Next Article in Journal
Semaphorin-3F/Neuropilin-2 Transcriptional Expression as a Predictive Biomarker of Occult Lymph Node Metastases in HNSCC
Next Article in Special Issue
Early Steps of Resistance to Targeted Therapies in Non-Small-Cell Lung Cancer
Previous Article in Journal
EGFR-Mutant Non-Small-Cell Lung Cancer at Surgical Stages: What Is the Place for Tyrosine Kinase Inhibitors?
Previous Article in Special Issue
The Purinergic Landscape of Non-Small Cell Lung Cancer
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Setting Up an Ultra-Fast Next-Generation Sequencing Approach as Reflex Testing at Diagnosis of Non-Squamous Non-Small Cell Lung Cancer; Experience of a Single Center (LPCE, Nice, France)

1
Laboratory of Clinical and Experimental Pathology, Pasteur Hospital, Université Côte d’Azur, 06000 Nice, France
2
Biobank-related Hospital (BB-0033-00025), Pasteur Hospital, 06000 Nice, France
3
FHU OncoAge, Pasteur Hospital, Université Côte d’Azur, 06000 Nice, France
4
Inserm U1081, CNRS UMR 7413, IRCAN, 06100 Nice, France
5
Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX 77030, USA
6
Department of Pulmonary Medicine and Thoracic Oncology, Pasteur Hospital, 06000 Nice, France
*
Author to whom correspondence should be addressed.
Cancers 2022, 14(9), 2258; https://doi.org/10.3390/cancers14092258
Submission received: 18 April 2022 / Accepted: 28 April 2022 / Published: 30 April 2022

Abstract

:

Simple Summary

Due to the increase of molecular biomarkers to be characterized to tailor therapeutic strategies for non-squamous non-small cell lung carcinoma (NS-NSCLC), it is now more and more challenging to evaluate these biomarkers using sequential analyses. We report here our experience concerning the development of an optimal workflow for genomic alteration assessment as reflex testing in routine clinical practice at diagnosis for NS-NSCLC patients by using an ultra-fast-next generation sequencing (NGS) approach. The analytical validation of the NGS workflow demonstrated 100% concordance with the gold standard methods. Only few cases failed for DNA/RNA NGS results. The mean turnaround time (TAT) was 72 h (ranging from 48 to 96 h). An ultra-fast NGS technique can maximize the management of the sample workflow in thoracic oncology to obtain the molecular biology results in an appropriate TAT, even when only a small amount of nucleic acids is available.

Abstract

The number of genomic alterations required for targeted therapy of non-squamous non-small cell lung cancer (NS-NSCLC) patients has increased and become more complex these last few years. These molecular abnormalities lead to treatment that provides improvement in overall survival for certain patients. However, these treated tumors inexorably develop mechanisms of resistance, some of which can be targeted with new therapies. The characterization of the genomic alterations needs to be performed in a short turnaround time (TAT), as indicated by the international guidelines. The origin of the tissue biopsies used for the analyses is diverse, but their size is progressively decreasing due to the development of less invasive methods. In this respect, the pathologists are facing a number of different challenges requiring them to set up efficient molecular technologies while maintaining a strategy that allows rapid diagnosis. We report here our experience concerning the development of an optimal workflow for genomic alteration assessment as reflex testing in routine clinical practice at diagnosis for NS-NSCLC patients by using an ultra-fast-next generation sequencing approach (Ion Torrent Genexus Sequencer, Thermo Fisher Scientific). We show that the molecular targets currently available to personalized medicine in thoracic oncology can be identified using this system in an appropriate TAT, notably when only a small amount of nucleic acids is available. We discuss the new challenges and the perspectives of using such an ultra-fast NGS in daily practice.

1. Introduction

Thanks to the availability of different targeted therapies for treatment of late-stage non-squamous non-small cell lung carcinoma (NS-NSCLC), depending on some of the genomic alterations, the overall survival (OS) of these patients has improved in recent years [1,2]. In this respect, the number of mandatory genes for analysis and of molecular targets to look for when treating NS-NSCLC has increased progressively over recent years and requires tissue biopsies, cytological specimens, and in certain situations, liquid biopsies [3,4,5,6]. Therefore, it is mandatory today, according to the recent international guidelines, to systematically obtain, at diagnosis, the status of EGFR, ALK, ROS1, BRAF, NTRK, RET, and MET, for late-stage NS-NSCLC treatment [5,7].
Moreover, since new drugs have recently given promising results in clinical trials, many genomic alterations will soon be searched for in a number of other genes, notably KRAS and HER2, but also NRG1 and NUT [3,8]. Knowing the status of different associated genes, such as STK11, KEAP1, and TP53, may also be of strong interest in the future for therapeutic strategies for these patients, to better predict the response or resistance to some targeted therapies and/or immune checkpoint inhibitors (ICIs) [9,10,11,12].
ICIs alone or in association with chemotherapy is now the standard of care for late-stage NS-NSCLC provided that these tumors do not have molecular alterations accessible to a targeted therapy [13,14]. Moreover, the upcoming development of neoadjuvant and adjuvant immunotherapy will lead to systematically look for genomic alterations in EGFR and ALK (at least) in early-stage NS-NSCLC, since ICIs should be administered only in EGFR and ALK wild-type tumors [15]. Moreover, it is now mandatory to look for EGFR mutations in early-stage NS-NSCLC, since a third-generation EGFR tyrosine kinase inhibitor (osimertinib) can be given as adjuvant therapy in some EGFR mutated tumors [16,17].
In this regard, the strategy for assessing the different biomarkers that can predict the response to the different targeted therapies and/or immunotherapies for NS-NSCLC patients is moving fast, making it increasingly difficult to identify these biomarkers in a sequential manner [7,18,19]. The association of next-generation sequencing (NGS) (for genomic alteration evaluation) and immunohistochemistry (IHC) (at least for PD-L1 status assessment) approaches is now the best way to obtain information concerning all the mandatory therapeutic targets [4,5,20]. However, these analyses need to take into consideration the sample size and the amount of extracted nucleic acids, and should be done in accordance with the TAT to obtain the results [4,5,21,22].
Here, we describe the experience of a single center (Laboratory of Clinical and Experimental Pathology Laboratory (LPCE), Nice University Hospital, France) in setting up an ultra-fast DNA and RNA-based NGS assay for molecular biology reflex testing at diagnosis of NS-NSCLC.
The advantages and the limitations of this workflow from the tissue biopsy to the report are discussed. Finally, we provide details into the current challenges of biomarker assessment of NS-NSCLC and a few perspectives related to this domain.

2. Materials and Methods

2.1. Patients

This cohort included 345 consecutive patients diagnosed with NS-NSCLC between 20 September and 31 January 2022. The patients had a fast DNA- and RNA-based NGS as reflex testing at the LPCE (Nice University Hospital, France), which is accredited according to the ISO 15189 norm for somatic genomic testing by NGS in routine clinical practice (www.cofrac.fr, accessed on 22 February 2022).
All tumor specimens were used with the informed signed consent from the patients. The study was approved by the local ethics committee (Human Research Ethics Committee, Nice University Hospital Center/Hospital-related Biobank BB-0033-00025; http://www.biobank-cotedazur.fr/, accessed on 18 January 2022) and was performed in accordance with the guidelines of the Declaration of Helsinki.

2.2. Ultra-Fast Next-Generation Sequencing

Briefly, nucleic acids were either extracted using the Maxwell RSC Instrument (Promega, catalog number AS4500) with the Maxwell RSC FFPE Plus DNA kit (catalog number AS1720) and Maxwell RSC RNA FFPE kit (catalog number AS1440), or using the Ion Torrent™Genexus™Purification System (Thermo Fisher Scientific, Waltham, MA, USA; catalog number A48148) with the Genexus™ FFPE DNA/RNA Purification Combo Kit (Thermo Fisher Scientific, catalog number A45539) (Figure 1).
Following nucleic acids’ extraction with the Maxwell RSC Instrument automaton, a Qubit Fluorometric quantification assay (Thermo Fisher Scientific, catalog number Q33327) was performed with the Qubit RNA HS Assay Kit (catalog number Q32852) and Qubit dsDNA HS Assay Kit (catalog number Q32851) to measure the concentration of extracted nucleic acid. The Ion Torrent™Genexus™ Purification System (Thermo Fisher Scientific) was equipped with a fluorometer and automatically assayed the extracted nucleic acid following the extraction step. Detection of genomic alterations was then performed using Ion semiconductor sequencing (Ion Torrent™ Technology, Thermo Fisher Scientific) on the Ion Torrent™Genexus™Integrated Sequencer. The panel used was the Oncomine™ Precision Assay GX (OPA, Thermo Fisher Scientific, catalog number A46291). This panel included 50 key genes of which 45 were targeted for DNA mutation detection, 18 for fusion detection and 14 for Copy Number Variant (CNV) detection. The panel also incorporated a 5′/3′ expression imbalance caller for the detection of novel fusions. With this panel, the Genexus sequencer was able to sequence up to 16 samples on a single run.
The TAT was considered as the time between obtaining the formalin fixed paraffin embedded (FFPE) sample and the electronic validation of the NGS report with the hospital software. This time included the deparaffinization step, the nucleic acids’ extraction steps, the sequencing step, the genomic alteration(s) assessment, and the post analytical time (Figure 1).
The performance of the Genexus workflow was assessed by comparison to the following gold standard methods used at the LPCE before starting this new workflow: (i) Idylla EGFR Mutation Test (Biocartis, Mechelen, Belgium); (ii) Idylla KRAS Mutation Test (Biocartis); (iii) ALK IHC (clone D5F3, Roche-Ventana, Tucson, AZ, USA) and/or ALK fluorescence in situ hybridization (FISH) (Vysis ALK Break Apart FISH Probe Kit, Abbott Molecular, Des Plaines, IL, USA); (iv) ROS1 IHC (clone D4D6, Cell Signaling Technology, Danvers, MA, USA) and/or FISH (POSEIDON ROS1 Dual Color Break Apart Probe, Leica Biosystems, Amsterdam, The Netherlands); (v) BRAFV600E IHC (clone VE1, Roche-Ventana), and (vi) the S5 system (Thermo Fisher Scientific) using the DNA Ion AmpliSeq™Cancer Hotspot Panel and the RNA Oncomine Focus Assay.

