions in Development and Disease. Cell 2009, 139, 871–890. [Google Scholar] [CrossRef] [PubMed]
  23. Yilmaz, M.; Christofori, G. EMT, the cytoskeleton, and cancer cell invasion. Cancer Metastasis Rev. 2009, 28, 15–33. [Google Scholar] [CrossRef] [Green Version]
  24. Barrallo-Gimeno, A.; Nieto, M.A. The Snail genes as inducers of cell movement and survival: Implications in development and cancer. Development 2005, 132, 3151–3161. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Allard, W.J.; Matera, J.; Miller, M.C.; Repollet, M.; Connelly, M.C.; Rao, C.; Tibbe, A.G.J.; Uhr, J.W.; Terstappen, L.W.M.M. Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clin. Cancer Res. 2004, 10, 6897–6904. [Google Scholar] [CrossRef] [Green Version]
  26. Denève, E.; Riethdorf, S.; Ramos, J.; Nocca, D.; Coffy, A.; Daurès, J.-P.; Maudelonde, T.; Fabre, J.-M.; Pantel, K.; Alix-Panabières, C. Capture of Viable Circulating Tumor Cells in the Liver of Colorectal Cancer Patients. Clin. Chem. 2013, 59, 1384–1392. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Tien, Y.W.; Kuo, H.C.; Ho, B.I.; Chang, M.C.; Chang, Y.T.; Cheng, M.F.; Chen, H.-L.; Liang, T.-Y.; Wang, C.-F.; Huang, C.-Y.; et al. A High Circulating Tumor Cell Count in Portal Vein Predicts Liver Metastasis from Periampullary or Pancreatic Cancer: A High Portal Venous CTC Count Predicts Liver Metastases. Medicine 2016, 95, e3407. [Google Scholar] [CrossRef] [PubMed]
  28. Bissolati, M.; Sandri, M.T.; Burtulo, G.; Zorzino, L.; Balzano, G.; Braga, M. Portal vein-circulating tumor cells predict liver metastases in patients with resectable pancreatic cancer. Tumor Biol. 2014, 36, 991–996. [Google Scholar] [CrossRef]
  29. Chapman, C.G.; Waxman, I. EUS-Guided Portal Venous Sampling of Circulating Tumor Cells. Curr. Gastroenterol. Rep. 2019, 21, 68. [Google Scholar] [CrossRef]
  30. Alix-Panabières, C.; Pantel, K. Circulating tumor cells: Liquid biopsy of cancer. Clin. Chem. 2013, 59, 110–118. [Google Scholar] [CrossRef]
  31. Shahneh, F.Z. Sensitive antibody-based CTCs detection from peripheral blood. Hum. Antibodies 2013, 22, 51–54. [Google Scholar] [CrossRef] [PubMed]
  32. Uenosono, Y.; Arigami, T.; Kozono, T.; Yanagita, S.; Hagihara, T.; Haraguchi, N.; Matsushita, D.; Hirata, M.; Arima, H.; Funasako, Y.; et al. Clinical significance of circulating tumor cells in peripheral blood from patients with gastric cancer. Cancer 2013, 119, 3984–3991. [Google Scholar] [CrossRef] [PubMed]
  33. Lee, S.J.; Lee, J.; Kim, S.T.; Park, S.H.; Park, J.O.; Park, Y.S.; Lim, H.Y.; Kang, W.K. Circulating Tumor Cells are Predictive of Poor Response to Chemotherapy in Metastatic gastric cancer. Int. J. Biol. Markers 2015, 30, 382–386. [Google Scholar] [CrossRef] [PubMed]
  34. Bang-Christensen, S.R.; Katerov, V.; Jørgensen, A.M.; Gustavsson, T.; Choudhary, S.; Theander, T.G.; Salanti, A.; Allawi, H.T.; Agerbæk, M. Detection of VAR2CSA-Captured Colorectal Cancer Cells from Blood Samples by Real-Time Reverse Transcription PCR. Cancers 2021, 13, 5881. [Google Scholar] [CrossRef]
  35. Lim, M.; Park, S.; Jeong, H.-O.; Park, S.H.; Kumar, S.; Jang, A.; Lee, S.; Kim, D.U.; Cho, Y.-K. Circulating Tumor Cell Clusters Are Cloaked with Platelets and Correlate with Poor Prognosis in Unresectable Pancreatic Cancer. Cancers 2021, 13, 5272. [Google Scholar] [CrossRef] [PubMed]
  36. Jin, C.; McFaul, S.M.; Duffy, S.P.; Deng, X.; Tavassoli, P.; Black, P.C.; Ma, H. Technologies for label-free separation of circulating tumor cells: From historical foundations to recent developments. Lab A Chip 2013, 14, 32–44. [Google Scholar] [CrossRef]
  37. Nordgård, O.; Tjensvoll, K.; Gilje, B.; Søreide, K. Circulating tumour cells and DNA as liquid biopsies in gastrointestinal cancer. Br. J. Surg. 2018, 105, e110–e120. [Google Scholar] [CrossRef] [Green Version]
  38. Dizdar, L.; Fluegen, G.; van Dalum, G.; Honisch, E.; Neves, R.P.; Niederacher, D.; Neubauer, H.; Fehm, T.; Rehders, A.; Krieg, A.; et al. Detection of circulating tumor cells in colorectal cancer patients using the GILUPI CellCollector: Results from a prospective, single-center study. Mol. Oncol. 2019, 13, 1548–1558. [Google Scholar] [CrossRef] [Green Version]
  39. Bork, U.; Rahbari, N.N.; Schölch, S.; Reissfelder, C.; Kahlert, C.; Büchler, M.W.; Weitz, J.; Koch, M. Circulating tumour cells and outcome in non-metastatic colorectal cancer: A prospective study. Br. J. Cancer 2015, 112, 1306–1313. [Google Scholar] [CrossRef] [Green Version]
  40. Van Dalum, G.; Stam, G.J.; Scholten, L.F.; Mastboom, W.J.; Vermes, I.; Tibbe, A.G.; De Groot, M.R.; Terstappen, L.W.M.M. Importance of circulating tumor cells in newly diagnosed colorectal cancer. Int. J. Oncol. 2015, 46, 1361–1368. [Google Scholar] [CrossRef] [Green Version]
  41. Sotelo, M.J.; Sastre, J.; Maestro, M.L.; Veganzones, S.; Viéitez, J.M.; Alonso, V.; Grávalos, C.; Escudero, P.; Vera, R.; Aranda, E.; et al. Role of circulating tumor cells as prognostic marker in resected stage III colorectal cancer. Ann. Oncol. 2014, 26, 535–541. [Google Scholar] [CrossRef]
  42. Lu, C.-Y.; Tsai, H.-L.; Uen, Y.-H.; Hu, H.-M.; Chen, C.-W.; Cheng, T.-L.; Lin, S.-R.; Wang, J.-Y. Circulating tumor cells as a surrogate marker for determining clinical outcome to mFOLFOX chemotherapy in patients with stage III colon cancer. Br. J. Cancer 2013, 108, 791–797. [Google Scholar] [CrossRef] [Green Version]
  43. Lu, Y.-J.; Wang, P.; Peng, J.; Wang, X.; Zhu, Y.-W.; Shen, N. Meta-analysis Reveals the Prognostic Value of Circulating Tumour Cells Detected in the Peripheral Blood in Patients with Non-Metastatic Colorectal Cancer. Sci. Rep. 2017, 7, 905. [Google Scholar] [CrossRef] [Green Version]
  44. Huang, X.; Gao, P.; Song, Y.; Sun, J.; Chen, X.; Zhao, J.; Xu, H.; Wang, Z. Meta-analysis of the prognostic value of circulating tumor cells detected with the CellSearch System in colorectal cancer. BMC Cancer 2015, 15, 202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Aranda, E.; Viéitez, J.M.; Gómez-España, A.; Calle, S.G.; Salud-Salvia, A.; Graña, B.; Garcia-Alfonso, P.; Rivera, F.; Quintero-Aldana, G.A.; Reina-Zoilo, J.J.; et al. FOLFOXIRI plus bevacizumab versus FOLFOX plus bevacizumab for patients with metastatic colorectal cancer and >/=3 circulating tumour cells: The randomised phase III VISNU-1 trial. ESMO Open 2020, 5, e000944. [Google Scholar] [CrossRef] [PubMed]
  46. Hardingham, J.E.; Grover, P.; Winter, M.; Hewett, P.J.; Price, T.J.; Thierry, B. Detection and Clinical Significance of Circulating Tumor Cells in Colorectal Cancer—20 Years of Progress. Mol. Med. 2015, 21 (Suppl. S1), S25–S31. [Google Scholar] [CrossRef]
  47. Krebs, M.G.; Renehan, A.G.; Backen, A.; Gollins, S.; Chau, I.; Hasan, J.; Valle, J.W.; Morris, K.; Beech, J.; Ashcroft, L.; et al. Circulating Tumor Cell Enumeration in a Phase II Trial of a Four-Drug Regimen in Advanced Colorectal Cancer. Clin. Color. Cancer 2014, 14, 115–122.e2. [Google Scholar] [CrossRef]
  48. Steinert, G.; Schölch, S.; Koch, M.; Weitz, J. Biology and significance of circulating and disseminated tumour cells in colorectal cancer. Langenbeck’s Arch. Surg. 2012, 397, 535–542. [Google Scholar] [CrossRef] [PubMed]
  49. Pernot, S.; Badoual, C.; Terme, M.; Castan, F.; Cazes, A.; Bouche, O.; Bennouna, J.; Francois, E.; Ghiringhelli, F.; De La Fouchardiere, C.; et al. Dynamic evaluation of circulating tumour cells in patients with advanced gastric and oesogastric junction adenocarcinoma: Prognostic value and early assessment of therapeutic effects. Eur. J. Cancer 2017, 79, 15–22. [Google Scholar] [CrossRef]
  50. Kang, H.M.; Kim, G.H.; Jeon, H.K.; Kim, D.H.; Jeon, T.Y.; Park, D.Y.; Jeong, H.; Chun, W.J.; Kim, M.-H.; Park, J.; et al. Circulating tumor cells detected by lab-on-a-disc: Role in early diagnosis of gastric cancer. PLoS ONE 2017, 12, e0180251. [Google Scholar] [CrossRef] [Green Version]
  51. Cheng, B.; Tong, G.; Wu, X.; Cai, W.; Li, Z.; Tong, Z.; He, L.; Yu, S.; Wang, S. Enumeration Aand Characterization Of Circulating Tumor Cells And Its Application In Advanced Gastric Cancer. OncoTargets Ther. 2019, 12, 7887–7896. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Liu, M.; Wang, R.; Sun, X.; Liu, Y.; Wang, Z.; Yan, J.; Kong, X.; Liang, S.; Liu, Q.; Zhao, T.; et al. Prognostic significance of PD-L1 expression on cell-surface vimentin-positive circulating tumor cells in gastric cancer patients. Mol. Oncol. 2020, 14, 865–881. [Google Scholar] [CrossRef]
  53. Jhi, J.H.; Kim, G.H.; Park, S.J.; Kim, D.U.; Lee, M.W.; Lee, B.E.; Kwon, C.H.; Cho, Y.-K. Circulating Tumor Cells and TWIST Expression in Patients with Metastatic Gastric Cancer: A Preliminary Study. J. Clin. Med. 2021, 10, 4481. [Google Scholar] [CrossRef] [PubMed]
  54. Yu, P.; Zhu, S.; Luo, Y.; Li, G.; Pu, Y.; Cai, B.; Zhang, C. Application of Circulating Tumor Cells and Circulating Free DNA from Peripheral Blood in the Prognosis of Advanced Gastric Cancer. J. Oncol. 2022, 2022, 9635218. [Google Scholar] [CrossRef] [PubMed]
  55. Wang, L.; Zhou, S.; Zhang, W.; Wang, J.; Wang, M.; Hu, X.; Liu, F.; Zhang, Y.; Jiang, B.; Yuan, H. Circulating tumor cells as an independent prognostic factor in advanced colorectal cancer: A retrospective study in 121 patients. Int. J. Color. Dis. 2019, 34, 589–597. [Google Scholar] [CrossRef] [Green Version]
  56. Bahnassy, A.A.; Salem, S.E.; Mohanad, M.; Abulezz, N.Z.; Abdellateif, M.S.; Hussein, M.; Zekri, C.A.; Zekri, A.-R.N.; Allahloubi, N.M. Prognostic significance of circulating tumor cells (CTCs) in Egyptian non-metastatic colorectal cancer patients: A comparative study for four different techniques of detection (Flowcytometry, CellSearch, Quantitative Real-time PCR and Cytomorphology). Exp. Mol. Pathol. 2018, 106, 90–101. [Google Scholar] [CrossRef]
