Next-Generation Sequencing Testing in Oncology

Faculty Perspectives: Next-Generation Sequencing Testing in Oncology | Part 4 of a 4-Part Series —March 13, 2019

Following the advent of molecularly targeted agents, and more recently, immunotherapy, over the past few decades, we have witnessed dramatic changes in the treatment paradigms for many types of cancer. These advancements were driven by molecular profiling that enabled the identification of those patient populations most likely to benefit from targeted therapy and/or immunotherapy—that is, precision medicine. Identifying biomarkers for these precision medicine initiatives has included the use of various techniques such as immunohistochemistry (IHC), cytogenetics, polymerase chain reaction (PCR), fluorescence in situ hybridization (FISH), comparative genomic hybridization assays, microarrays, and Sanger sequencing, with each method addressing specific clinical needs. More recently, technical advances in sequencing, combined with lower costs for more advanced technologies, have paved the way for the use of next-generation sequencing (NGS) analysis in oncology, with the promise of further refinement in diagnosis, classification, prognostication, and, ultimately, precision treatment. This review provides a discussion on NGS methodology, types of NGS approaches, the clinical utility of NGS in oncology, the challenges and benefits of NGS versus traditional orthogonal approaches to biomarker analysis, and future perspectives for NGS testing.

NGS Methodology

Sanger sequencing, which was the gold standard until the late 2000s, involved the sequencing of one or a few fragments of DNA that were initially amplified by PCR; this technique was limited to specific DNA regions because of high costs and the work involved in sequencing large regions of the genome.1 In contrast, NGS is a high-throughput method that uses massively parallel sequencing of multiple short fragments of DNA that do not require previous knowledge of the genome per se, thus allowing for simultaneous sequencing of multiple genes.1-3

Current basic methodology of NGS includes nucleic acid extraction and sample processing, library preparation, amplification, sequencing, and bioinformatics data analysis and interpretation (Figure 1).1 Sample processing and library preparation refers to readying sample DNA for use in a sequencer. This involves shearing the sample DNA into smaller fragments, followed by repairing DNA ends and, finally adding adapters to the DNA ends. Adapter designs can vary depending on the applications and may include patient-specific barcodes to allow for multiplexing, molecular barcodes or unique molecular identifiers to allow for error-correction, hybridization sequences to permit binding of the DNA fragment to a surface (such as P5/P7 sequences for flow cell binding), and sequencing primer binding sites.3 The final library contains short DNA fragments with adapters.

Figure 1

Unless the library is to be used for whole-genome sequencing (WGS), the DNA library must then be enriched for the targets of interest. Enrichment approaches may use either hybridization-based or amplification-based protocols, with the choice of strategy dictated by assay design and target size.3 In hybrid capture, the sample DNA fragments are selectively hybridized to biotinylated oligonucleotide probes (or baits) that are designed with homology to the genes of interest and subsequently pulled down by streptavidin-coated magnetic beads to obtain libraries that are enriched with the targets of interest.4 Amplification-based sequencing provides enrichment of target genes by PCR amplifying with primers designed specifically for the regions of interest.4 Generally speaking, hybrid-capture enrichment strategies are more efficient for enriching larger target areas (such as large gene panels or exome), whereas amplicon-based strategies can be well-suited for smaller gene panels. Additionally, hybrid-capture strategies may allow for more reliable detection of genetic alterations (such as copy number changes) and can be tailored for difficult-to-sequence regions such as those with high guanine-cytosine content. In contrast, amplicon-based sequencing assays often require less nucleic acid input and can have a shorter turnaround time.4

Various chemistries and sequencing strategies currently exist, with some being better established in clinical laboratories than others. A commonly used strategy is called “sequencing by synthesis” and involves the use of a fluorescently labeled reversible terminator associated with deoxynucleo­tides that allows base-by-base sequencing that can be captured by a high-resolution camera that also records the spatial coordinates and time. The sequence of each cluster is then determined by signal processing and base calling to generate a contiguous DNA sequence, which is known as a read.4