3. Results

In this study, 345 NSCLC specimens were examined at the LPCE between the period study. Among these tumors, 259/345 (75%) corresponded to NS-NSCLC and underwent clinical ultra-fast NGS testing. The main epidemiological, clinical, and pathological data are shown in Table 1.
Two expert thoracic pathologists (V.H. and M.I.) blindly assessed the percentage of tumor cells and any discrepancy was discussed using a multihead microscope. Samples with more than 10% of tumor cells were selected for nucleic acid extraction and further NGS analyses depending on the amount of nucleic acid extracted with a cutoff of 13 ng of DNA or RNA.
The majority of tests were performed on in-house samples, 248 (96%), with 11 (4%) performed on samples from outside centers.
Overall, 506 NGS analyses were performed (Table 2). Ten cases (4%) failed for DNA NGS results due to a low quality of nucleic acids (6 cases) and a low amount of nucleic acid (4 cases <13 ng of DNA, whereas 5 cases (2%) failed for RNA NGS results due to the poor quality of RNA and low amount of RNA (<13 ng of RNA). The mean % of tumor cells in the failed cases was low (15%, range 10% to 20%), whereas the range % of tumor cells in successful cases was between 30% to 90%. Of the 15 failed specimens, 11 were small tissue biopsies (mean area, 2 mm2), while 4 were cytological specimens (e.g., endobronchial ultrasound (EBUS)).
Of the 259 patients with NS-NSCLC with valid or available NGS analysis (n = 242), driver molecular alterations were detected as follows (Figure 2): EGFR, 44 (18.2%); KRAS, 61 (25.4%), BRAF, 15 (6.3%); ALK 10 (4.3%); ERBB2, 4 (1.7%); MET, 4 (1.7%); ROS1 11 (2.3%); RET, 9 (1.9%), and NTRK, 2 (0.8%), with additional alterations detected with an incidence below 1% (e.g., IDH1, CDKN2A, FGFR3, KIT, MTOR, FGFR4. NTRK3, NRAS, PIK3CA, IDH2, ERBB3, ERBB4, AR, CHECK2, SMO, PTEN).
The mean TAT was 72 h (range, 48 to 96 h) for all specimens, including those referred in from outside clinical centers.
The analytical validation of the Genexus OPA DNA RNA workflow demonstrated 100% concordance with the gold standard methods, as follows: (i) the DNA S5 Hotspot panel, 14 cases (EGFR, 4; KRAS, 2; BRAF, 1; PIK3CA, 1; TP53, 10; KIT, 3); (ii) the RNA Oncomine Focus Assay panel, 22 cases (ALK, 4; ROS1, 1; FGFR3, 1; RET, 1; MET, 3); (iii) the Idylla EGFR Mutation Test (n = 109, wild-type, 61, and mutated, 48); (iv) the Idylla KRAS Mutation Test (n = 30, wild-type, 23, and mutated, 7); (v) BRAFV600E IHC (n = 107, wild-type, 99; and mutated, 8); (vi) IHC and/or FISH ALK (n = 65; wild-type, 60, and rearranged, 5), and (vii) IHC and/or FISH ROS1 (n = 65; wild-type, 60; rearranged, 5).

4. Discussion

4.1. Advantages and Limitations of a Fast-Next Generation Sequencing

4.1.1. Advantages

The usefulness of ordered testing for molecular biomarkers for lung adenocarcinomas has been highlighted by many studies [23,24]. An NGS approach can optimize the management of the sample workflow in thoracic oncology to obtain the molecular biology results. Thus, NGS testing of advanced NS-NSCLC directly affects patient OS [23,25]. In this context, it has been demonstrated that NGS reflex testing for advanced NS-NSCLC is cost-effective. Reliable in-house molecular testing systems, including the alterations for all Food and Drug Administration (FDA) and European Medicine Agency (EMA) approved and international guideline-recommended therapies, as well as other emerging markers for these tumors are available [5,26,27]. The genomic alterations that, to date, can be detected on the different genes present in the OPA, DNA, and RNA panels cover the great majority of targets that can be associated with the current drugs for NS-NSCLC treatment [5]. An ultra-fast NGS is of strong interest since many of the NGS approaches described up to now can have a TAT to obtain the results that are sometimes not compatible with urgent therapeutic care leading to the use in parallel of rapid genotyping based on a RT-PCR approach [28,29]. To save time, notably for certain NSCLC patients such as non-smokers, some strategies use, in front-line, a frozen specimen to avoid the time due to the usual pre-analytical phase preformed in a pathology laboratory (formalin fixation and paraffin embedding steps). When using an ultra-fast NGS, the thoracic oncologist can obtain in around three working days, the “molecular portrait” of the tumor. Moreover, these molecular results can be obtained almost simultaneously from the IHC results, notably those concerning the percentage of PD-L1 positive tumor cells [20]. For this, the physician has the assessment of all the biomarkers in hands for the best therapeutic choice of first-line treatment, to give a targeted therapy or an immuno/immuno-chemotherapy [30]. More exceptionally, the patient can be included into a clinical trial depending on the genomic and/or the PD-L1 IHC results [31,32,33,34]. Depending on the use of the DNA OPA panel alone or in combination with the RNA OPA panel, and on the systematic use of a control sample, the number of tumors that can be analyzed on each run can vary from 7 to 16. Knowing that, at least in theory, it is possible to make three runs per week, and thus, 48 patients with tumors can benefit from this ultra-fast NGS analysis weekly.
The Genexus sequencer and, even more, the combination of this device and the nucleic acid Genexus purification system, reduces the time to obtain the results and the amount of work of the technicians. The possibility of quantifying the extracted DNA and RNA before library preparation, as well as the capacity to use low amounts of extracted nucleic acid (from a minimum of 13 ng of DNA or 13 ng of RNA, according to the specifications) allows rapid evaluation of the feasibility of the sequencing analyses. The possibility of using a low amount of nucleic acid is pivotal, due to the number of biopsies of very small size in thoracic oncology and also since some of the profiles of genomic alteration sometimes need to be performed with cytological samples [35,36,37].
Due to the progressive increase in the number of molecular biomarkers to be characterized to tailor therapeutic strategies for NS-NSCLC, it is now more and more challenging to evaluate these biomarkers using sequential analyses, which can involve, depending on the gene of interest, immunohistochemistry, FISH, and/or RT-PCR [38,39,40,41]. Moreover, these sequential analyses have the disadvantage of rapid exhaustion of the sample and, depending on the number of genes to be evaluated can be costly [42]. Conversely, analyses using NGS are cost-effective and overall allow the biological material to be saved [38,42,43,44,45,46,47,48,49,50]. However, for this approach, it is necessary to run enough samples at the same time to save on consumables, which is sometimes not possible, depending on the patient recruitment and the molecular pathology laboratory [51].