  57. Messaritakis, I.; Sfakianaki, M.; Papadaki, C.; Koulouridi, A.; Vardakis, N.; Koinis, F.; Hatzidaki, D.; Georgoulia, N.; Kladi, A.; Kotsakis, A.; et al. Prognostic significance of CEACAM5mRNA-positive circulating tumor cells in patients with metastatic colorectal cancer. Cancer Chemother. Pharmacol. 2018, 82, 767–775. [Google Scholar] [CrossRef] [PubMed]
  58. Iinuma, H.; Watanabe, T.; Mimori, K.; Adachi, M.; Hayashi, N.; Tamura, J.; Matsuda, K.; Fukushima, R.; Okinaga, K.; Sasako, M.; et al. Clinical Significance of Circulating Tumor Cells, Including Cancer Stem-Like Cells, in Peripheral Blood for Recurrence and Prognosis in Patients with Dukes’ Stage B and C Colorectal Cancer. J. Clin. Oncol. 2011, 29, 1547–1555. [Google Scholar] [CrossRef]
  59. Tol, J.; Koopman, M.; Miller, M.C.; Tibbe, A.; Cats, A.; Creemers, G.J.M.; Vos, A.H.; Nagtegaal, I.; Terstappen, L.; Punt, C.J.A. Circulating tumour cells early predict progression-free and overall survival in advanced colorectal cancer patients treated with chemotherapy and targeted agents. Ann. Oncol. 2009, 21, 1006–1012. [Google Scholar] [CrossRef]
  60. Cohen, S.J.A.; Punt, C.J.; Iannotti, N.; Saidman, B.H.; Sabbath, K.D.; Gabrail, N.Y.; Picus, J.; Morse, M.; Mitchell, E.; Miller, M.C.; et al. Relationship of Circulating Tumor Cells to Tumor Response, Progression-Free Survival, and Overall Survival in Patients with Metastatic Colorectal Cancer. J. Clin. Oncol. 2008, 26, 3213–3221. [Google Scholar] [CrossRef]
  61. Prasoppokakorn, T.; Buntho, A.; Ingrungruanglert, P.; Tiyarattanachai, T.; Jaihan, T.; Kulkraisri, K.; Ariyaskul, D.; Phathong, C.; Israsena, N.; Rerknimitr, R.; et al. Circulating tumor cells as a prognostic biomarker in patients with hepatocellular carcinoma. Sci. Rep. 2022, 12, 1–9. [Google Scholar] [CrossRef]
  62. Hamaoka, M.; Kobayashi, T.; Tanaka, Y.; Mashima, H.; Ohdan, H. Clinical significance of glypican-3-positive circulating tumor cells of hepatocellular carcinoma patients: A prospective study. PLoS ONE 2019, 14, e0217586. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Guo, W.; Yang, X.R.; Sun, Y.F.; Shen, M.N.; Ma, X.L.; Wu, J.; Zhang, C.-Y.; Zhou, Y.; Xu, Y.; Hu, B.; et al. Clinical significance of EpCAM mRNA-positive circulating tumor cells in hepatocellular carcinoma by an optimized negative enrichment and qRT-PCR-based platform. Clin. Cancer Res. 2014, 20, 4794–4805. [Google Scholar] [CrossRef] [Green Version]
  64. Xu, W.; Cao, L.; Chen, L.; Li, J.; Zhang, X.-F.; Qian, H.-H.; Kang, X.-Y.; Zhang, Y.; Liao, J.; Shi, L.-H.; et al. Isolation of Circulating Tumor Cells in Patients with Hepatocellular Carcinoma Using a Novel Cell Separation Strategy. Clin. Cancer Res. 2011, 17, 3783–3793. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Huang, X.Y.; Li, F.; Li, T.T.; Zhang, J.T.; Shi, X.J.; Huang, X.Y.; Zhou, J.; Tang, Z.-Y.; Huang, Z.-L. A clinically feasible circulating tumor cell sorting system for monitoring the progression of advanced hepatocellular carcinoma. J. Nanobiotechnol. 2023, 21, 25. [Google Scholar] [CrossRef]
  66. Winograd, P.; Hou, S.; Court, C.M.; Lee, Y.-T.; Chen, P.-J.; Zhu, Y.; Sadeghi, S.; Finn, R.S.; Teng, P.-C.; Wang, J.J.; et al. Hepatocellular Carcinoma–Circulating Tumor Cells Expressing PD-L1 Are Prognostic and Potentially Associated with Response to Checkpoint Inhibitors. Hepatol. Commun. 2020, 4, 1527–1540. [Google Scholar] [CrossRef]
  67. Li, J.; Shi, L.; Zhang, X.; Sun, B.; Yang, Y.; Ge, N.; Liu, H.; Yang, X.; Chen, L.; Qian, H.; et al. pERK/pAkt phenotyping in circulating tumor cells as a biomarker for sorafenib efficacy in patients with advanced hepatocellular carcinoma. Oncotarget 2015, 7, 2646–2659. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Gemenetzis, G.; Groot, V.; Yu, J.; Ding, D.; Teinor, J.; Javed, A.; Wood, L.; Burkhart, R.; Cameron, J.; Makary, M.; et al. Circulating tumor cells dynamics in pancreatic adenocarcinoma correlate with disease status: Results of the prospective cluster study. HPB 2019, 21, S1. [Google Scholar] [CrossRef] [Green Version]
  69. Soeth, E.; Grigoleit, U.; Moellmann, B.; Röder, C.; Schniewind, B.; Kremer, B.; Kalthoff, H.; Vogel, I. Detection of tumor cell dissemination in pancreatic ductal carcinoma patients by CK 20 RT-PCR indicates poor survival. J. Cancer Res. Clin. Oncol. 2005, 131, 669–676. [Google Scholar] [CrossRef]
  70. Gao, Y.; Zhu, Y.; Zhang, Z.; Zhang, C.; Huang, X.; Yuan, Z. Clinical significance of pancreatic circulating tumor cells using combined negative enrichment and immunostaining-fluorescence in situ hybridization. J. Exp. Clin. Cancer Res. 2016, 35, 66. [Google Scholar] [CrossRef] [Green Version]
  71. Court, C.; Ankeny, J.S.; Sho, S.; Winograd, P.; Hou, S.; Song, M.; Wainberg, Z.A.; Girgis, M.D.; Graeber, T.G.; Agopian, V.G.; et al. Circulating Tumor Cells Predict Occult Metastatic Disease and Prognosis in Pancreatic Cancer. Ann. Surg. Oncol. 2018, 25, 1000–1008. [Google Scholar] [CrossRef]
  72. Franses, J.W.; Philipp, J.; Missios, P.; Bhan, I.; Liu, A.; Yashaswini, C.; Tai, E.; Zhu, H.; Ligorio, M.; Nicholson, B.; et al. Pancreatic circulating tumor cell profiling identifies LIN28B as a metastasis driver and drug target. Nat. Commun. 2020, 11, 3303. [Google Scholar] [CrossRef] [PubMed]
  73. Mandel, P.; Metais, P. Nuclear Acids in Human Blood Plasma. Comptes Rendus Seances Soc. Biol. Ses Fil. 1948, 142, 241–243. [Google Scholar]
  74. Lo, Y.M.; Lau, T.K.; Zhang, J.; Leung, T.N.; Chang, A.M.; Hjelm, N.M.; Elmes, R.S.; Bianchi, D.W. Increased fetal DNA concentrations in the plasma of pregnant women carrying fetuses with trisomy 21. Clin. Chem. 1999, 45, 1747–1751. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Grumaz, S.; Stevens, P.; Grumaz, C.; Decker, S.O.; Weigand, M.A.; Hofer, S.; Brenner, T.; von Haeseler, A.; Sohn, K. Next-generation sequencing diagnostics of bacteremia in septic patients. Genome Med. 2016, 8, 73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. van der Pol, Y.; Mouliere, F. Toward the Early Detection of Cancer by Decoding the Epigenetic and Environmental Fingerprints of Cell-Free DNA. Cancer Cell 2019, 36, 350–368. [Google Scholar] [CrossRef]
  77. Aucamp, J.; Bronkhorst, A.J.; Badenhorst, C.P.S.; Pretorius, P.J. The diverse origins of circulating cell-free DNA in the human body: A critical re-evaluation of the literature. Biol. Rev. 2018, 93, 1649–1683. [Google Scholar] [CrossRef]
  78. Moss, J.; Magenheim, J.; Neiman, D.; Zemmour, H.; Loyfer, N.; Korach, A.; Samet, Y.; Maoz, M.; Druid, H.; Arner, P.; et al. Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease. Nat. Commun. 2018, 9, 5068. [Google Scholar] [CrossRef] [Green Version]
  79. Kahlert, C.; Melo, S.; Protopopov, A.; Tang, J.; Seth, S.; Koch, M.; Zhang, J.; Weitz, J.; Chin, L.; Futreal, A.; et al. Identification of Double-stranded Genomic DNA Spanning All Chromosomes with Mutated KRAS and p53 DNA in the Serum Exosomes of Patients with Pancreatic Cancer. J. Biol. Chem. 2014, 289, 3869–3875. [Google Scholar] [CrossRef] [Green Version]
  80. Nagata, S. Apoptotic DNA fragmentation. Exp. Cell Res. 2000, 256, 12–18. [Google Scholar] [CrossRef]
  81. Fleischhacker, M.; Schmidt, B. Circulating nucleic acids (CNAs) and cancer—A survey. Biochim. Biophys. Acta (BBA)-Rev. Cancer 2007, 1775, 181–232. [Google Scholar] [CrossRef]
  82. Leon, S.A.; Shapiro, B.; Sklaroff, D.M.; Yaros, M.J. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Res. 1977, 37, 646–650. [Google Scholar]
  83. Lyberopoulou, A.; Aravantinos, G.; Efstathopoulos, E.P.; Nikiteas, N.; Bouziotis, P.; Isaakidou, A.; Papalois, A.; Marinos, E.; Gazouli, M. Mutational Analysis of Circulating Tumor Cells from Colorectal Cancer Patients and Correlation with Primary Tumor Tissue. PLoS ONE 2015, 10, e0123902. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Kinugasa, H.; Nouso, K.; Miyahara, K.; Morimoto, Y.; Dohi, C.; Tsutsumi, K.; Kato, H.; Okada, H.; Yamamoto, K. Detection of K-ras gene mutation by liquid biopsy in patients with pancreatic cancer. Cancer 2015, 121, 2271–2280. [Google Scholar] [CrossRef]
  85. Lebofsky, R.; Decraene, C.; Bernard, V.; Kamal, M.; Blin, A.; Leroy, Q.; Frio, T.R.; Pierron, G.; Callens, C.; Bieche, I.; et al. Circulating tumor DNA as a non-invasive substitute to metastasis biopsy for tumor genotyping and personalized medicine in a prospective trial across all tumor types. Mol. Oncol. 2014, 9, 783–790. [Google Scholar] [CrossRef] [Green Version]
  86. Mouliere, F.; Chandrananda, D.; Piskorz, A.M.; Moore, E.K.; Morris, J.; Ahlborn, L.B.; Mair, R.; Goranova, T.; Marass, F.; Heider, K.; et al. Enhanced detection of circulating tumor DNA by fragment size analysis. Sci. Transl. Med. 2018, 10, eaat4921. [Google Scholar] [CrossRef] [Green Version]
  87. Shen, S.Y.; Singhania, R.; Fehringer, G.; Chakravarthy, A.; Roehrl, M.H.A.; Chadwick, D.; Zuzarte, P.C.; Borgida, A.; Wang, T.T.; Li, T.; et al. Sensitive tumour detection and classification using plasma cell-free DNA methylomes. Nature 2018, 563, 579–583. [Google Scholar] [CrossRef]
  88. Riva, F.; Dronov, O.I.; Khomenko, D.I.; Huguet, F.; Louvet, C.; Mariani, P.; Stern, M.-H.; Lantz, O.; Proudhon, C.; Pierga, J.-Y.; et al. Clinical applications of circulating tumor DNA and circulating tumor cells in pancreatic cancer. Mol. Oncol. 2016, 10, 481–493. [Google Scholar] [CrossRef]
  89. Iqbal, M.; Kasi, P.M.; Mody, K. Feasibility and clinical value of circulating tumor DNA testing in patients with gastroesophageal adenocarcinoma. J. Clin. Oncol. 2018, 36, e16045. [Google Scholar] [CrossRef]
  90. Moran, S.; Martínez-Cardús, A.; Sayols, S.; Musulén, E.; Balañá, C.; Estival-Gonzalez, A.; Moutinho, C.; Heyn, H.; Diaz-Lagares, A.; de Moura, M.C.; et al. Epigenetic profiling to classify cancer of unknown primary: A multicentre, retrospective analysis. Lancet Oncol. 2016, 17, 1386–1395. [Google Scholar] [CrossRef]