Data analysis begins with a number of individual bioinformatics processes applied on the raw data, and further downstream analyses can be customized based on the clinical applications needed for the data. Raw sequencing reads are first aligned to a reference genome with subsequent variant calling and other filtering steps applied, depending on the application. Once a list of variants or genomic alterations has been identified, interpretation requires expertise to determine the pathogenicity and clinical relevance of the findings.3,4

Types of NGS Approaches

NGS collectively refers to several DNA/RNA sequencing technologies that vary according to the input material, length of read, and portion of the genome to be sequenced.1,5 Broadly, the 2 major NGS technology types are short-read sequencing and long-read sequencing.1 Short-read sequencing is described as reads that are shorter than 300 bp, whereas long-read sequencing refers to reads that are longer than 2.5 Kb.1 Short-read sequencing is a relatively inexpensive option (low costs per Gb) that has a high level of accuracy. Compared with long-read sequencing, short-read sequencing is used more frequently in clinical practice for the detection of specific mutation hotspots. Moreover, based on the initial input material, different sequencing approaches may be used (ie, genomic DNA [DNA-seq], messenger or noncoding RNA [RNA-seq], or any nucleic or ribonucleic material obtained following the use of certain procedures).1,5

Current NGS approaches also differ based on the extent of target enrichment and sequencing involved, with the 3 major types being WGS, whole-exome sequencing (WES), and targeted gene panels.4 WGS refers to sequencing the entire genome, including coding and noncoding regions. It allows detection of several types of genetic aberrations, including single nucleotide variants and/or such structural alterations as insertions or deletions (also called indels), copy number variations involving duplications or deletions of long stretches of a chromosomal region, and rearrangements involving gross alterations in chromosomes or large chromosomal regions.4,5 For WGS, library preparation does not require the target enrichment or amplification steps, but because of the comprehensive nature, it does require multiple sequencing passes for adequate coverage of the whole genome, rendering it an expensive and labor-intensive option for routine clinical application.5 The issues with WGS for clinical applications are numerous—for the desired depth of sequencing, the cost is incredibly high. The list of clinically relevant genes and targets is fairly limited at this point—WGS generates an enormous amount of data for which there is no current clinical use. As turnaround times are important for clinical oncology diagnostics, the time to review the data generated from WGS is quite prohibitive, and insurance companies/payers are reticent about properly reimbursing for WGS.

In contrast, WES is not as comprehensive as WGS and involves sequencing only the coding regions of the genome, which requires a hybrid-capture enrichment step as described above.1,5 Although DNA-based WES can detect many of the alterations identified by WGS (eg, single nucleotide variants and indels), since the noncoding regions are not assayed, this approach is limited in its ability to detect rearrangements between genes with breakpoints that frequently occur in intronic regions.5 However, RNA-based whole-transcriptome approaches can be another strategy to identify gene rearrangements without previous knowledge of the fusion partners.6

The third NGS strategy, which is currently the most commonly used approach to cancer genotyping in clinical use, is targeted gene panels, which interrogate a discrete number of genes. This approach, which is a lower-cost alternative to WES and WGS, has the advantage of being able to focus on clinically relevant targets with deeper sequencer and focused analyses. Targeted gene panels can be performed with either amplicon-based or hybrid-capture enrichment strategies and can range from small, hotspot-only panels focusing on less than 50 genes to larger, more comprehensive panels that include hundreds to greater than a thousand genes with selected intronic tiling coverage. In addition to lower costs, the advantages of targeted gene panels include greater analytic sensitivity because of the greater depth of coverage, less complex data analysis and interpretation than would be necessary for WES and WGS, and greater flexibility that allows for tailoring the testing to genomic regions relevant to cancer.1,5

Clinical Utility of NGS in Oncology

Genetic Testing for Inheritable Cancers

NGS has several documented applications in a variety of clinical settings. A frequently used application for inherited cancer testing is targeted NGS panels focusing on high-penetrant/high-risk mutated genes, such as hereditary breast and ovarian cancer (HBOC) and Lynch syndrome, although at most institutions NGS panel testing is by far more frequently performed on tumor tissues, not for inherited cancer testing. In HBOC,BRCA1 and BRCA2 susceptibility genes have been well-described; however, other moderate-risk genes and low-penetrance alleles are also associated with breast cancer heritability, which can be interrogated efficiently using NGS panels as well.