4.1.2. Limitations

The development of an ultra-fast NGS tool as reflex testing at diagnosis of NSCLC, as described above, may hold certain limitations in daily practice. First, the number of genes available on the OPA panel (50 genes) is much lower than those present on large panels containing several hundreds of genes [52]. However, the OPA panel includes all the genes that are currently mandatory to detect a genomic alteration that can be associated with a current targeted therapy in thoracic oncology. It is noteworthy that some genes of interest in thoracic oncology (such as KEAP1, Rb1, and SMARCA4) were not present on the OPA panels used in the present work. Thus, some additional genes might be useful to evaluate prognosis or to predict response to some targeted therapies and immunotherapies [12,53].
The possibility of missing some partners of gene fusions or some exceptional mutations is theoretically possible when using ultra-fast NGS due to the amplicon sequencing technology [54].
The systematic use of an NGS approach for genomic alteration assessment of NSCLC at diagnosis as reflex testing could be considered as not very effective in comparison to performing an NGS approach only in case of physician bespoke testing. Thus, some testing can be done on an early-stage NSCLC for which, aside from osimertinib adjuvant treatment of EGFR mutated NS-NSCLC patients, no targeted therapies are currently available in routine daily practice. However, this practice raises questions related to the economic model and to the reimbursement of the NGS in general, which can be problematic depending on the country, notably in Europe [55]. Moreover, the reimbursement of NGS for early-stage NSCLC as well as the possibility of generating an unnecessary additional workload for the staff of the laboratory should be discussed. However, to systematically have, at the same time, the molecular profile of the early-stage NS-NSCLC, can be of strong interest when tumor recurrence or progression occurs. Thus, this can avoid doing an invasive re-biopsy at tumor progression to do some molecular biology testing. Moreover, the decision to provide targeted therapy can potentially be rapid at tumor progression without doing molecular biology testing on an FFPE block, which usually would be available in the pathology laboratory archives but for which the tissue may be exhausted. As mentioned above, the cost-effectiveness of NGS also depends on the number of samples available for each run, and should not just be used for EGFR, ALK, and ROS1 assessment, but to look for all the mandatory biomarkers of NS-NSCLC stipulated in the international guidelines [56,57]. The simultaneous use of both DNA and RNA NGS, although ideal, is debatable. An alternative strategy would be to do a first-step DNA NGS, and in the case of no detection of genetic alterations to do an RNA NGS in a second step to look, for example, for a gene fusion, knowing that most of the genomic alterations for a targeted therapy are mutually exclusive [38]. However, this reflex strategy would consequently lead to a longer TAT to obtaining a report.
The quantity as well as the quality of extracted nucleic acids can be one of the limits for the robustness of NGS analyses. This is particularly the case when using hybrid capture sequencing technology and large panels [8]. In this respect, the Genexus sequencing technology and the OPA panels offer the advantage of requiring only, at least, 13 ng of DNA and RNA. This is highly valuable in thoracic oncology since, currently, the size of samples are becoming smaller and smaller [58,59,60]. In our study, the overall failure rate was low (15/506, 2%), despite a high number of small samples (biopsies, 77% and cytology 8%). However, the failed specimens were notably small-sized specimens with low percentage of tumor cells (<10%). When dealing with a failed analysis, the oncologist should be consulted to examine the possibility of a tissue re-biopsy, according to the patient status and/or to the tumor accessibility, or of a liquid biopsy for making NGS from circulating free DNA [61].

4.2. Current Challenges Associated with the Rapid Revolution of Predictive Biomarkers in NS-NSCLC

The current mandatory biomarkers to look for in late-stage NS-NSCLC include different genomic alterations present on EGFR, ALK, ROS1, NTRK, BRAF, MET, and RET, as well as the PD-L1 expression of tumor cells [4,5]. The presence or absence of one of these biomarkers leads to the possibility of proposing targeted therapy or immunotherapy alone or combined with chemotherapy [4,7,18,30,51]. Therefore, different therapeutic molecules have obtained authorization from the FDA in the USA and the EMA in Europe for first-line treatment in daily practice [7,18]. Other molecular alterations can be examined on HER2, KRAS, and the EGFR exon 20 mutation that can lead to patient inclusion, when not showing targetable abnormalities on the previous cited genes, in clinical trials [62,63,64]. More recently, combinations of different therapies including targeted treatment and immunotherapy are ongoing in clinical trials, and might be proposed in the near future as first-line treatment or on tumor progression [65,66]. It is noteworthy that all these therapeutic strategies are mainly indicated to date for NS-NSCLC histological subtypes. So, most of the different treatments for squamous cell (SC)-NSCLC are based on immunotherapy associated or not with chemotherapy [67,68]. More exceptionally, a genomic alteration in one of the previous cited lists of genes can be looked for in young and/or nonsmoking SC-NSCLC patients or on the physician’s request, and can be associated with a targeted therapy [69,70,71]. The biomarkers associated with these different personalized treatments are mainly looked for on tissue biopsies, or sometimes on cytological samples [35]. Exceptionally, a liquid biopsy can be performed at baseline to look for some genomic alterations in case a tissue biopsy cannot be done or if the tissue sample cannot provide good quantity and/or quality nucleic acid for biomarker testing [61,72,73]. Despite the progress in surgical technologies and approaches to neoadjuvant or adjuvant chemotherapies or radio-chemotherapies, early-stage NSCLC patients still have a poor prognosis as they are associated with a death rate of around 50% of patients following complete tumor resection [74,75]. In this regard, the recent emergence of different targeted therapies and of immunotherapies for these patients is opening promise for better care and improvement in OS [76,77,78,79]. These new therapeutic approaches may be administered in neoadjuvant or adjuvant settings and need to be adapted according to the biomarkers identified by molecular testing and immunohistochemistry [80]. Adjuvant therapy with osimertinib for EGFR mutated NS-NSCLC (exon 19 deletion or p.L858R mutation) has received FDA and EMA approval for resected stage IB-IIIA, and thus can be used in daily practice [17]. Other therapeutic strategies, such as neoadjuvant immunotherapy in wild-type EGFR and ALK NS-NSCLC can, to date, be only discussed in clinical trials [81,82]. Moreover, many other clinical trials are currently ongoing for different targeted therapies for ALK rearrangements or adjuvant immunotherapies in early-stage NS-NSCLC [81,83]. All these treatments require identification of an associated biomarker that is characterized in tissue biopsies, cytological samples or in surgical resected specimens [35,72]. However, two challenges must be mastered: first, the TAT to obtain the results that are compatible with the therapeutic strategies, and secondly, the quality of the specimen to perform the different analyses [35,72]. Therefore, it is mandatory to adapt the best practices for effective partnerships and improve collaboration among thoracic surgeons, oncologists, pathologists, and other members of the multidisciplinary lung cancer care team who are managing patients with early-stage NSCLC. In this context, an ultra-fast NGS approach is certainly the best way to control all the different biomarkers that could be associated now and in the future with optimal treatment for early-stage NSCLC.
Finally, considering that the tumor stage at diagnosis is rarely known by the pathologist when examining the tumor tissue section with a microscope, one of the best strategies to optimize NS-NSCLC patient care, is to ask systematically, in addition to at least PD-L1 IHC, for reflex NGS [24,26].
NGS of liquid biopsies in advanced NS-NSCLC provides a great opportunity to detect targetable genomic alterations, which may not always be present in a tissue biopsy, due to tumor heterogeneity [30]. Moreover, according to the health care organization, liquid biopsies, in addition to being non-invasive and repeatable, can provide rapid molecular results [84]. So, some studies highlight the concept of “plasma first” to obtain results for advanced NS-NSCLC [84]. However, this is debatable since characterization of the histological subtype, and PD-L1 evaluation, as well as the detection of some genomic alterations, such as amplification and gene fusion, is not possible or is less sensitive with blood than with tissue samples [8,61]. However, to combine at diagnosis NGS with a liquid and a tissue biopsy could be, at least in theory, of strong value to detect all the current biomarkers of interest in late-stage NS-NSCLC, notably due to tumor heterogeneity [85].

4.3. What Should We Expect in the Future?

When thinking of the implementation of NGS as reflex testing at diagnosis of NS-NSCLC patients, we need to consider the biomarkers currently mandatory in practice, in addition to those that may be asked for when using targeted therapies in development (such as NRG1 and NUT), and for future new therapies [8]. It is certain that a medium- sized NGS panel containing 50 genes, including the main genes of interest in thoracic oncology, currently allows identification of the different genomic alterations that can be associated with one of the targeted therapies available today. However, it is probable that, since many new targets will certainly be associated with different drugs in the future, a large panel (containing several hundreds of genes) will be essential in the near future [51]. Currently, large panels can be used in some circumstances when patients are included in clinical trials since rare genomic alterations detected in some specific genes are not present in medium-sized gene panels [86]. So, the role of a tumor board in evaluating the best treatment according to complexity of genomic alteration assessment will become more and more indispensable [87,88].
The assessment of different protein biomarkers (not only for patient diagnosis, but also for the prediction of response to treatment) takes advantage of multiplex IHC approaches. By evaluating a variable number of proteins at the same time on one tissue section, this technology saves tissue specimens. In a routine clinical practice, it is probable that chromogenic multiplex IHC is an easy approach for surgical pathologists to set up in their daily work [89,90]. So, by combining multiplex IHC and NGS testing, the care of NSCLC patients will certainly be optimal at diagnosis.
Daily practice of liquid biopsies is, today, a useful approach at tumor progression to detect a resistance mechanism that can be treated with targeted therapy [73]. At diagnosis of advanced NS-NSCLC, as mentioned above, the use of NGS, both with liquid and tissue biopsies may be of strong interest to optimize the maximal detection of a drug targetable to genomic alteration [28,84]. For early-stage NS-NSCLC, liquid biopsies will certainly be implemented in the future in routine practice to detect early recurrence after surgery [91]. Therefore, quantifying the circulating free tumor DNA before and at different time points after surgery will become a biomarker of patient prognosis [92]. Moreover, the future optimization of nucleic acid extraction and characterization from plasma samples may allow selection of a liquid biopsy at baseline to identify different molecular abnormalities for better care, even if the amount of tumor DNA shedded into blood is usually low in early-stage NS-NSCLC [93,94].
To date, many considerations for personalized medicine have been made for NS-NSCLC treatment. Therefore, minimal targeted therapy for squamous cell (SC)-NSCLC is currently available since no molecule has yet been FDA and EMA approved for this histological subtype. However, promising research and some innovative molecules are in the pharmaceutical pipelines that open up room for new SC-NSCLC treatments in the near future [95]. In this regard, it will certainly be necessary to ask for NGS reflex testing at diagnosis of advanced SC-NSCLC when new drugs are used in clinical trials and then in daily practice.
Targeted NGS may provide in the future valuable information to predict recurrence and identify patients at a high risk of recurrence. This could facilitate selection of the treatment strategy with close monitoring and adjuvant-targeted therapy [96].