  91. Tham, C.; Chew, M.; Soong, R.; Lim, J.; Ang, M.; Tang, C.; Zhao, Y.; Ong, S.Y.K.; Liu, Y. Postoperative serum methylation levels of TAC1 and SEPT9 are independent predictors of recurrence and survival of patients with colorectal cancer. Cancer 2014, 120, 3131–3141. [Google Scholar] [CrossRef] [PubMed]
  92. Siveke, J.T.; Lueong, S.; Hinke, A.; Herbst, A.; Tannapfel, A.; Reinacher-Schick, A.C.; Kolligs, F.T.; Hegewisch-Becker, S. Serial analysis of mutant KRAS in circulation cell-free DNA (cfDNA) of patients with KRAS mutant metastatic colorectal cancer: A translational study of the KRK0207 trial. J. Clin. Oncol. 2018, 36, e15599. [Google Scholar] [CrossRef]
  93. 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, 224. [Google Scholar] [CrossRef] [Green Version]
  94. Liu, M.; Klein, E.; Hubbell, E.; Maddala, T.; Aravanis, A.; Beausang, J.; Filippova, D.; Gross, S.; Jamshidi, A.; Kurtzman, K.; et al. Plasma cell-free DNA (cfDNA) assays for early multi-cancer detection: The circulating cell-free genome atlas (CCGA) study. Ann. Oncol. 2018, 29, viii14. [Google Scholar] [CrossRef]
  95. Liu, M.C.; Oxnard, G.R.; Klein, E.A.; Swanton, C.; Seiden, M.V.; CCGA Consortium. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann. Oncol. 2020, 31, 745–759. [Google Scholar] [CrossRef] [PubMed]
  96. Payne, S.R.; Church, T.R.; Wandell, M.; Rösch, T.; Osborn, N.; Snover, D.; Day, R.W.; Ransohoff, D.F.; Rex, D.K. Endoscopic Detection of Proximal Serrated Lesions and Pathologic Identification of Sessile Serrated Adenomas/Polyps Vary on the Basis of Center. Clin. Gastroenterol. Hepatol. 2013, 12, 1119–1126. [Google Scholar] [CrossRef]
  97. Church, T.R.; Wandell, M.; Lofton-Day, C.; Mongin, S.J.; Burger, M.; Payne, S.R.; Castaños-Vélez, E.; Blumenstein, B.A.; Rösch, T.; Osborn, N.; et al. Prospective evaluation of methylated SEPT9 in plasma for detection of asymptomatic colorectal cancer. Gut 2013, 63, 317–325. [Google Scholar] [CrossRef] [Green Version]
  98. Taryma-Leśniak, O.; Sokolowska, K.E.; Wojdacz, T.K. Current status of development of methylation biomarkers for in vitro diagnostic IVD applications. Clin. Epigenet. 2020, 12, 100. [Google Scholar] [CrossRef]
  99. 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]
  100. Taniguchi, H.; Nakamura, Y.; Kotani, D.; Yukami, H.; Mishima, S.; Sawada, K.; Shirasu, H.; Ebi, H.; Yamanaka, T.; Aleshin, A.; et al. CIRCULATE-Japan: Circulating tumor DNA–guided adaptive platform trials to refine adjuvant therapy for colorectal cancer. Cancer Sci. 2021, 112, 2915–2920. [Google Scholar] [CrossRef]
  101. Folprecht, G.; Reinacher-Schick, A.; Tannapfel, A.; Weitz, J.; Kossler, T.; Weiss, L.; Aust, D.E.; Von Bubnoff, N.; Kramer, M.; Thiede, C. Circulating tumor DNA-based decision for adjuvant treatment in colon cancer stage II evaluation: (CIRCULATE-trial) AIO-KRK-0217. J. Clin. Oncol. 2020, 38, TPS273. [Google Scholar] [CrossRef]
  102. Taïeb, J.; Benhaim, L.; Puig, P.L.; Le Malicot, K.; Emile, J.F.; Geillon, F.; Tougeron, D.; Manfredi, S.; Chauvenet, M.; Taly, V.; et al. Decision for adjuvant treatment in stage II colon cancer based on circulating tumor DNA: The CIRCULATE-PRODIGE 70 trial? Dig. Liver Dis. 2020, 52, 730–733. [Google Scholar] [CrossRef] [PubMed]
  103. Nors, J.; Henriksen, T.V.; Gotschalck, K.A.; Juul, T.; Søgaard, J.; Iversen, L.H.; Andersen, C.L. IMPROVE-IT2: Implementing noninvasive circulating tumor DNA analysis to optimize the operative and postoperative treatment for patients with colorectal cancer—Intervention trial 2. Study protocol. Acta Oncol. 2020, 59, 336–341. [Google Scholar] [CrossRef]
  104. Tjensvoll, K.; Lapin, M.; Buhl, T.; Oltedal, S.; Berry, K.S.-O.; Gilje, B.; Søreide, J.A.; Javle, M.; Nordgård, O.; Smaaland, R. Abstract 5241: Clinical relevance of circulating tumor DNA in plasma from pancreatic cancer patients. Cancer Res. 2015, 75, 5241. [Google Scholar] [CrossRef]
  105. Liu, X.; Guo, S.; Ma, C.; Li, Y.; Liu, X.; Zhang, Z.; Yu, L.; Dai, M.; Shen, S.; Wu, H.M.; et al. Circulating tumor DNA methylation as markers for early detection of pancreatic ductal adenocarcinoma (PDAC). J. Clin. Oncol. 2021, 39, 395. [Google Scholar] [CrossRef]
  106. Yang, J.; Gong, Y.; Lam, V.K.; Shi, Y.; Guan, Y.; Zhang, Y.; Ji, L.; Chen, Y.; Zhao, Y.; Qian, F.; et al. Deep sequencing of circulating tumor DNA detects molecular residual disease and predicts recurrence in gastric cancer. Cell Death Dis. 2020, 11, 346. [Google Scholar] [CrossRef]
  107. Kim, S.T.; Cristescu, R.; Bass, A.J.; Kim, K.-M.; Odegaard, J.I.; Kim, K.; Liu, X.Q.; Sher, X.; Jung, H.; Lee, M.; et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat. Med. 2018, 24, 1449–1458. [Google Scholar] [CrossRef]
  108. Willis, J.; Lefterova, M.I.; Artyomenko, A.; Kasi, P.M.; Nakamura, Y.; Mody, K.; Catenacci, D.V.; Fakih, M.; Barbacioru, C.; Zhao, J.; et al. Validation of Microsatellite Instability Detection Using a Comprehensive Plasma-Based Genotyping Panel. Clin. Cancer Res. 2019, 25, 7035–7045. [Google Scholar] [CrossRef] [PubMed]
  109. Lan, Y.-T.; Chen, M.-H.; Fang, W.-L.; Hsieh, C.-C.; Lin, C.-H.; Jhang, F.-Y.; Yang, S.-H.; Lin, J.-K.; Chen, W.-S.; Jiang, J.-K.; et al. Clinical relevance of cell-free DNA in gastrointestinal tract malignancy. Oncotarget 2016, 8, 3009–3017. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  110. Qian, C.; Ju, S.; Qi, J.; Zhao, J.; Shen, X.; Jing, R.; Yu, J.; Li, L.; Shi, Y.; Zhang, L.; et al. Alu-based cell-free DNA: A novel biomarker for screening of gastric cancer. Oncotarget 2016, 8, 54037–54045. [Google Scholar] [CrossRef] [Green Version]
  111. Kim, K.; Shin, D.G.; Park, M.K.; Baik, S.H.; Kim, T.H.; Kim, S.; Lee, S. Circulating cell-free DNA as a promising biomarker in patients with gastric cancer: Diagnostic validity and significant reduction of cfDNA after surgical resection. Ann. Surg. Treat. Res. 2014, 86, 136–142. [Google Scholar] [CrossRef] [Green Version]
  112. Eissa, M.A.L.; Lerner, L.; Abdelfatah, E.; Shankar, N.; Canner, J.K.; Hasan, N.M.; Yaghoobi, V.; Huang, B.; Kerner, Z.; Takaesu, F.; et al. Promoter methylation of ADAMTS1 and BNC1 as potential biomarkers for early detection of pancreatic cancer in blood. Clin. Epigenet. 2019, 11, 59. [Google Scholar] [CrossRef] [PubMed]
  113. Bernard, V.; Kim, D.U.; Lucas, F.A.S.; Castillo, J.; Allenson, K.; Mulu, F.C.; Stephens, B.M.; Huang, J.; Semaan, A.; Guerrero, P.A.; et al. Circulating Nucleic Acids Are Associated with Outcomes of Patients with Pancreatic Cancer. Gastroenterology 2019, 156, 108–118.e4. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  114. Tie, J.; Wang, Y.; Tomasetti, C.; Li, L.; Springer, S.; Kinde, I.; Silliman, N.; Tacey, M.; Wong, H.-L.; Christie, M.; et al. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci. Transl. Med. 2016, 8, 346ra92. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  115. Tie, J.; Cohen, J.D.; Wang, Y.; Li, L.; Christie, M.; Simons, K.; Elsaleh, H.; Kosmider, S.; Wong, R.; Yip, D.; et al. Serial circulating tumour DNA analysis during multimodality treatment of locally advanced rectal cancer: A prospective biomarker study. Gut 2018, 68, 663–671. [Google Scholar] [CrossRef]
  116. Uesato, Y.; Sasahira, N.; Ozaka, M.; Sasaki, T.; Takatsuki, M.; Zembutsu, H. Evaluation of circulating tumor DNA as a biomarker in pancreatic cancer with liver metastasis. PLoS ONE 2020, 15, e0235623. [Google Scholar] [CrossRef]
  117. Pietrasz, D.; Pécuchet, N.; Garlan, F.; Didelot, A.; Dubreuil, O.; Doat, S.; Imbert-Bismut, F.; Karoui, M.; Vaillant, J.-C.; Taly, V.; et al. Plasma Circulating Tumor DNA in Pancreatic Cancer Patients Is a Prognostic Marker. Clin. Cancer Res. 2017, 23, 116–123. [Google Scholar] [CrossRef] [Green Version]
  118. Patel, H.; Okamura, R.; Fanta, P.; Patel, C.; Lanman, R.B.; Raymond, V.M.; Kato, S.; Kurzrock, R. Clinical correlates of blood-derived circulating tumor DNA in pancreatic cancer. J. Hematol. Oncol. 2019, 12, 130. [Google Scholar] [CrossRef] [Green Version]
  119. Takai, E.; Totoki, Y.; Nakamura, H.; Morizane, C.; Nara, S.; Hama, N.; Suzuki, M.; Furukawa, E.; Kato, M.; Hayashi, H.; et al. Clinical utility of circulating tumor DNA for molecular assessment in pancreatic cancer. Sci. Rep. 2015, 5, 18425. [Google Scholar] [CrossRef] [Green Version]
  120. Chen, I.; Raymond, V.M.; Geis, J.A.; Collisson, E.A.; Jensen, B.V.; Hermann, K.L.; Erlander, M.G.; Tempero, M.; Johansen, J.S. Ultrasensitive plasma ctDNA KRAS assay for detection, prognosis, and assessment of therapeutic response in patients with unresectable pancreatic ductal adenocarcinoma. Oncotarget 2017, 8, 97769–97786. [Google Scholar] [CrossRef] [Green Version]
  121. Botrus, G.; Kosirorek, H.; Sonbol, M.B.; Kusne, Y.; Uson, P.L.S.; Borad, M.J.; Ahn, D.H.; Kasi, P.M.; Drusbosky, L.M.; Dada, H.; et al. Circulating Tumor DNA-Based Testing and Actionable Findings in Patients with Advanced and Metastatic Pancreatic Adenocarcinoma. Oncol. 2021, 26, 569–578. [Google Scholar] [CrossRef]
  122. Sausen, M.; Phallen, J.; Adleff, V.; Jones, S.; Leary, R.J.; Barrett, M.T.; Anagnostou, V.; Parpart-Li, S.; Murphy, D.; Kay Li, Q.; et al. Clinical implications of genomic alterations in the tumour and circulation of pancreatic cancer patients. Nat. Commun. 2015, 6, 7686. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Lee, B.; Lipton, L.; Cohen, J.; Tie, J.; Javed, A.; Li, L.; Goldstein, D.; Burge, M.; Cooray, P.; Nagrial, A.; et al. Circulating tumor DNA as a potential marker of adjuvant chemotherapy benefit following surgery for localized pancreatic cancer. Ann. Oncol. 2019, 30, 1472–1478. [Google Scholar] [CrossRef] [PubMed]