An initial study using a 21-gene NGS panel for HBOC in 360 women diagnosed with ovarian, peritoneal, or fallopian tube carcinoma found that 22.8% of the patients harbored ≥1 loss-of-function mutations in 12 genes.6 Although the majority of the gene mutations were inBRCA1 (11.1%) and BRCA2 (6.4%), aberrations in 10 additional genes (6.1%) were also identified, which may confer a potential moderate to high risk for breast and ovarian cancer.7

Subsequently, Tung and colleagues sought to determine the frequency of germline mutations using a 25-gene panel in 1781 patients with breast cancer who were referred for BRCA1/2 gene testing. Overall, 9.3% of the patients were found to harbor a mutation in the BRCA1/2 genes and 4.2% carried a mutation in 14 additional genes, including PALB2, CHEK2, and ATM.8 Regarding Lynch syndrome, which is characterized by mutations in genes involved in DNA mismatch repair (MMR) that confer high penetrance for the onset of colorectal and endometrial cancer, multigene panel testing in a group of 1112 patients found mutations in 1 of the Lynch syndrome genes in 114 subjects, whereas 71 individuals carried mutations in other cancer predisposition genes.9

Detection of Driver or Resistance Mutations

Another key clinical application of NGS with broad applicability is the detection of driver mutations in different cancers. NGS has demonstrated improved diagnostic yield of identifying driver mutations that can select patients who may benefit from targeted therapy and thus predict response to treatment.5 For example, such actionable genomic alterations can be identified in the following genes: BRAF, KIT, EGFR, ERBB2, FGFR3, PIK3CA, AKT1, TSC1, ESR1, ROS1, and ALK rearrangements in different types of cancer, including non–small-cell lung cancer (NSCLC) and breast cancer.5 In a study of patients with NSCLC, following previous negative or inconclusive standard testing for actionable mutations in such specific genes as EGFR, RET, ALK, MET, and ERBB2, a broader NGS panel was able to detect actionable mutations in 14.9% of patients with advanced disease, resulting in a treatment switch in 42.6% of patients and an overall response rate of 64.7%.10

In addition to genes with current US Food and Drug Administration (FDA)-approved targeted therapies, there are other gene targets or biomarkers that may make patients eligible for enrollment in clinical trials or could guide future treatment decisions; this is the rationale for NGS panels to include several genes that are not directly related to the target mutations of interest. Although several tumor types harbor multiple, high-prevalence, and potentially actionable gene alterations, a “long tail” of gene alterations also occurs in <1% of patients, which may have potential clinical implications.5,10,11 For example, the presence of low-prevalence ERBB3 mutations in patients with metastatic breast cancer may be predictive of an objective response following the use of HER2 dual blockade therapy.12 Another example of a “long tail” gene is the presence of neurotrophic receptor tyrosine kinase (NTRK) fusions in NSCLC, which are estimated to occur in <1% of all cases. Tumors with these genomic alterations have been shown to be responsive to TRK inhibitors, and the FDA has recently approved the use of TRK inhibitor targeted therapy in advanced cancers with NTRK fusions, regardless of tumor type.13

Moreover, emerging evidence demonstrates that sequential NGS testing may allow for the detection of relevant resistance mechanisms in patients receiving targeted therapy and thus guide subsequent treatment. For example, among patients with lung cancer and secondary resistance to EGFR tyrosine kinase inhibitors (TKIs), NGS analysis identified acquisition of T790M mutations as the most common mechanism of acquired resistance to EGFR TKIs, as well as MET amplification, ERBB2 amplification, and small-cell lung carcinoma transformation.14-16 In addition, NGS-based liquid biopsy approaches at the time of the development of resistance may capture tumor heterogeneity, which could provide prognostic information, predict response to treatment, and identify resistance mechanisms. This may be a particularly suitable option if the patient has multiple sites of disease that are not amenable to obtaining a tissue biopsy.5