5. Conclusions

Ultra-fast NGS integration as reflex testing may be an optimal option for genomic alteration assessment at diagnosis of all stage NS-NSLC. This strategy allows sensitive and specific evaluation of the status of 50 genes, looking for mutations, fusions, and amplifications when using a low amount of nucleic acid. When a targeted therapy or an immunotherapy has to be rapidly administered, the absence of initial selection of an analysis by sequencing, depending on the tumor stage, and without waiting for the physician’s request saves time for the patient. It is quite certain that many targeted therapies will probably soon be made available for early-stage NS-NSCLC treatment in routine clinical practice, reinforcing the necessity to look for different molecular alterations at the time of diagnosis. This leads unavoidably to the use of an ultra-fast NGS approach at diagnosis in this setting. Moreover, it will be of added value to combine ultra-fast NGS and multiplex IHC approaches for the identification of the histological classification with both genomic and proteomic biomarkers obtained at the same time [20,89,90]. The latter in situ technologies will allow tissue samples to be saved for further NGS development.

Author Contributions

Conceptualization, P.H.; Data curation, M.I., V.H., C.B., V.L.-F., O.B., S.L. (Sandra Lassalle), S.L. (Salomé Lalvée) and P.H.; Formal analysis, M.I., V.H., C.B., S.H., O.B., S.L. (Salomé Lalvée), V.T., M.A., M.S., D.B. and E.L.-M.; Funding acquisition, P.H.; Investigation, V.H.; Methodology, M.I., V.H., C.B., S.H., V.L.-F., O.B., S.L. (Sandra Lassalle), S.L. (Salomé Lalvée), V.T., M.A., M.S., D.B., D.B. and P.H.; Project administration, M.I. and P.H.; Resources, M.I., V.H., C.B., S.H., V.L.-F., J.B., C.-H.M., E.L.-M. and P.H.; Supervision, M.I. and P.H.; Validation, M.I., V.H., C.B. and P.H.; Visualization, V.H. and P.H.; Writing—original draft, M.I., V.H., C.B., S.H. and P.H.; Writing—review and editing, M.I., V.H., C.B., S.H., V.L.-F., O.B., S.L. (Sandra Lassalle), S.L. (Salomé Lalvée), V.T., M.A., M.S., J.B., C.-H.M., E.L.-M. and P.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Medical Affairs from Thermo Fisher Scientific. The FHU OncoAge supported the article processing charge. The funders had no role in the analysis or writing of this paper.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Centre Hospitalier Universitaire de Nice.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available on request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Howlader, N.; Forjaz, G.; Mooradian, M.J.; Meza, R.; Kong, C.Y.; Cronin, K.A.; Mariotto, A.B.; Lowy, D.R.; Feuer, E.J. The Effect of Advances in Lung-Cancer Treatment on Population Mortality. N. Engl. J. Med. 2020, 383, 640–649. [Google Scholar] [CrossRef] [PubMed]
  2. Melosky, B.; Wheatley-Price, P.; Juergens, R.A.; Sacher, A.; Leighl, N.B.; Tsao, M.S.; Cheema, P.; Snow, S.; Liu, G.; Card, P.B.; et al. The rapidly evolving landscape of novel targeted therapies in advanced non-small cell lung cancer. Lung Cancer 2021, 160, 136–151. [Google Scholar] [CrossRef] [PubMed]
  3. Garrido, P.; Conde, E.; de Castro, J.; Gomez-Roman, J.J.; Felip, E.; Pijuan, L.; Isla, D.; Sanz, J.; Paz-Ares, L.; Lopez-Rios, F. Updated guidelines for predictive biomarker testing in advanced non-small-cell lung cancer: A National Consensus of the Spanish Society of Pathology and the Spanish Society of Medical Oncology. Clin. Transl. Oncol. 2020, 22, 989–1003. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Kerr, K.M.; Bibeau, F.; Thunnissen, E.; Botling, J.; Ryska, A.; Wolf, J.; Ohrling, K.; Burdon, P.; Malapelle, U.; Buttner, R. The evolving landscape of biomarker testing for non-small cell lung cancer in Europe. Lung Cancer 2021, 154, 161–175. [Google Scholar] [CrossRef]
  5. Mosele, F.; Remon, J.; Mateo, J.; Westphalen, C.B.; Barlesi, F.; Lolkema, M.P.; Normanno, N.; Scarpa, A.; Robson, M.; Meric-Bernstam, F.; et al. Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: A report from the ESMO Precision Medicine Working Group. Ann. Oncol. 2020, 31, 1491–1505. [Google Scholar] [CrossRef]
  6. Pennell, N.A.; Arcila, M.E.; Gandara, D.R.; West, H. Biomarker Testing for Patients With Advanced Non-Small Cell Lung Cancer: Real-World Issues and Tough Choices. Am. Soc. Clin. Oncol. Educ. Book 2019, 39, 531–542. [Google Scholar] [CrossRef]
  7. Hanna, N.H.; Robinson, A.G.; Temin, S.; Baker, S., Jr.; Brahmer, J.R.; Ellis, P.M.; Gaspar, L.E.; Haddad, R.Y.; Hesketh, P.J.; Jain, D.; et al. Therapy for Stage IV Non-Small-Cell Lung Cancer With Driver Alterations: ASCO and OH (CCO) Joint Guideline Update. J. Clin. Oncol. 2021, 39, 1040–1091. [Google Scholar] [CrossRef]
  8. Kazdal, D.; Hofman, V.; Christopoulos, P.; Ilie, M.; Stenzinger, A.; Hofman, P. Fusion-positive non-small cell lung carcinoma: Biological principles, clinical practice, and diagnostic implications. Genes Chromosomes Cancer 2022, 61, 244–260. [Google Scholar] [CrossRef]
  9. Hellyer, J.A.; White, M.N.; Gardner, R.M.; Cunanan, K.; Padda, S.K.; Das, M.; Ramchandran, K.; Neal, J.W.; Wakelee, H.A. Impact of Tumor Suppressor Gene Co-Mutations on Differential Response to EGFR TKI Therapy in EGFR L858R and Exon 19 Deletion Lung Cancer. Clin. Lung Cancer 2021, S1525-7304(21)00245-X. [Google Scholar] [CrossRef]
  10. Mograbi, B.; Heeke, S.; Hofman, P. The Importance of STK11/LKB1 Assessment in Non-Small Cell Lung Carcinomas. Diagnostics 2021, 11, 196. [Google Scholar] [CrossRef]
  11. Nadal, E.; Heeke, S.; Benzaquen, J.; Vilarino, N.; Navarro, A.; Azuara, D.; Varela, M.; Otto, J.; Baixeras, N.; Shahbazian, D.; et al. Two Patients With Advanced-Stage Lung Adenocarcinoma With Radiologic Complete Response to Nivolumab Treatment Harboring an STK11/LKB1 Mutation. JCO Precis Oncol. 2020, 4, 1239–1245. [Google Scholar] [CrossRef] [PubMed]
  12. Ricciuti, B.; Arbour, K.C.; Lin, J.J.; Vajdi, A.; Vokes, N.; Hong, L.; Zhang, J.; Tolstorukov, M.Y.; Li, Y.Y.; Spurr, L.F.; et al. Diminished Efficacy of Programmed Death-(Ligand)1 Inhibition in STK11- and KEAP1-Mutant Lung Adenocarcinoma Is Affected by KRAS Mutation Status. J. Thorac. Oncol. 2022, 17, 399–410. [Google Scholar] [CrossRef] [PubMed]
  13. Hanna, N.; Johnson, D.; Temin, S.; Baker, S., Jr.; Brahmer, J.; Ellis, P.M.; Giaccone, G.; Hesketh, P.J.; Jaiyesimi, I.; Leighl, N.B.; et al. Systemic Therapy for Stage IV Non-Small-Cell Lung Cancer: American Society of Clinical Oncology Clinical Practice Guideline Update. J. Clin. Oncol. 2017, 35, 3484–3515. [Google Scholar] [CrossRef] [PubMed]