  124. Théry, C. Exosomes: Secreted vesicles and intercellular communications. F1000 Biol. Rep. 2011, 3, 15. [Google Scholar] [CrossRef]
  125. Cheng, L.; Sharples, R.A.; Scicluna, B.J.; Hill, A.F. Exosomes provide a protective and enriched source of miRNA for biomarker profiling compared to intracellular and cell-free blood. J. Extracell. Vesicles 2014, 3, 23743. [Google Scholar] [CrossRef] [PubMed]
  126. Rak, J. Microparticles in Cancer. Semin. Thromb. Hemost. 2010, 36, 888–906. [Google Scholar] [CrossRef] [Green Version]
  127. Hood, J.L.; San, R.S.; Wickline, S.A. Exosomes Released by Melanoma Cells Prepare Sentinel Lymph Nodes for Tumor Metastasis. Cancer Res. 2011, 71, 3792–3801. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  128. Li, A.; Zhang, T.; Zheng, M.; Liu, Y.; Chen, Z. Exosomal proteins as potential markers of tumor diagnosis. J. Hematol. Oncol. 2017, 10, 175. [Google Scholar] [CrossRef] [Green Version]
  129. Liangsupree, T.; Multia, E.; Riekkola, M.-L. Modern isolation and separation techniques for extracellular vesicles. J. Chromatogr. A 2020, 1636, 461773. [Google Scholar] [CrossRef]
  130. Cai, X.; Janku, F.; Zhan, Q.; Fan, J.-B. Accessing Genetic Information with Liquid Biopsies. Trends Genet. 2015, 31, 564–575. [Google Scholar] [CrossRef]
  131. Xu, R.; Greening, D.W.; Zhu, H.-J.; Takahashi, N.; Simpson, R.J. Extracellular vesicle isolation and characterization: Toward clinical application. J. Clin. Investig. 2016, 126, 1152–1162. [Google Scholar] [CrossRef] [Green Version]
  132. Hoshino, A.; Costa-Silva, B.; Shen, T.-L.; Rodrigues, G.; Hashimoto, A.; Mark, M.T.; Molina, H.; Kohsaka, S.; Di Giannatale, A.; Ceder, S.; et al. Tumour exosome integrins determine organotropic metastasis. Nature 2015, 527, 329–335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  133. Théry, C.; Amigorena, S.; Raposo, G.; Clayton, A. Isolation and characterization of exosomes from cell culture supernatants and biological fluids. Curr. Protoc. Cell Biol. 2006, 30, 3.22.1–3.22.29. [Google Scholar] [CrossRef] [PubMed]
  134. Fan, Y.; Che, X.; Qu, J.; Hou, K.; Wen, T.; Li, Z.; Li, C.; Wang, S.; Xu, L.; Liu, Y.; et al. Exosomal PD-L1 Retains Immunosuppressive Activity and is Associated with Gastric Cancer Prognosis. Ann. Surg. Oncol. 2019, 26, 3745–3755. [Google Scholar] [CrossRef] [PubMed]
  135. Zheng, J.; Hernandez, J.M.; Doussot, A.; Bojmar, L.; Zambirinis, C.P.; Costa-Silva, B.; Van Beek, E.J.A.H.; Mark, M.T.; Molina, H.; Askan, G.; et al. Extracellular matrix proteins and carcinoembryonic antigen-related cell adhesion molecules characterize pancreatic duct fluid exosomes in patients with pancreatic cancer. HPB 2018, 20, 597–604. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  136. Jin, H.; Liu, P.; Wu, Y.; Meng, X.; Wu, M.; Han, J.; Tan, X. Exosomal zinc transporter ZIP4 promotes cancer growth and is a novel diagnostic biomarker for pancreatic cancer. Cancer Sci. 2018, 109, 2946–2956. [Google Scholar] [CrossRef] [Green Version]
  137. Melo, S.A.; Luecke, L.B.; Kahlert, C.; Fernandez, A.F.; Gammon, S.T.; Kaye, J.; LeBleu, V.S.; Mittendorf, E.A.; Weitz, J.; Rahbari, N.; et al. Glypican-1 identifies cancer exosomes and detects early pancreatic cancer. Nature 2015, 523, 177–182. [Google Scholar] [CrossRef] [Green Version]
  138. Lin, K.; Baenke, F.; Lai, X.; Schneider, M.; Helm, D.; Polster, H.; Rao, V.S.; Ganig, N.; Wong, F.C.; Seifert, L.; et al. Comprehensive proteomic profiling of serum extracellular vesicles in patients with colorectal liver metastases identifies a signature for non-invasive risk stratification and early-response evaluation. Mol. Cancer 2022, 21, 91. [Google Scholar] [CrossRef]
  139. Tao, L.; Zhou, J.; Yuan, C.; Zhang, L.; Li, D.; Si, D.; Xiu, D.; Zhong, L. Metabolomics identifies serum and exosomes metabolite markers of pancreatic cancer. Metabolomics 2019, 15, 86. [Google Scholar] [CrossRef]
  140. Kitagawa, T.; Taniuchi, K.; Tsuboi, M.; Sakaguchi, M.; Kohsaki, T.; Okabayashi, T.; Saibara, T. Circulating pancreatic cancer exosomal RNA s for detection of pancreatic cancer. Mol. Oncol. 2018, 13, 212–227. [Google Scholar] [CrossRef] [Green Version]
  141. Pascucci, L.; Coccè, V.; Bonomi, A.; Ami, D.; Ceccarelli, P.; Ciusani, E.; Viganò, L.; Locatelli, A.; Sisto, F.; Doglia, S.M.; et al. Paclitaxel is incorporated by mesenchymal stromal cells and released in exosomes that inhibit in vitro tumor growth: A new approach for drug delivery. J. Control. Release 2014, 192, 262–270. [Google Scholar] [CrossRef]
  142. Agrawal, A.K.; Aqil, F.; Jeyabalan, J.; Spencer, W.A.; Beck, J.; Gachuki, B.W.; Alhakeem, S.S.; Oben, K.; Munagala, R.; Bondada, S.; et al. Milk-derived exosomes for oral delivery of paclitaxel. Nanomed. Nanotechnol. Biol. Med. 2017, 13, 1627–1636. [Google Scholar] [CrossRef]
  143. Batista, I.A.; Melo, S.A. Exosomes and the Future of Immunotherapy in Pancreatic Cancer. Int. J. Mol. Sci. 2019, 20, 567. [Google Scholar] [CrossRef] [Green Version]
  144. Tang, G.; Wang, J.; Dong, W.; Dai, K.; Du, J. Exosomal miRNA Expression Profiling and the Roles of Exosomal miR-4741, miR-32, miR-3149, and miR-6727 on Gastric Cancer Progression. BioMed Res. Int. 2022, 2022, 1263812. [Google Scholar] [CrossRef] [PubMed]
  145. Zhou, H.; Shen, W.; Zou, H.; Lv, Q.; Shao, P. Circulating exosomal long non-coding RNA H19 as a potential novel diagnostic and prognostic biomarker for gastric cancer. J. Int. Med. Res. 2020, 48, 300060520934297. [Google Scholar] [CrossRef] [PubMed]
  146. Zheng, P.; Gao, H.; Xie, X.; Lu, P. Plasma Exosomal hsa_circ_0015286 as a Potential Diagnostic and Prognostic Biomarker for Gastric Cancer. Pathol. Oncol. Res. 2022, 28, 1610446. [Google Scholar] [CrossRef] [PubMed]
  147. Fu, H.; Yang, H.; Zhang, X.; Wang, B.; Mao, J.; Li, X.; Wang, M.; Zhang, B.; Sun, Z.; Qian, H.; et al. Exosomal TRIM3 is a novel marker and therapy target for gastric cancer. J. Exp. Clin. Cancer Res. 2018, 37, 162. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  148. Che, Y.; Geng, B.; Xu, Y.; Miao, X.; Chen, L.; Mu, X.; Pan, J.; Zhang, C.; Zhao, T.; Wang, C.; et al. Helicobacter pylori -induced exosomal MET educates tumour-associated macrophages to promote gastric cancer progression. J. Cell. Mol. Med. 2018, 22, 5708–5719. [Google Scholar] [CrossRef]
  149. Ostenfeld, M.S.; Jensen, S.G.; Jeppesen, D.K.; Christensen, L.L.; Thorsen, S.B.; Stenvang, J.; Nielsen, H.J.; Thomsen, A.; Mouritzen, P.; Rasmussen, M.H.; et al. miRNA profiling of circulating EpCAM+ extracellular vesicles: Promising biomarkers of colorectal cancer. J. Extracell Vesicles 2016, 5, 31488. [Google Scholar] [CrossRef] [Green Version]
  150. Julich-Haertel, H.; Urban, S.K.; Krawczyk, M.; Willms, A.; Jankowski, K.; Patkowski, W.; Kruk, B.; Krasnodębski, M.; Ligocka, J.; Schwab, R.; et al. Cancer-associated circulating large extracellular vesicles in cholangiocarcinoma and hepatocellular carcinoma. J. Hepatol. 2017, 67, 282–292. [Google Scholar] [CrossRef]
  151. Yan, L.; Dong, X.; Gao, J.; Liu, F.; Zhou, L.; Sun, Y.; Zhao, X. A novel rapid quantitative method reveals stathmin-1 as a promising marker for esophageal squamous cell carcinoma. Cancer Med. 2018, 7, 1802–1813. [Google Scholar] [CrossRef]
  152. Tian, Y.; Ma, L.; Gong, M.; Su, G.; Zhu, S.; Zhang, W.; Wang, S.; Li, Z.; Chen, C.; Li, L.; et al. Protein Profiling and Sizing of Extracellular Vesicles from Colorectal Cancer Patients via Flow Cytometry. ACS Nano 2018, 12, 671–680. [Google Scholar] [CrossRef] [PubMed]
  153. Bavisotto, C.C.; Cappello, F.; Macario, A.J.; de Macario, E.C.; Logozzi, M.; Fais, S.; Campanella, C. Exosomal HSP60: A potentially useful biomarker for diagnosis, assessing prognosis, and monitoring response to treatment. Expert Rev. Mol. Diagn. 2017, 17, 815–822. [Google Scholar] [CrossRef] [PubMed]
  154. Li, J.; Chen, Y.; Guo, X.; Zhou, L.; Jia, Z.; Peng, Z.; Tang, Y.; Liu, W.; Zhu, B.; Wang, L.; et al. GPC1 exosome and its regulatory miRNAs are specific markers for the detection and target therapy of colorectal cancer. J. Cell. Mol. Med. 2017, 21, 838–847. [Google Scholar] [CrossRef]
  155. Sun, B.; Li, Y.; Zhou, Y.; Ng, T.K.; Zhao, C.; Gan, Q.; Gu, X.; Xiang, J. Circulating exosomal CPNE3 as a diagnostic and prognostic biomarker for colorectal cancer. J. Cell. Physiol. 2018, 234, 1416–1425. [Google Scholar] [CrossRef] [PubMed]
  156. Franco, A.T.; Corken, A.; Ware, J. Platelets at the interface of thrombosis, inflammation, and cancer. Blood 2015, 126, 582–588. [Google Scholar] [CrossRef] [Green Version]
  157. Lambert, A.W.; Pattabiraman, D.R.; Weinberg, R.A. Emerging Biological Principles of Metastasis. Cell 2017, 168, 670–691. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  158. Menter, D.G.; Kopetz, S.; Hawk, E.; Sood, A.K.; Loree, J.M.; Gresele, P.; Honn, K.V. Platelet "first responders" in wound response, cancer, and metastasis. Cancer Metastasis Rev. 2017, 36, 199–213. [Google Scholar] [CrossRef]
  159. Naderi-Meshkin, H.; Ahmadiankia, N. Cancer metastasis versus stem cell homing: Role of platelets. J. Cell. Physiol. 2018, 233, 9167–9178. [Google Scholar] [CrossRef]
  160. Haemmerle, M.; Stone, R.L.; Menter, D.G.; Afshar-Kharghan, V.; Sood, A.K. The Platelet Lifeline to Cancer: Challenges and Opportunities. Cancer Cell 2018, 33, 965–983. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  161. Olsson, A.; Cedervall, J. The pro-inflammatory role of platelets in cancer. Platelets 2018, 29, 569–573. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  162. Xu, X.R.; Yousef, G.M.; Ni, H. Cancer and platelet crosstalk: Opportunities and challenges for aspirin and other antiplatelet agents. Blood 2018, 131, 1777–1789. [Google Scholar] [CrossRef] [Green Version]