Single vs Complex Markers for Biomarker Testing

More recently, increasing evidence suggests that the assessment of complex biomarkers, including homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI), rather than such single biomarkers as PD-L1, may have utility for certain clinical applications. In the context of immunotherapy, a need exists for biomarkers that can predict likely therapeutic benefit, with several candidates having been identified, including PD-L1 expression, TMB, and MSI-High. PD-L1 expression status is an FDA-approved biomarker indication for immune checkpoint inhibitors, with a number of IHC-based companion diagnostic and laboratory-developed tests available for use in identifying PD-L1 expression.17

Not all patients with PD-L1 expression who meet the IHC cutoff respond to immune checkpoint inhibitors, however; patients with no PD-L1 expression may also respond to these therapies, indicating that PD-L1 expression is an imperfect biomarker and that other factors may be involved in the response of a tumor to immunotherapy.2,17 Additionally, from the standpoint of a PD-L1 assay, the lack of standardization among the commercially available PD-L1 IHC assays, including different scoring systems, test cutoffs, and cell source assayed, remains an issue.2,18

A systematic literature review that assessed scoring algorithms for PD-L1 IHC tests in patients with urothelial, lung, gastric, or ovarian cancer found significant heterogeneity among the available tests, with no definitive cutoff for PD-L1 positivity, >1 threshold defined for most anti–PD-L1 antibodies, and discordance regarding whether tumor cells and/or tumor-infiltrating immune cells had been assayed.19 Taken together, these data suggest that more robust biomarkers are needed to predict response to immunotherapy.

Mutational landscape, as determined by NGS, is a promising new biomarker in immunotherapy, since high TMB has been shown to be associated with increased sensitivity to immune checkpoint inhibitors.2 High TMB or mutational load, which refers to the total number of mutations per coding area of a tumor genome, correlates with high neoantigen levels that may elicit an immune response.2 Immune checkpoint inhibitor therapy in patients with NSCLC who have a high mutational burden has been associated with favorable treatment outcomes.20,21

Rizvi and colleagues reported that a durable clinical benefit (DCB) rate of 91% was achieved by patients with NSCLC who exhibited a high nonsynonymous mutational burden and some degree of PD-L1 tumor expression (weak/strong). In contrast, those with low mutational burden and some degree of PD-L1 expression achieved a DCB rate of only 10%.20 In this context, the feasibility of using WES for prospective clinical use was described using archival formalin-fixed, paraffin-embedded (FFPE) tumor samples.22 Recently, targeted NGS performed in 240 patients with advanced NSCLC treated with anti–PD-1 or anti–PD-L1 therapy accurately estimated TMB, which correlated with DCB.23

A subset of tumors with high mutational burden also have MMR deficiency and MSI, which involves the gain or loss of nucleotides from microsatellite tracts.24 Although MSI has long been known to be seen in Lynch syndrome–associated tumors secondary to inherited mutations in MMR genes, the prevalence of MSI as a somatic mutational signature outside the context of Lynch syndrome is increasingly being recognized in a number of tumor types, with the most common being colorectal and endometrial cancers.24

The value of MSI status for predicting response of solid tumors to the anti–PD-1 monoclonal antibody pembrolizu­mab led to its tumor-agnostic drug approval.25,26 The gold standard method for MSI detection is fragment analysis (FA) of a small number of conserved microsatellite regions by PCR.26 Feasibility is a concern, however, since FA requires samples of both tumor tissue and noncancerous tissue.24 An MSI assay that used data from an NGS panel determined MSI status across 26 cancer types without requiring matched samples from normal tissue.26 MSI-NGS, compared with MSI by PCR FA, had a sensitivity of 95.8%, a specificity of 99.4%, a positive predictive value of 94.5%, and a negative predictive value of 99.2%.26 Incorporating MSI testing into NGS panels is also a practical approach because many tumors are already being interrogated by these broader panels for the identification of other driver mutations and biomarkers.