  14. Petrelli, F.; Ferrara, R.; Signorelli, D.; Ghidini, A.; Proto, C.; Roudi, R.; Sabet, M.N.; Facelli, S.; Garassino, M.C.; Luciani, A.; et al. Immune checkpoint inhibitors and chemotherapy in first-line NSCLC: A meta-analysis. Immunotherapy 2021, 13, 621–631. [Google Scholar] [CrossRef]
  15. Ahern, E.; Solomon, B.J.; Hui, R.; Pavlakis, N.; O’Byrne, K.; Hughes, B.G.M. Neoadjuvant immunotherapy for non-small cell lung cancer: Right drugs, right patient, right time? J. Immunother. Cancer 2021, 9, e002248. [Google Scholar] [CrossRef]
  16. Jones, D.R.; Wu, Y.L.; Tsuboi, M.; Herbst, R.S. Targeted therapies for resectable lung adenocarcinoma: ADAURA opens for thoracic oncologic surgeons. J. Thorac. Cardiovasc. Surg. 2021, 162, 288–292. [Google Scholar] [CrossRef]
  17. Koch, A.L.; Vellanki, P.J.; Drezner, N.; Li, X.; Mishra-Kalyani, P.S.; Shen, Y.L.; Xia, H.; Li, Y.; Liu, J.; Zirkelbach, J.F.; et al. FDA Approval Summary: Osimertinib for Adjuvant Treatment of Surgically Resected Non-Small Cell Lung Cancer, a Collaborative Project Orbis Review. Clin. Cancer Res. 2021, 27, 6638–6643. [Google Scholar] [CrossRef]
  18. Hanna, N.H.; Schneider, B.J.; Temin, S.; Baker, S., Jr.; Brahmer, J.; Ellis, P.M.; Gaspar, L.E.; Haddad, R.Y.; Hesketh, P.J.; Jain, D.; et al. Therapy for Stage IV Non-Small-Cell Lung Cancer Without Driver Alterations: ASCO and OH (CCO) Joint Guideline Update. J. Clin. Oncol. 2020, 38, 1608–1632. [Google Scholar] [CrossRef]
  19. Mazieres, J.; Drilon, A.; Lusque, A.; Mhanna, L.; Cortot, A.B.; Mezquita, L.; Thai, A.A.; Mascaux, C.; Couraud, S.; Veillon, R.; et al. Immune checkpoint inhibitors for patients with advanced lung cancer and oncogenic driver alterations: Results from the IMMUNOTARGET registry. Ann. Oncol. 2019, 30, 1321–1328. [Google Scholar] [CrossRef]
  20. Sheffield, B.S.; Beharry, A.; Diep, J.; Perdrizet, K.; Iafolla, M.A.J.; Raskin, W.; Dudani, S.; Brett, M.A.; Starova, B.; Olsen, B.; et al. Point of Care Molecular Testing: Community-Based Rapid Next-Generation Sequencing to Support Cancer Care. Curr. Oncol. 2022, 29, 1326–1334. [Google Scholar] [CrossRef]
  21. DiStasio, M.; Chen, Y.; Rangachari, D.; Costa, D.B.; Heher, Y.K.; VanderLaan, P.A. Molecular Testing Turnaround Time for Non-Small Cell Lung Cancer in Routine Clinical Practice Confirms Feasibility of CAP/IASLC/AMP Guideline Recommendations: A Single-center Analysis. Clin. Lung Cancer 2017, 18, e349–e356. [Google Scholar] [CrossRef] [PubMed]
  22. Heeke, S.; Hofman, V.; Long-Mira, E.; Lespinet, V.; Lalvee, S.; Bordone, O.; Ribeyre, C.; Tanga, V.; Benzaquen, J.; Leroy, S.; et al. Use of the Ion PGM and the GeneReader NGS Systems in Daily Routine Practice for Advanced Lung Adenocarcinoma Patients: A Practical Point of View Reporting a Comparative Study and Assessment of 90 Patients. Cancers 2018, 10, 88. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Al-Ahmadi, A.; Ardeshir-Larijani, F.; Fu, P.; Cao, S.; Lipka, M.B.; Dowlati, A.; Bruno, D.S. Next Generation Sequencing of Advanced Non-Small Cell Lung Cancer: Utilization Based on Race and Impact on Survival. Clin. Lung Cancer 2021, 22, 16–22.e11. [Google Scholar] [CrossRef] [PubMed]
  24. Anand, K.; Phung, T.L.; Bernicker, E.H.; Cagle, P.T.; Olsen, R.J.; Thomas, J.S. Clinical Utility of Reflex Ordered Testing for Molecular Biomarkers in Lung Adenocarcinoma. Clin. Lung Cancer 2020, 21, 437–442. [Google Scholar] [CrossRef] [PubMed]
  25. Kim, J.H.; Yoon, S.; Lee, D.H.; Jang, S.J.; Chun, S.M.; Kim, S.W. Real-world utility of next-generation sequencing for targeted gene analysis and its application to treatment in lung adenocarcinoma. Cancer Med. 2021, 10, 3197–3204. [Google Scholar] [CrossRef]
  26. Miller, T.E.; Yang, M.; Bajor, D.; Friedman, J.D.; Chang, R.Y.C.; Dowlati, A.; Willis, J.E.; Sadri, N. Clinical utility of reflex testing using focused next-generation sequencing for management of patients with advanced lung adenocarcinoma. J. Clin. Pathol. 2018, 71, 1108–1115. [Google Scholar] [CrossRef]
  27. Zacharias, M.; Absenger, G.; Kashofer, K.; Wurm, R.; Lindenmann, J.; Terbuch, A.; Konjic, S.; Sauer, S.; Gollowitsch, F.; Gorkiewicz, G.; et al. Reflex testing in non-small cell lung carcinoma using DNA- and RNA-based next-generation sequencing-a single-center experience. Transl. Lung Cancer Res. 2021, 10, 4221–4234. [Google Scholar] [CrossRef]
  28. Dagogo-Jack, I.; Azzolli, C.G.; Fintelmann, F.; Mino-Kenudson, M.; Farago, A.F.; Gainor, J.F.; Jiang, G.; Piotrowska, Z.; Heist, R.S.; Lennes, I.T.; et al. Clinical Utility of Rapid EGFR Genotyping in Advanced Lung Cancer. JCO Precis Oncol. 2018, 2018, PO.17.00299. [Google Scholar] [CrossRef]
  29. Dagogo-Jack, I.; Robinson, H.; Mino-Kenudson, M.; Farago, A.F.; Kamesan, V.; Iafrate, A.J.; Shaw, A.T.; Lennerz, J.K. Expediting Comprehensive Molecular Analysis to Optimize Initial Treatment of Lung Cancer Patients With Minimal Smoking History. J. Thorac. Oncol. 2019, 14, 835–843. [Google Scholar] [CrossRef]
  30. Camidge, D.R.; Doebele, R.C.; Kerr, K.M. Comparing and contrasting predictive biomarkers for immunotherapy and targeted therapy of NSCLC. Nat. Rev. Clin. Oncol. 2019, 16, 341–355. [Google Scholar] [CrossRef]
  31. Rosas, D.; Raez, L.E.; Russo, A.; Rolfo, C. Neuregulin 1 Gene (NRG1). A Potentially New Targetable Alteration for the Treatment of Lung Cancer. Cancers 2021, 13, 5038. [Google Scholar] [CrossRef] [PubMed]
  32. Shapiro, G.I.; LoRusso, P.; Dowlati, A.; Do, K.T.; Jacobson, C.A.; Vaishampayan, U.; Weise, A.; Caimi, P.F.; Eder, J.P.; French, C.A.; et al. A Phase 1 study of RO6870810, a novel bromodomain and extra-terminal protein inhibitor, in patients with NUT carcinoma, other solid tumours, or diffuse large B-cell lymphoma. Br. J. Cancer 2021, 124, 744–753. [Google Scholar] [CrossRef]
  33. Schoenfeld, A.J.; Bandlamudi, C.; Lavery, J.A.; Montecalvo, J.; Namakydoust, A.; Rizvi, H.; Egger, J.; Concepcion, C.P.; Paul, S.; Arcila, M.E.; et al. The Genomic Landscape of SMARCA4 Alterations and Associations with Outcomes in Patients with Lung Cancer. Clin. Cancer Res. 2020, 26, 5701–5708. [Google Scholar] [CrossRef] [PubMed]
  34. Zhang, K.; Hong, X.; Song, Z.; Xu, Y.; Li, C.; Wang, G.; Zhang, Y.; Zhao, X.; Zhao, Z.; Zhao, J.; et al. Identification of Deleterious NOTCH Mutation as Novel Predictor to Efficacious Immunotherapy in NSCLC. Clin. Cancer Res. 2020, 26, 3649–3661. [Google Scholar] [CrossRef] [Green Version]
  35. Hofman, P. What Is New in Biomarker Testing at Diagnosis of Advanced Non-Squamous Non-Small Cell Lung Carcinoma? Implications for Cytology and Liquid Biopsy. J. Mol. Pathol. 2021, 2, 147–172. [Google Scholar] [CrossRef]