  163. Zhang, Q.; Liu, H.; Zhu, Q.; Zhan, P.; Zhu, S.; Zhang, J.; Lv, T.; Yong, S. Patterns and functional implications of platelets upon tumor "education". Int. J. Biochem. Cell Biol. 2017, 90, 68–80. [Google Scholar] [CrossRef]
  164. Mancuso, M.E.; Santagostino, E. Platelets: Much more than bricks in a breached wall. Br. J. Haematol. 2017, 178, 209–219. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  165. Hisada, Y.; Mackman, N. Cancer-associated pathways and biomarkers of venous thrombosis. Blood 2017, 130, 1499–1506. [Google Scholar] [CrossRef] [PubMed]
  166. Kanikarla-Marie, P.; Lam, M.; Menter, D.G.; Kopetz, S. Platelets, circulating tumor cells, and the circulome. Cancer Metastasis Rev. 2017, 36, 235–248. [Google Scholar] [CrossRef]
  167. Leblanc, R.; Peyruchaud, O. Metastasis: New functional implications of platelets and megakaryocytes. Blood 2016, 128, 24–31. [Google Scholar] [CrossRef]
  168. Kuznetsov, H.S.; Marsh, T.; Markens, B.A.; Castaño, Z.; Greene-Colozzi, A.; Hay, S.A.; Brown, V.E.; Richardson, A.L.; Signoretti, S.; Battinelli, E.M.; et al. Identification of Luminal Breast Cancers That Establish a Tumor-Supportive Macroenvironment Defined by Proangiogenic Platelets and Bone Marrow–Derived Cells. Cancer Discov. 2012, 2, 1150–1165. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  169. Best, M.G.; Sol, N.; Kooi, I.E.; Tannous, J.; Westerman, B.A.; Rustenburg, F.; Schellen, P.; Verschueren, H.; Post, E.; Koster, J.; et al. RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics. Cancer Cell 2015, 28, 666–676. [Google Scholar] [CrossRef] [Green Version]
  170. Tjon-Kon-Fat, L.-A.; Lundholm, M.; Schröder, M.; Wurdinger, T.; Thellenberg-Karlsson, C.; Widmark, A.; Wikström, P.; Nilsson, R.J.A. Platelets harbor prostate cancer biomarkers and the ability to predict therapeutic response to abiraterone in castration resistant patients. Prostate 2017, 78, 48–53. [Google Scholar] [CrossRef]
  171. Xiao, R.; Liu, C.; Zhang, B.; Ma, L. Tumor-Educated Platelets as a Promising Biomarker for Blood-Based Detection of Renal Cell Carcinoma. Front. Oncol. 2022, 12, 844520. [Google Scholar] [CrossRef]
  172. Best, M.G.; Veld, S.G.J.G.I.; Sol, N.; Wurdinger, T. RNA sequencing and swarm intelligence–enhanced classification algorithm development for blood-based disease diagnostics using spliced blood platelet RNA. Nat. Protoc. 2019, 14, 1206–1234. [Google Scholar] [CrossRef] [PubMed]
  173. Yang, L.; Jiang, Q.; Li, D.-Z.; Zhou, X.; Yu, D.-S.; Zhong, J. TIMP1 mRNA in tumor-educated platelets is diagnostic biomarker for colorectal cancer. Aging 2019, 11, 8998–9012. [Google Scholar] [CrossRef]
  174. Asghar, S.; Waqar, W.; Umar, M.; Manzoor, S. Tumor educated platelets, a promising source for early detection of hepatocellular carcinoma: Liquid biopsy an alternative approach to tissue biopsy. Clin. Res. Hepatol. Gastroenterol. 2020, 44, 836–844. [Google Scholar] [CrossRef] [PubMed]
  175. Ishibashi, Y.; Tsujimoto, H.; Sugasawa, H.; Kouzu, K.; Itazaki, Y.; Sugihara, T.; Harada, M.; Ito, N.; Kishi, Y.; Ueno, H. Prognostic value of platelet-related measures for overall survival in esophageal squamous cell carcinoma: A systematic review and meta-analysis. Crit. Rev. Oncol. 2021, 164, 103427. [Google Scholar] [CrossRef] [PubMed]
  176. Yang, W.; Zheng, X.; Wu, M.; Zhang, F.; Xu, S.; Wang, X.; Song, M.; You, C.; Zhang, T.; Jiang, M.; et al. Development and validation of postoperative and preoperative platelets ratio (PPR) to predict the prognosis of patients undergoing surgery for colorectal cancer: A dual-center retrospective cohort study. Cancer Med. 2022, 12, 111–121. [Google Scholar] [CrossRef]
  177. Zhang, L.-X.; Wei, Z.-J.; Xu, A.-M.; Zang, J.H. Can the neutrophil-lymphocyte ratio and platelet-lymphocyte ratio be beneficial in predicting lymph node metastasis and promising prognostic markers of gastric cancer patients? Tumor maker retrospective study. Int. J. Surg. 2018, 56, 320–327. [Google Scholar] [CrossRef]
  178. Cohen, J.D.; Li, L.; Wang, Y.; Thoburn, C.; Afsari, B.; Danilova, L.; Douville, C.; Javed, A.A.; Wong, F.; Mattox, A.; et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 2018, 359, 926–930. [Google Scholar] [CrossRef] [Green Version]
  179. Sabrkhany, S.; Kuijpers, M.J.; van Kuijk, S.M.; Sanders, L.; Pineda, S.; Damink, S.O.; Dingemans, A.-M.C.; Griffioen, A.W.; Egbrink, M.G.O. A combination of platelet features allows detection of early-stage cancer. Eur. J. Cancer 2017, 80, 5–13. [Google Scholar] [CrossRef]
  180. Sabrkhany, S.; Kuijpers, M.J.E.; Knol, J.C.; Olde Damink, S.W.M.; Dingemans, A.C.; Verheul, H.M.; Piersma, S.R.; Pham, T.V.; Griffioen, A.W.; Oude Egbrink, M.G.A.; et al. Exploration of the platelet proteome in patients with early-stage cancer. J. Proteom. 2018, 177, 65–74. [Google Scholar] [CrossRef]
  181. Peterson, J.E.; Zurakowski, D.; Italiano, J.E., Jr.; Michel, L.V.; Connors, S.; Oenick, M.; D’Amato, R.J.; Klement, G.L.; Folkman, J. VEGF, PF4 and PDGF are elevated in platelets of colorectal cancer patients. Angiogenesis 2012, 15, 265–273. [Google Scholar] [CrossRef]
Cancers 15 01924 g001 550
Figure 1. Clinical application of liquid biopsy (LB) in gastrointestinal cancer (GICs). Circulating tumor cells (CTCs), cell-free or circulating tumor DNA (cfDNA/ctDNA), tumor-educated platelets (TEP), exosomes, and RBCs in the blood of GICs patients can be used as potential biomarkers for LBs and their expression levels can be measured to determine the clinical status of GICs patients.
Figure 1. Clinical application of liquid biopsy (LB) in gastrointestinal cancer (GICs). Circulating tumor cells (CTCs), cell-free or circulating tumor DNA (cfDNA/ctDNA), tumor-educated platelets (TEP), exosomes, and RBCs in the blood of GICs patients can be used as potential biomarkers for LBs and their expression levels can be measured to determine the clinical status of GICs patients.
Cancers 15 01924 g001
Cancers 15 01924 g002 550
Figure 2. Techniques for detection of LB biomarkers in GICs. (a) Detection of CTCs, (b) detection of ctDNAs, (c) detection of tumor-educated platelets, and (d) detection of exosomes.
Figure 2. Techniques for detection of LB biomarkers in GICs. (a) Detection of CTCs, (b) detection of ctDNAs, (c) detection of tumor-educated platelets, and (d) detection of exosomes.
Cancers 15 01924 g002
Table
Table 1. Clinical relevance of CTCs in GICs.
Table 1. Clinical relevance of CTCs in GICs.
Cancer TypeThresholdSample Size (Number)SensitivitySpecificityAUCClinical SignificanceReferences
Gastric cancer2 CTCs11685.390.30.928Distinguish between GC patients and healthy controls and provide clinical output[50]
Gastric cancerCTC-PD-L132 with progressive GCs Monitor prognosis and guide future individualized immunotherapy[51]
Gastric cancerCSV+PD-L1+CTCs7071 Predicts treatment response and prognosis in GC patients[52]
Gastric cancerCTCs and TWIST32 with metastatic cancer80.6 As a prognostic marker[53]
Gastric cancerCTCs/cfDNA45 patients with progressive GC95.6 Predicting the efficacy and prognosis of neoadjuvant chemotherapy for progressive GC[54]
Colorectal cancer≥3 (chemotherapy and serum CEA)121 Presence of CTCs might be valuable for predicting survival outcome[55]
Non-metastatic colorectal cancer (NMCRC)≥4 (CS. CK19, MUC1, CD44, CD133 and ALDH1)6368.395 CTCs could be novel therapeutic targets for NMCRC[56]
Metastatic colorectal cancer (mCRC)≥1.92 (CEACAM)436 Detection of peripheral blood CEACAM5 mRNA-positive CTCs as an adverse prognostic factor correlated with poor clinical outcome in patients with mCRC[57]
Duke’s stage B and C colorectal cancer(carcinoembryonic antigen CEA), cytokeratin (CK) 19, CK20, and/or CD133 (CEA/CK/CD133)735 CTC as a detection marker in patients with Duke’s stage B and C[58]
Advanced CRC≥3 CTCs (EpCAM, CK and CD45)467 CTC count before and during chemotherapy treatment as an independent predictor of PFS and OS in advanced CRC patients[59]
Colorectal cancer≥3 CTCs (EpCAM, CK and CD45)430 CTC count before and during chemotherapy treatment as an independent predictor of PFS and OS during metastatic CRC patients[60]
Hepatocellular carconoma≥5 CTCs EpCAM and mucin173 CTCs could possibly be a novel prognostic biomarker in HCC[61]
Hepatocellular carconoma≥2 CTCs, EpCAM, CD8/18/19964 The CellSearch system could determine the clinical utility of CTCs in HCC[25]
Hepatocellular carconoma≥5 CTCs, Glypican-385 GPC-3 as a useful biomarker for HCC patient outcomes[62]
Hepatocellular carconomaEpCAM299 CTC detection by qPCR could be utilized in clinics for auxiliary diagnosis, treatment response assessment, and decision making[63]
Hepatocellular carconomaASGPR, Hep Par 185 A highly sensitive and specific CTC detection tool[64]
Hepatocellular carconoma(EpCAM)/vimentin/Glypican-3 (GPC3)4496.9498.12 A convenient and feasible CTC capture system to predict clinical outcomes in HCC patients[65]
Hepatocellular carconomaPD-L18771.191.8 Favorable response to anti-PD-1 therapy is associated with the presence of PD-L1+ CTCs[66]
Hepatocellular carconomapERK+/pAkt− CTCs109 pERK+/pAkt− CTCs are sensible to sorafenib[67]
Pancreatic cancerISET165 Higher CTC counts correlate with earlier recurrence. Increase in CTC numbers after neoadjuvant treatment. CTC+ correlates with early recurrence and OS in the pretreated group.[68]
Pancreatic cancerCK20172 CTC predicts poor OS[69]
Pancreatic cancerCK20258890 CTCs predict the prognosis of pancreatic cancer[70]
Pancreatic cancerNanoVelcro CTC assay (CK)100 CTC as a promising prognostic biomarker for PDAC patients[71]
Pancreatic cancerLIN28B35 Molecular characterization of CTCs provides a unique opportunity to correlate gene set metastatic profiles, identify drivers of dissemination, and develop therapies targeting the “seeds” of metastasis[72]
Table
Table 2. Clinical relevance of ctDNA/cfDNA in GICs.