In ovarian and breast cancers, quantification of HRD identifies patients who are particularly sensitive to platinum or poly (ADP-ribose) polymerase (PARP) inhibitor–based therapy. HRD causes genomic instability, which is reflected by genome-wide loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transitions (LST).27 Comprehensive genomic profiling based on NGS measures the genome-wide LOH, TAI, and LST.

NGS vs Traditional Orthogonal Approaches to Biomarker Analysis

As noted earlier, traditional techniques used to analyze cellular biomarkers included IHC, PCR, FISH, comparative genomic hybridization assays, microarrays, and Sanger sequencing. Compared with these traditional approaches, NGS has the advantages of high speed, high throughput, and high accuracy (Figure 2).1,3 Traditional molecular assays focus on only a relatively small panel of genomic loci that are known to harbor common aberrations (referred to as hotspots), and are not capable of providing information regarding other alterations that may be present. In contrast, NGS simultaneously characterizes many genes in the same assay, provides a broader picture of genetic heterogeneity, and allows for quantitative and sensitive detection of genomic aberrations that otherwise may not be tested.

Figure 2

The diagnostic yield for NGS is higher compared with single-gene testing, as evidenced by the results of an NGS gene panel performance analysis of 10,030 consecutive patients who were screened for inherited cancers.28 Overall, a molecular diagnosis was made in 9% of patients tested, with the highest yield in the Lynch syndrome/colorectal cancer panel. In patients with breast, ovarian, or colon/stomach cancer, positive yields were 9.7%, 13.4%, and 14.8%, respectively.28 Approximately half of the pathogenic variants identified in patients with breast or ovarian cancer were in genes other than BRCA1/2, which highlights the usefulness of multigene panels over genetic tests focusing on 1 or 2 genes. A practical consideration is that testing for such multiple modalities as IHC, FISH, and PCR is cumbersome, and requires sending samples to different laboratories, which can be eliminated with the use of an NGS-based assay. From a cost perspective, although NGS-based assays were cost-prohibitive when they were initially introduced, further refinements have made the cost more competitive with that of traditional methodologies.1 A few challenges include high complexity of workflow, informatics, and data interpretation, requiring validation of assay performance (Figure 2).

NGS Testing Landscape

The NGS testing landscape is expanding rapidly, which may be attributable largely to technologic advancements in sequencing platforms, increased clinical utility, and reduced cost of sequencing. Several NGS-based diagnostics are commercially available, which demonstrate variability in terms of the genes that are involved and the number of genes that are included.

The FDA authorized the first comprehensive NGS diagnostic assay for the detection of actionable genomic aberrations in cancer—called MSK-IMPACT™—which uses a 468-gene NGS panel developed at the Memorial Sloan Kettering Cancer Center.29 Foundation Medicine’s FoundationOne CDx™ (F1CDx™) was subsequently approved. F1CDx serves as a companion diagnostic for 15 different targeted therapies used to treat 5 types of cancer and is also able to detect genomic signatures, including MSI and TMB, as well as substitutions, indels, and copy number alterations, in 324 genes and select gene rearrangements with the use of DNA isolated from FFPE tumor tissue specimens.30 Myriad Genetics offers the myChoice® HRD, which guides PARP inhibitor treatment decisions by testing for BRCA1/2 status and HRD status.31 The myRisk® Hereditary Cancer 29-gene NGS panel, also by Myriad Genetics, identifies an elevated risk for 8 different types of cancer, including melanoma, breast, ovarian, endometrial, colon, prostate, gastric, and pancreatic cancers.31

Future Perspectives for NGS Testing

Major advancements have occurred in NGS technology, with multiple clinical applications described in the oncology arena. In addition to identifying driver mutations that may be clinically actionable with targeted therapy, NGS may have utility for detecting resistance mechanisms, recognizing prognostic and predictive biomarkers, and assessing tumoral heterogeneity.