  36. Roy-Chowdhuri, S.; Goswami, R.S.; Chen, H.; Patel, K.P.; Routbort, M.J.; Singh, R.R.; Broaddus, R.R.; Barkoh, B.A.; Manekia, J.; Yao, H.; et al. Factors affecting the success of next-generation sequencing in cytology specimens. Cancer Cytopathol. 2015, 123, 659–668. [Google Scholar] [CrossRef]
  37. Pisapia, P.; Pepe, F.; Iaccarino, A.; Sgariglia, R.; Nacchio, M.; Conticelli, F.; Salatiello, M.; Tufano, R.; Russo, G.; Gragnano, G.; et al. Next Generation Sequencing in Cytopathology: Focus on Non-Small Cell Lung Cancer. Front. Med. 2021, 8, 633923. [Google Scholar] [CrossRef]
  38. Cohen, D.; Hondelink, L.M.; Solleveld-Westerink, N.; Uljee, S.M.; Ruano, D.; Cleton-Jansen, A.M.; von der Thusen, J.H.; Ramai, S.R.S.; Postmus, P.E.; Graadt van Roggen, J.F.; et al. Optimizing Mutation and Fusion Detection in NSCLC by Sequential DNA and RNA Sequencing. J. Thorac. Oncol. 2020, 15, 1000–1014. [Google Scholar] [CrossRef] [Green Version]
  39. Hofman, V.; Benzaquen, J.; Heeke, S.; Lassalle, S.; Poudenx, M.; Long, E.; Lanteri, E.; Bordone, O.; Lespinet, V.; Tanga, V.; et al. Real-world assessment of the BRAF status in non-squamous cell lung carcinoma using VE1 immunohistochemistry: A single laboratory experience (LPCE, Nice, France). Lung Cancer 2020, 145, 58–62. [Google Scholar] [CrossRef]
  40. Ilie, M.; Long, E.; Hofman, V.; Dadone, B.; Marquette, C.H.; Mouroux, J.; Vignaud, J.M.; Begueret, H.; Merlio, J.P.; Capper, D.; et al. Diagnostic value of immunohistochemistry for the detection of the BRAFV600E mutation in primary lung adenocarcinoma Caucasian patients. Ann. Oncol. 2013, 24, 742–748. [Google Scholar] [CrossRef]
  41. Lassalle, S.; Hofman, V.; Heeke, S.; Benzaquen, J.; Long, E.; Poudenx, M.; Lanteri, E.; Boutros, J.; Tanga, V.; Zahaf, K.; et al. Targeted Assessment of the EGFR Status as Reflex Testing in Treatment-Naive Non-Squamous Cell Lung Carcinoma Patients: A Single Laboratory Experience (LPCE, Nice, France). Cancers 2020, 12, 955. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Yu, T.M.; Morrison, C.; Gold, E.J.; Tradonsky, A.; Layton, A.J. Multiple Biomarker Testing Tissue Consumption and Completion Rates With Single-gene Tests and Investigational Use of Oncomine Dx Target Test for Advanced Non-Small-cell Lung Cancer: A Single-center Analysis. Clin. Lung Cancer 2019, 20, 20–29.e28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Christofyllakis, K.; Bittenbring, J.T.; Thurner, L.; Ahlgrimm, M.; Stilgenbauer, S.; Bewarder, M.; Kaddu-Mulindwa, D. Cost-effectiveness of precision cancer medicine-current challenges in the use of next generation sequencing for comprehensive tumour genomic profiling and the role of clinical utility frameworks (Review). Mol. Clin. Oncol. 2022, 16, 21. [Google Scholar] [CrossRef] [PubMed]
  44. Pennell, N.A.; Mutebi, A.; Zhou, Z.Y.; Ricculli, M.L.; Tang, W.; Wang, H.; Guerin, A.; Arnhart, T.; Dalal, A.; Sasane, M.; et al. Economic Impact of Next-Generation Sequencing Versus Single-Gene Testing to Detect Genomic Alterations in Metastatic Non-Small-Cell Lung Cancer Using a Decision Analytic Model. JCO Precis Oncol. 2019, 3, 1–9. [Google Scholar] [CrossRef] [PubMed]
  45. Pisapia, P.; Pepe, F.; Baggi, A.; Barberis, M.; Galvano, A.; Gristina, V.; Mastrilli, F.; Novello, S.; Pagni, F.; Pasini, S.; et al. Next generation diagnostic algorithm in non-small cell lung cancer predictive molecular pathology: The KWAY Italian multicenter cost evaluation study. Crit. Rev. Oncol. Hematol. 2022, 169, 103525. [Google Scholar] [CrossRef]
  46. Pruneri, G.; De Braud, F.; Sapino, A.; Aglietta, M.; Vecchione, A.; Giusti, R.; Marchio, C.; Scarpino, S.; Baggi, A.; Bonetti, G.; et al. Next-Generation Sequencing in Clinical Practice: Is It a Cost-Saving Alternative to a Single-Gene Testing Approach? Pharm. Open 2021, 5, 285–298. [Google Scholar] [CrossRef]
  47. Tan, A.C.; Lai, G.G.Y.; Tan, G.S.; Poon, S.Y.; Doble, B.; Lim, T.H.; Aung, Z.W.; Takano, A.; Tan, W.L.; Ang, M.K.; et al. Utility of incorporating next-generation sequencing (NGS) in an Asian non-small cell lung cancer (NSCLC) population: Incremental yield of actionable alterations and cost-effectiveness analysis. Lung Cancer 2020, 139, 207–215. [Google Scholar] [CrossRef] [Green Version]
  48. Volckmar, A.L.; Leichsenring, J.; Kirchner, M.; Christopoulos, P.; Neumann, O.; Budczies, J.; Morais de Oliveira, C.M.; Rempel, E.; Buchhalter, I.; Brandt, R.; et al. Combined targeted DNA and RNA sequencing of advanced NSCLC in routine molecular diagnostics: Analysis of the first 3000 Heidelberg cases. Int. J. Cancer 2019, 145, 649–661. [Google Scholar] [CrossRef]
  49. Yu, T.M.; Morrison, C.; Gold, E.J.; Tradonsky, A.; Arnold, R.J.G. Budget Impact of Next-Generation Sequencing for Molecular Assessment of Advanced Non-Small Cell Lung Cancer. Value Health 2018, 21, 1278–1285. [Google Scholar] [CrossRef] [Green Version]
  50. Zheng, Y.; Vioix, H.; Liu, F.X.; Singh, B.; Sharma, S.; Sharda, D. Diagnostic and economic value of biomarker testing for targetable mutations in non-small-cell lung cancer: A literature review. Future Oncol. 2022, 18, 505–518. [Google Scholar] [CrossRef]
  51. De Maglio, G.; Pasello, G.; Dono, M.; Fiorentino, M.; Follador, A.; Sciortino, M.; Malapelle, U.; Tiseo, M. The storm of NGS in NSCLC diagnostic-therapeutic pathway: How to sun the real clinical practice. Crit. Rev. Oncol. Hematol. 2022, 169, 103561. [Google Scholar] [CrossRef] [PubMed]
  52. Zhong, Y.; Xu, F.; Wu, J.; Schubert, J.; Li, M.M. Application of Next Generation Sequencing in Laboratory Medicine. Ann. Lab. Med. 2021, 41, 25–43. [Google Scholar] [CrossRef] [PubMed]
  53. Skoulidis, F.; Heymach, J.V. Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy. Nat. Rev. Cancer 2019, 19, 495–509. [Google Scholar] [CrossRef] [PubMed]
  54. Bruno, R.; Fontanini, G. Next Generation Sequencing for Gene Fusion Analysis in Lung Cancer: A Literature Review. Diagnostics 2020, 10, 521. [Google Scholar] [CrossRef]
  55. Horgan, D.; Curigliano, G.; Riess, O.; Hofman, P.; Buttner, R.; Conte, P.; Cufer, T.; Gallagher, W.M.; Georges, N.; Kerr, K.; et al. Identifying the Steps Required to Effectively Implement Next-Generation Sequencing in Oncology at a National Level in Europe. J. Pers. Med. 2022, 12, 72. [Google Scholar] [CrossRef]
  56. Schluckebier, L.; Caetano, R.; Garay, O.U.; Montenegro, G.T.; Custodio, M.; Aran, V.; Gil Ferreira, C. Cost-effectiveness analysis comparing companion diagnostic tests for EGFR, ALK, and ROS1 versus next-generation sequencing (NGS) in advanced adenocarcinoma lung cancer patients. BMC Cancer 2020, 20, 875. [Google Scholar] [CrossRef]