Table 2. Clinical relevance of ctDNA/cfDNA in GICs.
Cancer TypeSample SizeSensitivity (%)Specificity (%)AUCClinical SignificanceReferences
Gastric cancer46 patients with stage I–III GC39100 MRD with ctDNA testing identifies patients at high risk of recurrence[106]
Gastric cancer61 cases of partially metastatic GC Associated with improved prognosis[107]
Gastric cancer114587 0.984Potential to expand access to targetted therapies and immunotherapy to all patients with advanced cancer[108]
Gastric cancer42868.995.80.98Predicts response to chemotherapy and surgery in patients with CRC; tumor recurrence should be considered in GC with persistently elevated cfDNAs levels after surgery[109]
Gastric cancer12478.9691.810.94For early screening of GC[110]
Gastric cancer3096.6794.110.991For early detection of cancer and assessment of tumor load[111]
Pancreatic cancer3997.391.6 Minimal invasive blood-based biomarker panel which could potentially be used as a diagnostic and screening tool in a select subset of high-risk populations[112]
Pancreatic cancer194 ctDNA in combination with exosomal DNA provides both predictive and prognostic information relevant to therapeutic stratification[113]
Colorectal cancer455 Reduced the usage of adjuvant chemotherapy [99]
Colorectal cancer250 Detection of residual disease [114]
Locally advanced rectal cancer (LARC)462 ctDNA analysis as a useful guide for adjuvant chemotherapy selection in LARC patients[115]
Pancreatic cancer with liver metastasis104 Use of circulating tumor DNA as an independent prognostic marker for advanced pancreatic cancer[116]
Pancreatic cancer135 ctDNA as an independent prognostic marker in advanced PDAC as well as an indicator of shorter disease-free survival in resected patients when detected after surgery[117]
Pancreatic cancer112 Increased ctDNA levels were a poor prognostic factor for survival.[118]
Pancreatic cancer259 Plasma cfDNA might provide a prognostic and diagnostic tool to assist surgical decision-making in PDAC patients[119]
Pancreatic cancer189 Longitudinal ctDNA KRAS assists in therapeutical decision-making and provides a kinetically robust and quantitative measurement of patient response.[120]
Pancreatic cancer1718688 ctDNA methylation approach to discriminate PDAC plasma from non-malignant diseases [105,121]
Pancreatic cancer101 ctDNA as genetic predictors of result in pancreatic cancer and might open new avenues of therapeutic intervention.[122]
Pancreatic cancer112 ctDNA-guided approach intensified the treatment strategies for pancreatic cancer patients. [123]
Table
Table 3. Clinical relevance of Exosomes in GICs.
Table 3. Clinical relevance of Exosomes in GICs.
Cancer TypeBiomarkersSample TypeExpressionClinical SignificanceReferences
Gastric cancermiRNA-4741, miR-32, miR-3149 and miR-6727tissue and plasmamiR-4741—upregulated
miR-32, miR-3149 and miR-6727—downregulated		Acts as a diagnostic marker for GC and an influential factor in inhibiting GC progression[144]
Gastric cancerLncRNAH19GCserumdownregulatedPossible biomarkers with diagnostic and prognostic value[145]
Gastric cancerhsa_circ_00115286tissue, plasma, and cellsupregulatedPossibly a non-invasive biomarker for GC diagnosis and prognostic assessment[146]
Gastric cancerTRIM3serumdownregulatedInhibition of GC progression in vitro and in vivo[147]
Gastric cancerMETcellsupregulatedAmplifies tumor growth and development in vitro and in vivo[148]
Colorectal cancerExo-EpCAMplasmaupregulated May have potential as non-invasive biomarkers for detection of CRC[149]
HCC/ColongiocarcinomaEpCAMserumupregulatedA novel non-invasive biomarker to assess the presence and possible extent of cancers in patients with advanced liver disease[150]
Esophageal cancerStathminserumupregulatedA very promising diagnostic and predictive marker for SCC in the clinic, especially for ESCC[151]
Colorectal cancerCD147bloodupregulatedEV-mediated intercellular communication and the development of advanced diagnostic and therapeutic strategies[152]
Colorectal liver metastasis (CRLM)CXCL17serumdownregulatedEV-bound CXCL7 was found as a biomarker of early response in CRLM patients receiving systemic chemotherapy[138]
HCC/ColongiocarcinomaCD147serumupregulatedA novel non-invasive biomarker to assess the presence and possible extent of cancers in patients with advanced liver disease[150]
Colorectal cancerHsp60cellsupregulatedBiomarker for diagnostics, assessing prognosis, and monitoring disease progression and response to treatment, particularly in cancer[153]
Colorectal cancerGlypican-1 (GPC1)plasmaupregulatedSpecific markers for the diagnosis of CRC and targets for the therapy of CRC.[154]
Colorectal cancerCopineIII (CPNE3)plasmaupregulatedExosomal CPNE3 show potential implications in CRC diagnosis and prognosis.[155]
Pancreatic cancerCEACAMspancreatic fluidupregulatedExosome isolation is feasible from pancreatic duct fluid, and that exosomal proteins may be utilized to diagnose patients with PDAC.[135]
Pancreatic cancerTenascin Cpancreatic fluidupregulatedExosome isolation is feasible from pancreatic duct fluid, and that exosomal proteins may be utilized to diagnose patients with PDAC.[135]
Pancreatic cancerGlypcan-1 (GCP-1)serumupregulatedGPC1+ crExos may serve as a potential non-invasive diagnostic and screening tool to detect early stages of pancreatic cancer to facilitate possible curative surgical therapy.[137]
Pancreatic cancerZIP-4cell lineupregulatedExosomal ZIP4 promotes cancer growth and is a novel diagnostic biomarker for pancreatic cancer[136]
Pancreatic cancerDNA MAFsplasmaupregulatedExosomal DNA in combination with ctDNA provides both predictive and prognostic information relevant to therapeutic stratification[113]
HCC/ColongiocarcinomaAnnexin VserumupregulatedA novel non-invasive biomarker to assess the presence and possible extent of cancers in patients with advanced liver disease[150]
Table
Table 4. Clinical relevance of tumor-educated platelets in GICs.
Table 4. Clinical relevance of tumor-educated platelets in GICs.
Cancer TypeSample Size (Number)SensitivitySpecificityAUCClinical SignificanceReferences
Gastric cancer904 NLR is better to predict overall survival than PLR in gastric cancer patients[177]
Stage I to III liver, stomach, pancreas, and esophagus100569–98%99% CancerSEEK localized cancer to a small number of anatomic sites in a median of 83% of the patients[178]
Pancreatic cancer42 82.70%Discriminate between patients with early-stage cancer and healthy individuals[179]
Pancreatic cancer4 Platelet proteome can be mined for potential biomarkers of cancer.[180]
Pan cancer (colorectal cancer, pancreatic cancer, hepatobiliary cancer)90 81%, 71%, 58%0.996, 0.999, 1.00Provides a valuable platform that could potentially enable clinical advances in blood-based liquid biopsies[169]
Liver cancer127 96 Provides a valuable platform that could potentially enable clinical advances in blood-based liquid biopsies[169]
Colorectal cancer35 0.893Differences between cancer and control samples in this study, although statistically significant, were not clinically significant[181]
Table
Table 5. Observational study with ongoing clinical trials of LB in GICs.
Table 5. Observational study with ongoing clinical trials of LB in GICs.