Several challenges remain, however, which serve as barriers to NGS testing in clinical practice. Compared with many traditional laboratory methods, NGS testing is a complex process that is predicated on procurement of adequate amounts and appropriately preserved tumor samples, with complex laboratory and analytical processes that can result in long turnaround times. The increase in the number of genes included in NGS panels may be associated with more technical issues, including panel validation, quality assessment, and quality control, as well as such clinical issues as management of variants of uncertain significance and comprehensive analysis of the network of mutations.32 In the future, it is hoped that increased computational ability and improved bioinformatics algorithms will enhance the speed and precision of NGS, whereas larger databases may provide insight into the variants identified and functional data may improve data interpretation.32

Moreover, although tumor tissue remains the gold standard for molecular diagnostic analysis, procuring adequate tissue may be difficult in certain instances, with the invasive nature of biopsies posing risks and significant discomfort to patients.2,5 Furthermore, since tumor tissue obtained from a biopsy represents only a single tumor site, it may not reflect intratumoral heterogeneity within a primary tumor or between metastatic sites.5 Thus, other sources of tumor cells are being evaluated for sequencing, including circulating tumor cells and circulating cell-free tumor DNA, which is referred to as liquid biopsy.5 Although this strategy for obtaining cell-free DNA allows for repeated sampling by noninvasive blood draws and monitoring of tumor evolution over time and treatment, it can be technically challenging.2,5

As NGS is increasingly being adopted into routine clinical practice, particularly for tumor types such as NSCLC, it is evidence that NGS platforms hold great promise as multiapplication tools in oncology, and their utility will only further grow with our advancing knowledge of cancer genomics and the clinical utility of biomarkers that we can generate from this technology.