  57. Steuten, L.; Goulart, B.; Meropol, N.J.; Pritchard, D.; Ramsey, S.D. Cost Effectiveness of Multigene Panel Sequencing for Patients With Advanced Non-Small-Cell Lung Cancer. JCO Clin. Cancer Inf. 2019, 3, 1–10. [Google Scholar] [CrossRef]
  58. Goswami, R.S.; Luthra, R.; Singh, R.R.; Patel, K.P.; Routbort, M.J.; Aldape, K.D.; Yao, H.; Dang, H.D.; Barkoh, B.A.; Manekia, J.; et al. Identification of Factors Affecting the Success of Next-Generation Sequencing Testing in Solid Tumors. Am. J. Clin. Pathol. 2016, 145, 222–237. [Google Scholar] [CrossRef]
  59. Hofman, P. The challenges of evaluating predictive biomarkers using small biopsy tissue samples and liquid biopsies from non-small cell lung cancer patients. J. Thorac. Dis. 2019, 11, S57–S64. [Google Scholar] [CrossRef]
  60. Ilie, M.; Hofman, P. Pitfalls in lung cancer molecular pathology: How to limit them in routine practice? Curr. Med. Chem. 2012, 19, 2638–2651. [Google Scholar] [CrossRef]
  61. Rolfo, C.; Mack, P.; Scagliotti, G.V.; Aggarwal, C.; Arcila, M.E.; Barlesi, F.; Bivona, T.; Diehn, M.; Dive, C.; Dziadziuszko, R.; et al. Liquid Biopsy for Advanced NSCLC: A Consensus Statement From the International Association for the Study of Lung Cancer. J. Thorac. Oncol. 2021, 16, 1647–1662. [Google Scholar] [CrossRef] [PubMed]
  62. Li, B.T.; Smit, E.F.; Goto, Y.; Nakagawa, K.; Udagawa, H.; Mazieres, J.; Nagasaka, M.; Bazhenova, L.; Saltos, A.N.; Felip, E.; et al. Trastuzumab Deruxtecan in HER2-Mutant Non-Small-Cell Lung Cancer. N. Engl. J. Med. 2022, 386, 241–251. [Google Scholar] [CrossRef] [PubMed]
  63. Ou, S.I.; Janne, P.A.; Leal, T.A.; Rybkin, I.I.; Sabari, J.K.; Barve, M.A.; Bazhenova, L.; Johnson, M.L.; Velastegui, K.L.; Cilliers, C.; et al. First-in-Human Phase I/IB Dose-Finding Study of Adagrasib (MRTX849) in Patients With Advanced KRAS(G12C) Solid Tumors (KRYSTAL-1). J. Clin. Oncol. 2022, JCO2102752. [Google Scholar] [CrossRef] [PubMed]
  64. Park, K.; Haura, E.B.; Leighl, N.B.; Mitchell, P.; Shu, C.A.; Girard, N.; Viteri, S.; Han, J.Y.; Kim, S.W.; Lee, C.K.; et al. Amivantamab in EGFR Exon 20 Insertion-Mutated Non-Small-Cell Lung Cancer Progressing on Platinum Chemotherapy: Initial Results From the CHRYSALIS Phase I Study. J. Clin. Oncol. 2021, 39, 3391–3402. [Google Scholar] [CrossRef]
  65. Colli, L.M.; Machiela, M.J.; Zhang, H.; Myers, T.A.; Jessop, L.; Delattre, O.; Yu, K.; Chanock, S.J. Landscape of Combination Immunotherapy and Targeted Therapy to Improve Cancer Management. Cancer Res. 2017, 77, 3666–3671. [Google Scholar] [CrossRef] [Green Version]
  66. Gotwals, P.; Cameron, S.; Cipolletta, D.; Cremasco, V.; Crystal, A.; Hewes, B.; Mueller, B.; Quaratino, S.; Sabatos-Peyton, C.; Petruzzelli, L.; et al. Prospects for combining targeted and conventional cancer therapy with immunotherapy. Nat. Rev. Cancer 2017, 17, 286–301. [Google Scholar] [CrossRef]
  67. Socinski, M.A.; Obasaju, C.; Gandara, D.; Hirsch, F.R.; Bonomi, P.; Bunn, P.A., Jr.; Kim, E.S.; Langer, C.J.; Natale, R.B.; Novello, S.; et al. Current and Emergent Therapy Options for Advanced Squamous Cell Lung Cancer. J. Thorac. Oncol. 2018, 13, 165–183. [Google Scholar] [CrossRef] [Green Version]
  68. Wu, Z.; Man, S.; Sun, R.; Li, Z.; Wu, Y.; Zuo, D. Recent advances and challenges of immune checkpoint inhibitors in immunotherapy of non-small cell lung cancer. Int. Immunopharmacol. 2020, 85, 106613. [Google Scholar] [CrossRef]
  69. Greenhalgh, J.; Boland, A.; Bates, V.; Vecchio, F.; Dundar, Y.; Chaplin, M.; Green, J.A. First-line treatment of advanced epidermal growth factor receptor (EGFR) mutation positive non-squamous non-small cell lung cancer. Cochrane Database Syst. Rev. 2021, 3, CD010383. [Google Scholar] [CrossRef]
  70. Lewis, W.E.; Hong, L.; Mott, F.E.; Simon, G.; Wu, C.C.; Rinsurongkawong, W.; Lee, J.J.; Lam, V.K.; Heymach, J.V.; Zhang, J.; et al. Efficacy of Targeted Inhibitors in Metastatic Lung Squamous Cell Carcinoma With EGFR or ALK Alterations. JTO Clin. Res. Rep. 2021, 2, 100237. [Google Scholar] [CrossRef]
  71. Stinchcombe, T.E. Targeted therapies for locally advanced or metastatic squamous cell carcinoma of the lung. Curr. Treat. Options Oncol. 2013, 14, 568–579. [Google Scholar] [CrossRef] [PubMed]
  72. Aggarwal, C.; Rolfo, C.D.; Oxnard, G.R.; Gray, J.E.; Sholl, L.M.; Gandara, D.R. Strategies for the successful implementation of plasma-based NSCLC genotyping in clinical practice. Nat. Rev. Clin. Oncol. 2021, 18, 56–62. [Google Scholar] [CrossRef] [PubMed]
  73. Heitzer, E.; van den Broek, D.; Denis, M.G.; Hofman, P.; Hubank, M.; Mouliere, F.; Paz-Ares, L.; Schuuring, E.; Sultmann, H.; Vainer, G.; et al. Recommendations for a practical implementation of circulating tumor DNA mutation testing in metastatic non-small-cell lung cancer. ESMO Open 2022, 7, 100399. [Google Scholar] [CrossRef] [PubMed]
  74. Merritt, R.E.; Abdel-Rasoul, M.; Fitzgerald, M.; D’Souza, D.M.; Kneuertz, P.J. The Academic Facility Type Is Associated With Improved Overall Survival for Early-Stage Lung Cancer. Ann. Thorac. Surg. 2021, 111, 261–268. [Google Scholar] [CrossRef] [PubMed]
  75. Woodard, G.A.; Jones, K.D.; Jablons, D.M. Lung Cancer Staging and Prognosis. Cancer Treat. Res. 2016, 170, 47–75. [Google Scholar] [CrossRef] [PubMed]
  76. Hofmann, M.H.; Gerlach, D.; Misale, S.; Petronczki, M.; Kraut, N. Expanding the Reach of Precision Oncology by Drugging All KRAS Mutants. Cancer Discov. 2022, 12, 924–937. [Google Scholar] [CrossRef] [PubMed]
  77. Kartolo, A.; Robinson, A.; Fung, A.S. Optimal first-line immune checkpoint inhibitor treatment in lung cancer: How to choose? Future Oncol. 2022, 18, 635–638. [Google Scholar] [CrossRef]
  78. Middleton, G.; Robbins, H.; Andre, F.; Swanton, C. A state-of-the-art review of stratified medicine in cancer: Towards a future precision medicine strategy in cancer. Ann. Oncol. 2022, 33, 143–157. [Google Scholar] [CrossRef]
  79. Tan, A.C.; Tan, D.S.W. Targeted Therapies for Lung Cancer Patients With Oncogenic Driver Molecular Alterations. J. Clin. Oncol. 2022, 40, 611–625. [Google Scholar] [CrossRef]
  80. Mielgo-Rubio, X.; Calvo, V.; Luna, J.; Remon, J.; Martin, M.; Berraondo, P.; Jarabo, J.R.; Higuera, O.; Conde, E.; De Castro, J.; et al. Immunotherapy Moves to the Early-Stage Setting in Non-Small Cell Lung Cancer: Emerging Evidence and the Role of Biomarkers. Cancers 2020, 12, 3459. [Google Scholar] [CrossRef]
  81. Friedlaender, A.; Naidoo, J.; Banna, G.L.; Metro, G.; Forde, P.; Addeo, A. Role and impact of immune checkpoint inhibitors in neoadjuvant treatment for NSCLC. Cancer Treat. Rev. 2022, 104, 102350. [Google Scholar] [CrossRef] [PubMed]