Liquid BiopsyStatusCancerStudy TitleStudy TypeClinical Trial IdentifierEstimated EnrollmentConditionsInterventionsLocations
CTC-1CTCRecruitingGastric cancerDetection of CTC in the Diagnosis of Metastasis in Gastric CancerObservationalNCT05208372200Stomach Neoplasms, MetastasisDiagnostic test: CTC testLiaoning, China
CTC-2CTCRecruitingGastric cancerTumor Cell and DNA Detection in the Blood, Urine and Bone Marrow of Patients With Solid CancersObservationalNCT02838836120Esophageal Cancer, Gastric Cancer, Pancreatic Cancer, Hepatocellular Cancer, Colorectal CancerProcedure: study sample collectionMissouri, United States
CTC-3CTCRecruitingGastric cancerTumor Cell and DNA Detection in the Blood, Urine, and Bone MarrowObservationalNCT03551951320Esophageal Cancer, Gastric Cancer, Pancreatic Cancer, Hepatocellular Cancer, Colorectal CancerDiagnostic test: test for circulating tumor cells, DNA alterationsMissouri, United States
CTC-4CTCRecruitingPancreatic cancerHeat Shock Protein (HSP) 70 to Quantify and Characterize Circulating Tumor Cells (HSP70CTC)Observational (Patient Registry)NCT04628806120Pancreatic Cancer Stage IVDiagnostic Test: CTC isolation by HSP70Berlin, Germany
CTC-5CTCRecruitingLiver cancerPrognostic Value of Liver Cancer CTCs Isolated by a Novel Microfluidic PlatformObservational (Patient Registry)NCT05242237300Hepatocellular Carcinoma, Circulating Tumor Cell, Whole Genome Sequencing Chongqing, China
CTC-6CTCRecruitingLiver cancerClinical Study for Combined Analysis of CTC and Exosomes on Predicting the Efficacy of Immunotherapy in Patients with Hepatocellular CarcinomaObservationalNCT05575622200HCCDevice: CTC PD-L1, exosomal PD-L1, and exosomal LAG-3 detectionHubei, China
CTC-7CTCRecruitingLiver cancerThe Role of Circulating Tumor Cells As Markers of Advanced Disease and Prognosis In HCCObservationalNCT04800497200Hepatocellular Carcinoma, Recurrent Hepatocellular Carcinoma, Circulating Tumor CellProcedure: hepatic resection4 locations in Italy
CTC-8CTCRecruitingColorectal cancerSample Collection Study for the CellMax Life Circulating Tumor Cell and Circulating Tumor DNA Platforms for the Early Detection of Colorectal Cancer and AdenomasObservationalNCT05127096100Colorectal Cancer ScreeningDiagnostic test: FirstSight blood testAlabama, California, United States
ctDNA-1ctDNARecruitingGastric cancerDetection of ctDNA in the Diagnosis of Metastasis in Gastric CancerObservationalNCT05208372200Stomach Neoplasms, MetastasisDiagnostic test: ctDNA testLiaoning, China
ctDNA-2ctDNARecruitingGastric cancerctDNA Screening in Advanced HER2 Positive Gastric CancerObservationalNCT04520295100HER2-Positive Gastric CancerGenetic: ctDNA screeningShanghai, China
ctDNA-3ctDNARecruitingGastric cancerMonitoring Minimal Residual Disease in Gastric Cancer by Liquid Biopsy Study DescriptionObservationalNCT05029869100Gastric Cancer, ctDNADiagnostic test: ctDNAHo Chi Minh City, Vietnam
ctDNA-4ctDNARecruitingGastric cancerPotential Clinical Utilities of Circulating Tumor DNA in Advanced HER2 Negative Gastric CancerObservationalNCT0551314430Gastric Cancer, ctDNA Jiangsu, China
ctDNA-5ctDNARecruitingGastric cancerDetection of Plasma Circulating Tumor DNA in Gastric CancerObservationalNCT05027347200ctDNA, Gastric CancerDiagnostic test: plasma circulating tumor DNAHo Chi Minh City, Vietnam
ctDNA-6ctDNARecruitingGastric cancerClinical Utility of Circulating Tumor DNA in Gastro-Esophageal Cancer (CURE)ObservationalNCT045768581950Esophageal Cancer, Gastric CancerDiagnostic test: circulating tumor DNACopenhagen, Denmark
ctDNA-7ctDNARecruitingPancreatic cancerObservational Study of ctDNA in Resectable and Borderline Resectable Pancreatic CancerObservationalNCT0537990730Pancreatic CancerOther: SIGNATERA™ ctDNA testingVirginia, United States
ctDNA-8ctDNARecruitingPancreatic cancerctDNA Assay in Patients with Resectable Pancreatic CancerObservationalNCT0505267150Pancreas Cancer Oklahoma, United States
ctDNA-9ctDNARecruitingPancreatic cancerLiquid Biopsy for ctDNA in Peritoneal Lavage and Blood in Pancreatic CancerObservational (Patient Registry)NCT05400681200Pancreatic Cancer, Pancreatic Adenocarcinoma Odense, Denmark
ctDNA-10ctDNARecruitingPancreatic cancerPrognostic Role of Circulating Tumor DNA in Resectable Pancreatic Cancer (PROJECTION)ObservationalNCT04246203200Pancreatic CancerOther: liquid BiopsyBavaria, Berlin, Cologne, Germany
ctDNA-11ctDNARecruitingPancreatic cancerDNA Mutation Detection in Circulating Tumor DNA and Tissue by mmADPS for Pancreatic CancerObservational (Patient Registry)NCT05604573150Pancreatic CancerDiagnostic Test: cell-free DNA in blood, genetic mutation in tissueSeoul, South Korea
ctDNA-12ctDNARecruitingLiver cancerTumor Cell and DNA Detection in the Blood, Urine and Bone Marrow of Patients with Solid CancersObservationalNCT02838836120Esophageal Cancer, Gastric Cancer, Pancreatic Cancer, Hepatocellular Cancer, Colorectal CancerProcedure: study sample collectionMissouri, United States
ctDNA-13ctDNARecruitingLiver cancerCohort Study of Patients with Hepatocellular Carcinoma and Circulating Tumor DNA Monitoring of Chemoembolization (Mona-Lisa)ObservationalNCT05390112167Circulating Tumor DNA Hepatocellular Carcinoma Non-resectableBiological: DNARouen, France
ctDNA-14ctDNARecruitingColorectal cancerComparison of Diagnostic Sensitivity Between ctDNA Methylation and CEA in Colorectal CancerObservational (Patient Registry)NCT05558436712Colorectal CancerDiagnostic test: detection of ctDNA methylationGuangdong, China
ctDNA-15ctDNARecruitingColorectal cancerRole of Circulating Tumour DNA Testing in Assessing for Alterations of Primary Anti-EGFR Resistance in RAS/RAF Wild-type Metastatic Colorectal Cancer PatientsObservationalNCT0505159240Colorectal Cancer Singapore, Singapore
ctDNA-16ctDNARecruitingColorectal cancerCirculating Tumor DNA Analysis to Optimize Treatment for Patients with Colorectal CancerObservationalNCT036376861800Colorectal Cancer 10 locations in Denmark
ctDNA-17ctDNARecruitingColorectal cancerTracking Mutations in Cell Free Tumour DNA to Predict Relapse in Early Colorectal Cancer (TRACC)ObservationalNCT040503451000Colorectal Cancer 36 locations in United Kingdom
ctDNA-18ctDNARecruitingColorectal cancerCirculating Tumour DNA (ctDNA) as a Prognostic and Predictive Marker in Colorectal Cancer—a Pilot StudyObservationalNCT04726800300Colorectal Cancer 8 locations in Sweden and Norway
ctDNA-19ctDNARecruitingColorectal cancerSample Collection Study for the CellMax Life Circulating Tumor Cell and Circulating Tumor DNA Platforms for the Early Detection of Colorectal Cancer and AdenomasObservationalNCT051270961000Colorectal Cancer ScreeningDiagnostic test: FirstSight blood test15 locations in United States
ctDNA-20ctDNARecruitingColorectal cancerDynamic Monitoring of ctDNA Methylation to Predict Relapse in Colorectal Cancer after Radical ResectionObservational (Patient Registry)NCT03737539300Colorectal Cancer, ctDNA, Surveillance, MethylationDiagnostic test: multigene methylation detectionShanghai, China
ctDNA-21ctDNARecruitingColorectal cancerEpidemiological Study to Monitor Study Participants With Resected Stage II (High Risk) or Stage III Colorectal Cancer for Circulating Tumor DNA before, during and after Their Treatment with Adjuvant ChemotherapyObservationalNCT048136271500Colorectal Cancer Stage II and IIIProcedure: regular blood sample collection for ctDNA assessment67 locations in United States
ctDNA-22ctDNARecruitingColorectal cancerBESPOKE Study of ctDNA Guided ImmunotherapyObservationalNCT047617831539Colorectal Cancer California, United States
exo-1ExosomesRecruitingGastric cancerUse of Circulating Exosomal LncRNA-GC1 to Monitor Gastric CancerObservationalNCT05397548700Gastric CancerDiagnostic test: measurement of levels of circulating exosomal lncRNA-GC1Beijing, China
exo-2ExosomesRecruitingPancreatic cancerInterrogation of Exosome-mediated Intercellular Signaling in Patients with Pancreatic CancerObservationalNCT02393703111Pancreatic Cancer, Benign Pancreatic Disease New York, United States
exo-3ExosomesRecruitingPancreatic cancerNew Biomarkers in Pancreatic Cancer Using EXPEL Concept (PANEXPEL)ObservationalNCT03791073200Oncology Montpellier, France
exo-4ExosomesRecruitingPancreatic cancerA Pancreatic Cancer Screening Study in Hereditary High Risk IndividualsObservationalNCT03250078100Pancreatic NeoplasmsDiagnostic test: MRI/MRCPConnecticut, United States
exo-5ExosomesRecruitingPancreatic cancerA Study of Blood Based Biomarkers for Pancreas AdenocarcinomaObservationalNCT03334708700Pancreatic Cancer, Pancreatic Diseases, Pancreatitis, Pancreatic CystDiagnostic test: blood draw, diagnostic test: tumor tissue collection, diagnostic test: cyst fluid13 locations in United States
exo-6ExosomesRecruitingLiver cancerA Study of Imaging, Blood, and Tissue Samples to Guide Treatment of Colon Cancer and Related Liver TumorsObservationalNCT0343280680Colon Cancer, Liver TumorOther: blood draws, procedure: colectomy or hepatectomy, diagnostic test: Fibroscan testNew Jersey, New York, United States
exo-7ExosomesRecruitingLiver cancerClinical Study for Combined Analysis of CTC and Exosomes on Predicting the Efficacy of Immunotherapy in Patients with Hepatocellular CarcinomaObservationalNCT05575622200HCCDevice: CTC PD-L1, exosomal PD-L1, and exosomal LAG-3 detectionHubei, China
TEP-1Tumor educated Platelets (TEP)RecruitingGastric cancerProject CADENCE (CAncer Detected Early caN be CurEd)ObservationalNCT0563334215,000Liver Cancer, Gastric Cancer, Colorectal Cancer, Esophageal Cancer, Pancreatic Cancer Singapore, Singapore
TEP-2Tumor educated Platelets (TEP)Not recruiting yetPancreatic cancerITGA2b and SELP Expression in Cancer Pancreas and Biliary Tract CancerObservational (Patient Registry)NCT05493878128Pancreatic CancerDiagnostic test: mRNA expressionAssiut, Egypt
TEP-3Tumor educated Platelets (TEP)RecruitingPancreatic cancerPre- and Post-operative TEG Indices in Patients with or without Adenocarcinoma Undergoing Surgical ResectionObservationalNCT05517811400Liver Cancer, Esophageal Cancer, Colorectal Cancer, Pancreas Cancer, Biliary CancerDiagnostic test: TEG indicesColorado, United States
Table
Table 6. Interventional study with ongoing clinical trials of LBs in GICs.
Table 6. Interventional study with ongoing clinical trials of LBs in GICs.
Liquid BiopsyStatusCancerStudy TitleStudy TypeClinical Trial IdentifierEstimated EnrollmentConditionsInterventionsLocations
CTC-1CTCRecruitingGastric cancerLiquid Biopsy in Monitiring the Neoadjuvant Chemotherapy and Operation in Gastric CancerInterventional
(Clinical Trial)		NCT0395756440Gastric Cancer, Gastro-Esophageal Junction CancerDetection of imaging data and level of CTCsQinghai, China
CTC-2CTCRecruitingGastric cancerPhase III Randomised Trial to Evaluate Folfox with or without Docetaxel (tfox) as 1st Line Chemotherapy for Locally Advanced or Metastatic Oesophago-Gastric carcinomaInterventional
(Clinical Trial)		NCT03006432506Esophago-Gastric CarcinomaDrug testing and CTC level98 locations in France
CTC-3CTCRecruitingGastric cancerRegoNivo vs. Standard of Care Chemotherapy in AGOCInterventional
(Clinical Trial)		NCT04879368450Gastro-Esophageal cancerDrug: regorafenib, biological: nivolumab, drug: docetaxel, drug: paclitaxel, drug: irinotecan, drug: trifluridine/tipracil75 locations in United States
CTC-4CTCRecruitingGastric cancerAvelumab + Paclitaxel/Ramucirumab (RAP) as Second Line Treatment in Gastro-esophageal Adenocarcinoma (AIO-STO-0218)Interventional (Clinical Trial)NCT0396611859Gastroesophageal Junction Adenocarcinoma, Adenocarcinoma of the StomachDrug: avelumab, drug: ramucirumab, drug: paclitaxelBerlin, Germany
CTC-5CTCRecruitingGastric cancerAscending Doses of Ceralasertib in Combination with Chemotherapy and/or Novel Anti Cancer AgentsInterventional (Clinical Trial)NCT02264678330Gastric CancerDrug: administration of ceralasertib in combination with carboplatin, drug: administration of ceralasertib, drug: administration of ceralasertib in combination with olaparib, drug: administation of ceralasertib in combination with durvalumab27 locations in United States