References

  1. Kamps R, Brandão RD, van den Bosch BJ, et al. Next-generation sequencing in oncology: genetic diagnosis, risk prediction and cancer classification. Int J Mol Sci. 2017;18:308.
  2. Groisberg R, Maymani H, Subbiah V. Immunotherapy and next-generation sequencing guided therapy for precision oncology: what have we learnt and what does the future hold? Expert Rev Precis Med Drug Dev. 2018;3:205-213.
  3. Yohe S, Thyagarajan B. Review of clinical next-generation sequencing. Arch Pathol Lab Med. 2017;141:1544-1557.
  4. Gagan J, Van Allen EM. Next-generation sequencing to guide cancer therapy. Genome Med. 2015;7:80.
  5. Cummings CA, Peters E, Lacroix L, et al. The role of next-generation sequencing in enabling personalized oncology therapy. Clin Transl Sci. 2016;9:283-292.
  6. Maher CA, Kumar-Sinha C, Cao X, et al. Transcriptome sequencing to detect gene fusions in cancer. Nature. 2009;458:97-101.
  7. Walsh T, Casadei S, Lee MK, et al. Mutations in 12 genes for inherited ovarian, fallopian tube, and peritoneal carcinoma identified by massively parallel sequencing. Proc Natl Acad Sci U S A. 2011;108:18032-18037.
  8. Tung N, Battelli C, Allen B, et al. Frequency of mutations in individuals with breast cancer referred forBRCA1 and BRCA2 testing using next-generation sequencing with a 25-gene panel. Cancer. 2015;121:25-33.
  9. Yurgelun MB, Allen B, Kaldate RR, et al. Identification of a variety of mutations in cancer predisposition genes in patients with suspected Lynch syndrome. Gastroenterology. 2015;149:604-613.e20.
  10. Rozenblum AB, Ilouze M, Dudnik E, et al. Clinical impact of hybrid capture-based next-generation sequencing on changes in treatment decisions in lung cancer. J Thorac Oncol. 2017;12:258-268.
  11. Lawrence MS, Stojanov P, Mermel CH, et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature. 2014;505:495-501.
  12. Bidard F-C, Ng CKY, Cottu P, et al. Response to dual HER2 blockade in a patient with HER3-mutant metastatic breast cancer. Ann Oncol. 2015;26:1704-1709.
  13. 13. Farago AF, Taylor MS, Doebele RC, et al. Clinicopathologic features of non-small-cell lung cancer harboring an NTRK gene fusion. JCO Precis Oncol. 2018 Jul 23. Epub ahead of print.
  14. Lee CK, Kim S, Lee JS, et al. Next-generation sequencing reveals novel resistance mechanisms and molecular heterogeneity in EGFR-mutant non-small cell lung cancer with acquired resistance to EGFR-TKIs. Lung Cancer. 2017;113:106-114.
  15. Piotrowska Z, Sequist LV. Treatment of EGFR-mutant lung cancers after progression in patients receiving first-line EGFR tyrosine kinase inhibitors: a review. JAMA Oncol. 2016;2:948-954.
  16. Morgillo F, Della Corte CM, Fasano M, et al. Mechanisms of resistance to EGFR-targeted drugs: lung cancer. ESMO Open. 2016;1:e000060. eCollection 2016.
  17. Diggs LP, Hseuh EC. Utility of PD-L1 immunohistochemistry assays for predicting PD-1/PD-L1 inhibitor response. Biomark Res. 2017;5:12.
  18. Bernicker E. Next-generation sequencing and immunotherapy biomarkers: a medical oncology perspective. Arch Pathol Lab Med. 2016;140:245-248.
  19. Udall M, Rizzo M, Kenny J, et al. PD-L1 diagnostic tests: a systematic literature review of scoring algorithms and test-validation metrics. Diagn Pathol. 2018;13:12.
  20. Rizvi NA, Hellmann MD, Snyder A, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer. Science. 2015;348:124-128.
  21. McGranahan N, Furness AJ, Rosenthal R, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351:1463-1469.
  22. Van Allen EM, Wagle N, Stojanov P, et al. Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine. Nat Med. 2014;20:682-688.
  23. Rizvi H, Sanchez-Vega F, La K, et al. Molecular determinants of response to anti–programmed cell death (PD)-1 and anti–programmed death-ligand 1 (PD-L1) blockade in patients with non–small-cell lung cancer profiled with targeted next-generation sequencing. J Clin Oncol. 2018;36:633-641.
  24. de la Chapelle A, Hampel H. Clinical relevance of microsatellite instability in colorectal cancer. J Clin Oncol. 2010;28:3380-3387.
  25. US Food and Drug Administration (FDA). FDA News Release. FDA approves first cancer treatment for any solid tumor with a specific genetic feature. www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm560167.htm. Accessed January 21, 2019.
  26. Vanderwalde A, Spetzler D, Xiao N, et al. Microsatellite instability status determined by next-generation sequencing and compared with PD-L1 and tumor mutational burden in 11,348 patients. Cancer Med. 2018;7:746-756.
  27. Frey MK, Pothuri B. Homologous recombination deficiency (HRD) testing in ovarian cancer clinical practice: a review of the literature. Gynecol Oncol Res Pract. 2017;4:4.
  28. Susswein LR, Marshall ML, Nusbaum R, et al. Pathogenic and likely pathogenic variant prevalence among the first 10,000 patients referred for next-generation cancer panel testing. Genet Med. 2016;18:823-832.
  29. Memorial Sloan Kettering Cancer Center. Pressroom/Press Releases. MSK-IMPACT™ is the first tumor-profiling multiplex panel authorized by the FDA, setting a new pathway to market for future oncopanels. November 15, 2017. www.mskcc.org/press-releases/msk-impact-first-tumor-profiling-multiplex-panel- authorized-fda-setting-new-pathway-market-future-oncopanels. Accessed January 21, 2019.
  30. Foundation Medicine. www.foundationmedicine.com/genomic-testing. Accessed January 21, 2019.
  31. Myriad Genetics. https://myriad.com/products-services/all-products/overview/. Accessed January 21, 2019.
  32. Garinet S, Laurent-Puig P, Blons H, Oudart J-B. Current and future molecular testing in NSCLC, what can we expect from new sequencing technologies? J Clin Med. 2018;7(6).
Last modified: March 18, 2019

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