  82. Roller, J.F.; Veeramachaneni, N.K.; Zhang, J. Exploring the Evolving Scope of Neoadjuvant Immunotherapy in NSCLC. Cancers 2022, 14, 741. [Google Scholar] [CrossRef] [PubMed]
  83. Friedlaender, A.; Addeo, A.; Russo, A.; Gregorc, V.; Cortinovis, D.; Rolfo, C.D. Targeted Therapies in Early Stage NSCLC: Hype or Hope? Int. J. Mol. Sci. 2020, 21, 6329. [Google Scholar] [CrossRef] [PubMed]
  84. Hofman, P. Next-Generation Sequencing with Liquid Biopsies from Treatment-Naive Non-Small Cell Lung Carcinoma Patients. Cancers 2021, 13, 2049. [Google Scholar] [CrossRef]
  85. Dagogo-Jack, I.; Shaw, A.T. Tumour heterogeneity and resistance to cancer therapies. Nat. Rev. Clin. Oncol. 2018, 15, 81–94. [Google Scholar] [CrossRef]
  86. Lazzari, C.; Bulotta, A.; Cangi, M.G.; Bucci, G.; Pecciarini, L.; Bonfiglio, S.; Lorusso, V.; Ippati, S.; Arrigoni, G.; Grassini, G.; et al. Next Generation Sequencing in Non-Small Cell Lung Cancer: Pitfalls and Opportunities. Diagnostics 2020, 10, 1092. [Google Scholar] [CrossRef]
  87. Huang, B.; Chen, Q.; Allison, D.; El Khouli, R.; Peh, K.H.; Mobley, J.; Anderson, A.; Durbin, E.B.; Goodin, D.; Villano, J.L.; et al. Molecular Tumor Board Review and Improved Overall Survival in Non-Small-Cell Lung Cancer. JCO Precis Oncol. 2021, 5, 1530–1539. [Google Scholar] [CrossRef]
  88. Luchini, C.; Lawlor, R.T.; Milella, M.; Scarpa, A. Molecular Tumor Boards in Clinical Practice. Trends Cancer 2020, 6, 738–744. [Google Scholar] [CrossRef]
  89. Ilie, M.; Beaulande, M.; Hamila, M.; Erb, G.; Hofman, V.; Hofman, P. Automated chromogenic multiplexed immunohistochemistry assay for diagnosis and predictive biomarker testing in non-small cell lung cancer. Lung Cancer 2018, 124, 90–94. [Google Scholar] [CrossRef]
  90. Ilie, M.; Beaulande, M.; Long-Mira, E.; Bontoux, C.; Zahaf, K.; Lalvee, S.; Hamila, M.; Benzaquen, J.; Cohen, C.; Berthet, J.P.; et al. Analytical validation of automated multiplex chromogenic immunohistochemistry for diagnostic and predictive purpose in non-small cell lung cancer. Lung Cancer 2022, 166, 1–8. [Google Scholar] [CrossRef]
  91. Lengel, H.B.; Connolly, J.G.; Jones, G.D.; Caso, R.; Zhou, J.; Sanchez-Vega, F.; Mastrogiacomo, B.; Isbell, J.M.; Li, B.T.; Liu, Y.; et al. The Emerging Importance of Tumor Genomics in Operable Non-Small Cell Lung Cancer. Cancers 2021, 13, 3656. [Google Scholar] [CrossRef] [PubMed]
  92. Soh, J.; Hamada, A.; Fujino, T.; Mitsudomi, T. Perioperative Therapy for Non-Small Cell Lung Cancer with Immune Checkpoint Inhibitors. Cancers 2021, 13, 4035. [Google Scholar] [CrossRef] [PubMed]
  93. Ignatiadis, M.; Sledge, G.W.; Jeffrey, S.S. Liquid biopsy enters the clinic—Implementation issues and future challenges. Nat. Rev. Clin. Oncol. 2021, 18, 297–312. [Google Scholar] [CrossRef] [PubMed]
  94. Liang, W.; Zhao, Y.; Huang, W.; Gao, Y.; Xu, W.; Tao, J.; Yang, M.; Li, L.; Ping, W.; Shen, H.; et al. Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA). Theranostics 2019, 9, 2056–2070. [Google Scholar] [CrossRef]
  95. Sands, J.M.; Nguyen, T.; Shivdasani, P.; Sacher, A.G.; Cheng, M.L.; Alden, R.S.; Janne, P.A.; Kuo, F.C.; Oxnard, G.R.; Sholl, L.M. Next-generation sequencing informs diagnosis and identifies unexpected therapeutic targets in lung squamous cell carcinomas. Lung Cancer 2020, 140, 35–41. [Google Scholar] [CrossRef] [PubMed]
  96. Kim, I.A.; Hur, J.Y.; Kim, H.J.; Park, J.H.; Hwang, J.J.; Lee, S.A.; Lee, S.E.; Kim, W.S.; Lee, K.Y. Targeted Next-Generation Sequencing Analysis for Recurrence in Early-Stage Lung Adenocarcinoma. Ann. Surg. Oncol. 2021, 28, 3983–3993. [Google Scholar] [CrossRef]
Figure 1. Genexus System workflows used in this study. (A) Workflow using the Maxwell automate for DNA and RNA extraction. (B) Workflow with AutoLys tubes and Genexus Purification System for DNA and RNA extraction.
Figure 1. Genexus System workflows used in this study. (A) Workflow using the Maxwell automate for DNA and RNA extraction. (B) Workflow with AutoLys tubes and Genexus Purification System for DNA and RNA extraction.
Cancers 14 02258 g001
Figure 2. Distribution of driver molecular alterations detected in NS-NSCLC specimens during the study period.
Figure 2. Distribution of driver molecular alterations detected in NS-NSCLC specimens during the study period.
Cancers 14 02258 g002aCancers 14 02258 g002bCancers 14 02258 g002c
Table 1. Main epidemiological and clinico-pathological features of the study population. EBUS: endobronchial ultrasound.
Table 1. Main epidemiological and clinico-pathological features of the study population. EBUS: endobronchial ultrasound.
Characteristicsn (%)
259 (100)
Age at diagnosisMedian69
Range34–84
GenderMale197 (76)
Female62 (24)
Smoking statusSmokers186(72)
Non-smokers44 (17)
Unknown29 (11)
Type of specimensBronchial biopsy153 (59)
Transthoracic biopsy47 (18)
Surgical specimen39 (15)
Pleural effusion (cellblock)13 (5)
EBUS7 (3)
HistologyAdenocarcinoma250 (97)
Large cell carcinoma9 (3)
pTNM stageStage I78 (30)
Stage II73 (28)
Stage III28 (11)
Stage IV80 (31)
Table 2. Throughput of analyses during the study period. OPA: Oncomine Precision Assay.
Table 2. Throughput of analyses during the study period. OPA: Oncomine Precision Assay.
OPA analyses
Overall = 506
DNA252
RNA254
Failed DNA10/252 (4%)
Failed RNA5/254 (2%)
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Ilié, M.; Hofman, V.; Bontoux, C.; Heeke, S.; Lespinet-Fabre, V.; Bordone, O.; Lassalle, S.; Lalvée, S.; Tanga, V.; Allegra, M.; et al. Setting Up an Ultra-Fast Next-Generation Sequencing Approach as Reflex Testing at Diagnosis of Non-Squamous Non-Small Cell Lung Cancer; Experience of a Single Center (LPCE, Nice, France). Cancers 2022, 14, 2258. https://doi.org/10.3390/cancers14092258

AMA Style

Ilié M, Hofman V, Bontoux C, Heeke S, Lespinet-Fabre V, Bordone O, Lassalle S, Lalvée S, Tanga V, Allegra M, et al. Setting Up an Ultra-Fast Next-Generation Sequencing Approach as Reflex Testing at Diagnosis of Non-Squamous Non-Small Cell Lung Cancer; Experience of a Single Center (LPCE, Nice, France). Cancers. 2022; 14(9):2258. https://doi.org/10.3390/cancers14092258

Chicago/Turabian Style

Ilié, Marius, Véronique Hofman, Christophe Bontoux, Simon Heeke, Virginie Lespinet-Fabre, Olivier Bordone, Sandra Lassalle, Salomé Lalvée, Virginie Tanga, Maryline Allegra, and et al. 2022. "Setting Up an Ultra-Fast Next-Generation Sequencing Approach as Reflex Testing at Diagnosis of Non-Squamous Non-Small Cell Lung Cancer; Experience of a Single Center (LPCE, Nice, France)" Cancers 14, no. 9: 2258. https://doi.org/10.3390/cancers14092258

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

Article Metrics

Back to TopTop