CTC-6CTCRecruitingPancreaticcancerLiquid Biopsy and Pancreas Cancer: Detection of AXL(+) CTCs (CTC-AXL-PANC)Interventional (Clinical Trial)NCT0534653663Pancreatic Ductal Adenocarcinoma Metastatic Pancreatic Cancer Circulating Tumor CellOther: detection of circulating tumor cells expressing Axl: CTC-AXL(+)Montpellier, France
CTC-7CTCRecruitingPancreatic cancerEUS-guided PORtal Vein Sampling for Circulating Tumor Cells in Pancreatic Cancer PatientsInterventional (Clinical Trial)NCT0524716470Pancreatic Cancer, Pancreatic AdenocarcinomaProcedure: EUS-guided portal vein samplingMilan, Italy
CTC-8CTCRecruitingPancreatic cancerEcho-endoscopy Biopsy Impact on the Circulating Tumor Cell LevelInterventional (Clinical Trial)NCT0467724442Cancer of PancreasProcedure: blood sample in portal veinMarseille, France
CTC-9CTCRecruitingLiver cancerA Trial of Adjuvant Therapy after Hepatocarcinoma Resection Based on Folate Receptor-positive Circulating Tumor CellsInterventional (Clinical Trial)NCT04521491184HCCDrug: FOLFOX4 (infusional fluorouracil [FU], leucovorin [LV], and oxaliplatin [OXA]).Shanghai, China
CTC-10CTCRecruitingColorectal cancerInfluence of Opioid Analgesia on Circulating Tumor Cells in Open Colorectal Cancer SurgeryInterventional (Clinical Trial)NCT03700411120Colorectal Cancer, Circulating Tumor CellDrug: morphine, piritramid, epidural3 locations in Czech Republic
CTC-11CTCRecruitingColorectal cancerTumoral Circulating Cells and Colorectal Cancer ProgressionInterventional (Clinical Trial)NCT03256084120Colorectal CancerProcedure: blood and tumor samplesMarseille, France
ctDNA-1ctDNARecruitingGastric cancerLiquid Biopsy in Monitoring the Neoadjuvant Chemotherapy and Operation in Gastric CancerInterventional (Clinical Trial)NCT0395756440Gastric Cancer, Gastro-Esophageal Junction CancerDrug: neoadjuvant chemotherapy with PSOX regimen. Other: detect the imaging data and levels of CTC, ctDNA, cfDNA, CEA, CA19-9, CA72-4 in plasma. Other: detect the tumor-related DNA in pathological tissues after operation. Other: follow-up of DFS and OS in patients with gastric cancer after operation.Qinghai, China
ctDNA-2ctDNARecruitingGastric cancerMR-guided Pre-operative RT in Gastric CancerInterventional (Clinical Trial)NCT0416266536Gastric AdenocarcinomaRadiation: MR-guided radiation therapy, procedure: blood for ctDNAMissouri, United States, Seoul, South Korea
ctDNA-3ctDNARecruitingGastric cancerPeritoneal Carcinomatosis Leveraging ctDNA Guided Treatment in GI Cancer Study (PERICLES Study)Interventional (Clinical Trial)NCT0492901530Gastric Cancer, ctDNAColorectal carcinoma by AJCC V8 stage, digestive system neoplasm, esophageal carcinoma by AJCC V8 stage, gastric carcinoma by AJCC V8 stage, liver and intrahepatic bile duct carcinoma, peritoneal carcinomatosisNew Jersey, United States
ctDNA-4ctDNARecruitingPancreatic cancerPilot Comparing ctDNA IDV vs. SPV Sample in Pts Undergoing Biopsies for Hepatobiliary and Pancreatic CancersInterventional (Clinical Trial)NCT0549753115Hepatobiliary Cancer, Pancreatic Cancer, Hepatocellular Carcinoma, Cholangiocarcinoma, Ampullary Cancer, Pancreatic CarcinomaDiagnostic test: ctDNA blood collectionCalifornia, United States
ctDNA-5ctDNARecruitingPancreatic cancerPLATON—Platform for Analyzing Targetable Tumor Mutations (Pilot-study)Interventional (Clinical Trial)NCT04484636200Hepatocellular Cancer, Cholangiocarcinoma, Gallbladder Cancer, Pancreatic Cancer, Esophageal Cancer, Stomach CancerDiagnostic test: FoundationOne®CDx and FoundationOne®Liquid30 locations in Germany
ctDNA-6ctDNARecruitingLiver cancerctDNA-Directed Post-Hepatectomy Chemotherapy for Patients With Resectable Colorectal Liver MetastasesInterventional (Clinical Trial)NCT05062317120Liver MetastasesDrug: leucovorin drug: 5-FLUOROURACIL, drug: oxaliplatin, drug: irinotecan, drug: capecitabine, drug: bevacizumabTexas, United States
ctDNA-7ctDNARecruitingHepatocellular, GastricRisk factors of Immune—ChEckpoint inhibitors MEdiated Liver, gastrointestinal, endocrine and skin Toxicity (ICEMELT)Interventionl (Clinical Trial)NCT04631731200Gastric Cancer, Hepatocellular CarcinomaDiagnostic test: blood screening, diagnostic test: tissue screeningNew South Wales, Australia
ctDNA-8ctDNARecruitingColorectal cancerA Phase II Randomized Therapeutic Optimization Trial for Subjects with Refractory Metastatic Colorectal Cancer Using ctDNA: Rapid 1 TrialInterventional (Clinical Trial)NCT0478660078Metastatic Colorectal cancerDevice: Signatera ctDNA assay, drug: pre-specified sequence of FDA-approved drugs and drug combinationsFlorida, United States
ctDNA-9ctDNARecruitingColorectal cancerInitial Attack on Latent Metastasis Using TAS-102 for ct DNA Identified Colorectal Cancer Patients after Curative Resection (ALTAIR)Interventional (Clinical Trial)NCT04457297240Colorectal Neoplasms, Trifluridine, and Tipiracil, Circulating Tumor DNA Drug: trifluridine and tipiracil, drug: placebo39 locations in Japan
ctDNA-10ctDNARecruitingColorectal cancerIMPROVE Intervention Trial Implementing Non-invasive Circulating Tumor DNA Analysis to Optimize the Operative and Postoperative Treatment for Patients with Colorectal CancerInterventional (Clinical Trial) NCT0374868064Colorectal Cancer, Circulating Tumor DANN, Adjuvant Chemotherapy, Progression Free SurvivalDrug: Capox (or FOLFOX) including fluoropyrimidine and oxaliplatin combination chemotherapy4 locations in Denmark
ctDNA-11ctDNARecruitingColorectal cancerCirculating Tumor DNA Analysis to Optimize the Operative and Postoperative Treatment for Patients with Colorectal Cancer—Intervention Trial 2 (IMPROVE-IT2)Interventional (Clinical Trial) NCT04084249254Colorectal Cancer, Colo-rectal Cancer, ctDNA, Gastro-Intestinal Disorder, Colorectal Neoplasms, Gastrointestinal Cancer, Gastrointestinal Neoplasms, Digestive System Disease, Digestive System Neoplasm, Colonic Diseases, Colonic Neoplasms, Colonic Cancer,Diagnostic test: ctDNA-analysis, other: intensified follow-up scheduleRanders, Denmark
ctDNA-12ctDNARecruitingColorectal cancerCirculating Cell-Free Tumor DNA Testing in Guiding Treatment for Patients with Advanced or Metastatic Colorectal CancerInterventional (Clinical Trial)NCT03844620100Refractory Colorectal Carcinoma, Stage III Colorectal Cancer AJCC v8, Stage IIIA Colorectal Cancer AJCC v8, Stage IIIB Colorectal Cancer AJCC v8, Stage IIIC Colorectal Cancer AJCC v8, Stage IV Colorectal Cancer AJCC v8, Stage IVA Colorectal Cancer AJCC v8, Stage IVB Colorectal Cancer AJCC v8 Stage, IVC Colorectal Cancer AJCC v8Other: best practice, other: laboratory procedure, other: quality-of-life assessment, other: questionnaire administration, drug: regorafenib, drug: trifluridine and tipiracil hydrochlorideTexas, United States
ctDNA-13ctDNARecruitingColorectal cancerA Phase II Clinical Trial Comparing the Efficacy of RO7198457 Versus Watchful Waiting in Patients With ctDNA-positive, Resected Stage II (High Risk) and Stage III Colorectal CancerInterventional (Clinical Trial)NCT04486378201Colorectal Cancer Stage II and IIIDrug: RO7198457 intravenous (i.v.), other: observational group (no intervention)53 locations in United States
ctDNA-14ctDNARecruitingColorectal cancerTAS-102 in ctDNA-defined Minimal Residual Disease in Colorectal Cancer after Completion of Adjuvant ChemotherapyInterventional (Clinical Trial)NCT0534301315Colorectal CancerDrug: TAS-102Texas, United States
ctDNA-15ctDNARecruitingColon cancerColon Adjuvant Chemotherapy Based on Evaluation of Residual Disease (CIRCULATE-US)Interventional (Clinical Trial)NCT051741691912Stage III Colon CancerDevice: Signatera test, Drug: mFOLFOX6 3–6 month, drug: CAPOX 3 month, drug: mFOLFIRINOX, drug: mFOLFOX6 6 month, drug: CAPOX 6 monthPennsylvania, United States
ctDNA-16ctDNARecruitingColon cancerDYNAMIC-III: Circulating Tumour DNA Analysis Informing Adjuvant Chemotherapy in Stage III Colon Cancer: A Multi-centre Phase II/III Randomised Controlled Study (Protocol No: ctDNA-08)Interventional (Clinical Trial)ACTRN12617001566325356/1000Stage III Colon CancerPre-operative combined chemotherapy and radiotherapy, post-operative combined chemotherapy and radiotherapy, 3 months of fluoropyrimidine adjuvant chemotherapy, ECOG performance status 0–2NSW, NT, QLD, SA, TAS, WA, VIC, Australia
exo-1ExosomesRecruitingGastric cancerA Study of exoASO-STAT6 (CDK-004) in Patients With Advanced Hepatocellular Carcinoma (HCC) and Patients With Liver Metastases From Primary Gastric Cancer and Colorectal Cancer (CRC)Interventional (Clinical Trial)NCT0537560430Advanced Hepatocellular Carcinoma (HCC), Gastric Cancer Metastatic to Liver, Colorectal Cancer Metastatic to LiverDrug: CDK-004California, New York, Tennessee, United States
exo-2ExosomesRecruitingPancreatic canceriExosomes in Treating Participants with Metastatic Pancreas Cancer with KrasG12D MutationInterventional (Clinical Trial)NCT0360863128KRAS NP_004976.2:p.G12DMetastatic Pancreatic AdenocarcinomaPancreatic Ductal AdenocarcinomaStage IV Pancreatic Cancer AJCC v8 Drug: mesenchymal stromal cells-derived exosomes with KRAS G12D siRNATexas, United States
exo-3ExosomesRecruitingPancreatic cancerUltra-High Resolution Optical Coherence Tomography in Detecting Micrometer Sized Early Stage Pancreatic Cancer in Participants with Pancreatic CancerInterventional (Clinical Trial)NCT0371189075Pancreatic Carcinoma, Pancreatic Intraductal Papillary Mucinous Neoplasm, Pancreatobiliary-Type Procedure: Optical Coherence TomographyProcedure: Therapeutic Conventional SurgeryDiagnostic Test: Laboratory EvaluationOhio, United States
exo-4ExosomesRecruitingLiver cancerA Study of exoASO-STAT6 (CDK-004) in Patients with Advanced Hepatocellular Carcinoma (HCC) and Patients with Liver Metastases from Primary Gastric Cancer and Colorectal Cancer (CRC)Interventional (Clinical Trial)NCT0537560430Advanced Hepatocellular Carcinoma (HCC), Gastric Cancer Metastatic to Liver, Colorectal Cancer Metastatic to LiverDrug: CDK-0043 locations in United States
TEP-1Tumor educated Platelets (TEP)RecruitingPancreatic cancerSerial Measurements of Molecular and Architectural Responses to Therapy (SMMART) PRIME TrialInterventional (Clinical Trial)NCT0387852440Stage II Pancreatic Cancer AJCC v8, Stage III Pancreatic Cancer AJCC v8, Stage IV Pancreatic Cancer AJCC v8, Stage IV AJCC v8, Unresectable Pancreatic Adenocarcinoma Drug testingOregon, United States
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MDPI and ACS Style

David, P.; Mittelstädt, A.; Kouhestani, D.; Anthuber, A.; Kahlert, C.; Sohn, K.; Weber, G.F. Current Applications of Liquid Biopsy in Gastrointestinal Cancer Disease—From Early Cancer Detection to Individualized Cancer Treatment. Cancers 2023, 15, 1924. https://doi.org/10.3390/cancers15071924

AMA Style

David P, Mittelstädt A, Kouhestani D, Anthuber A, Kahlert C, Sohn K, Weber GF. Current Applications of Liquid Biopsy in Gastrointestinal Cancer Disease—From Early Cancer Detection to Individualized Cancer Treatment. Cancers. 2023; 15(7):1924. https://doi.org/10.3390/cancers15071924

Chicago/Turabian Style

David, Paul, Anke Mittelstädt, Dina Kouhestani, Anna Anthuber, Christoph Kahlert, Kai Sohn, and Georg F. Weber. 2023. "Current Applications of Liquid Biopsy in Gastrointestinal Cancer Disease—From Early Cancer Detection to Individualized Cancer Treatment" Cancers 15, no. 7: 1924. https://doi.org/10.3390/cancers15071924

APA Style

David, P., Mittelstädt, A., Kouhestani, D., Anthuber, A., Kahlert, C., Sohn, K., & Weber, G. F. (2023). Current Applications of Liquid Biopsy in Gastrointestinal Cancer Disease—From Early Cancer Detection to Individualized Cancer Treatment. Cancers, 15(7), 1924. https://doi.org/10.3390/cancers15071924

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