You are here

Clinical Impact of Hybrid Capture–Based Next-Generation Sequencing on Changes in Treatment Decisions in Lung Cancer

Journal of Thoracic Oncology, Volume 12, Issue 2, February 2017, Pages 258 - 268

Abstract

Introduction

Targeted therapy significantly prolongs survival in lung adenocarcinoma. Current diagnostic guidelines include only EGFR and anaplastic lymphoma receptor tyrosine kinase gene (ALK) testing. Next-generation sequencing (NGS) reveals more actionable genomic alterations than do standard diagnostic methods. Data on the influence of hybrid capture (HC)-based NGS on treatment are limited, and we investigated its impact on treatment decisions and clinical outcomes.

Methods

This retrospective study included patients with advanced lung cancer on whom HC-based NGS was performed between November 2011 and October 2015. Demographic and clinicopathologic characteristics, treatments, and outcome data were collected.

Results

A total of 101 patients were included (median age 63 years [53% females, 45% never-smokers, and 85% with adenocarcinoma]). HC-based NGS was performed upfront and after EGFR/ALK testing yielded negative or inconclusive results in 15% and 85% of patients, respectively. In 51.5% of patients, HC-based NGS was performed before first-line therapy, and in 48.5%, it was performed after treatment failure. HC-based NGS identified clinically actionable genomic alterations in 50% of patients, most frequently in EGFR (18%), Ret proto-oncogene (RET) (9%), ALK (8%), Mesenchymal-epithelial transition factor (MET) receptor tyrosine kinase gene (6%), and erb-b2 receptor tyrosine kinase 2 gene (ERBB2) (5%). In 15 patients, it identified EGFR/ALK aberrations after negative results of prior standard testing. Treatment strategy was changed for 43 patients (42.6%). The overall response rate in these patients was 65% (complete response 14.7%, partial response 50%). Median survival was not reached. Immunotherapy was administered in 33 patients, mostly without an actionable driver, with a presenting disease control rate of 32%, and with an association with tumor mutation burden.

Conclusions

HC-based NGS influenced treatment decisions in close to half of the patients with lung adenocarcinoma and was associated with an overall response rate of 65%, which may translate into a survival benefit.

Keywords: Driver mutations, Next-generation sequencing, Oncogenic drivers, Precision/personalized medicine, Targeted therapy, Immunotherapy.

Introduction

NSCLC tumors are highly genetically diverse and present a treatment challenge.1 Until a decade ago, systemic treatment for advanced lung cancer focused primarily on platinum-based doublets.2 In 2002, the concept of “oncogene addiction” was introduced by Weinstein et al.,3 and since then important advances in understanding lung cancer cellular signal pathways have been made, leading to the development of multiple targeted drugs.

The new treatment paradigm in lung cancer focuses on personalizing treatment on the basis of tumor molecular properties, specifically, on targeting driver genomic alterations (GAs).4, 5, 6, 7, 8, and 9 Tumor genotyping allows detection of oncogenic drivers in approximately 60% of patients with lung adenocarcinoma, and using the appropriate targeted treatment has a significant impact on survival.10, 11, and 12 The most frequently altered genes are KRAS, EGFR, and anaplastic lymphoma receptor tyrosine kinase gene (ALK), which are detected in 15% to 25%, 10% to 35%, and 3% to 7% of patients, respectively.13, 14, 15, and 16 At present, the KRAS driver cannot be effectively targeted; thus, the current treatment strategy focuses on targeting GAs in the EGFR and ALK genes. However, current typical technologies for identifying GAs (i.e., polymerase chain reaction [PCR], immunohistochemistry, and fluorescence in situ hybridization [FISH]) cannot identify all druggable alterations in EGFR exons and/or introns or variants of ALK rearrangement.5, 7, 10, 11, and 12 Other targets that are not routinely tested in lung adenocarcinoma include ret proto-oncogine (RET) (1%), ROS1 (1%), Mesenchymal-epithelial transition factor (MET) receptor tyrosine kinase gene (2%), and erb-b2 receptor tyrosine kinase 2 gene (ERBB2) (2%).13

Massive parallel sequencing (i.e., next-generation sequencing [NGS]), is a new platform that allows detection of numerous GAs in tens to hundreds of genes simultaneously, as well as detection of rare somatic mutations. One NGS approach uses PCR amplification of candidate regions followed by NGS (amplicon sequencing) and offers sequencing of a narrow gene spectrum, focusing on point mutations in several hotspot regions. Other, more comprehensive methods such as hybrid capture (HC)-based NGS offer broad gene sequencing and provide extensive genetic information regarding the broad aberration repertoire, including information on exon and intron mutations, gene rearrangements, amplifications, etc.

Clinical utilization of NGS began in 2011. Since then, NGS assays have improved considerably, with respect to the bioinformatics involved, as well as with respect to translational/clinical implementation.17 A study from 2013 investigated the genetic repertoire of 2221 clinical specimens by using HC-based NGS and detected actionable GAs in 76% of tumors, which is three times the number detected by traditional diagnostic tests.18

NGS is also applicable to liquid biopsies, a novel strategy for cancer diagnosis. Since circulating tumor cell-free DNA (cfDNA) was discovered by Stroun et al. in 1987,19 numerous technologies have been developed to detect and use these genetic materials as an alternative to invasive tissue biopsy.20, 21, and 22 Notably, cfDNA may mirror in real time the spatial genomic repertoire of the tumor in contrast to pathologic specimens that reflect the genomic status at the time of biopsy.

Although HC-based NGS allows elaborate molecular characterization of the tumor, many of the GAs are not druggable (i.e., without an associated therapy that is approved and commercially available). The cost of HC-based NGS, as well as treatment reimbursement issues, should be considered. Therefore, the role of HC-based NGS in disease management is unclear. Here, we assessed the contribution of HC-based NGS to clinical decision making and clinical outcomes in real-life clinical practice while also considering other diagnostic tests carried out according to physicians' decisions.

Materials and Methods

Patients

This retrospective cohort study included 101 sequential patients with advanced lung cancer who were treated at the Davidoff Cancer Center at Rabin Medical Center (Petah Tikva, Israel) between November 2011 and October 2015 and underwent HC-based NGS with broad gene panels. HC-based NGS was performed upon the recommendation of the treating physician, mostly on the basis of young age and smoking history. The results of standard molecular testing for EGFR mutations and ALK rearrangements (using validated and approved diagnostic kits) were negative before HC-based NGS in 80.2% (81 of 101) and 70.3% (71 of 101) of the patients, respectively. Upfront HC-based NGS was performed on 15 patients because of very little biopsy material. Blood-based cfDNA analysis served as a salvage method for gene analysis in cases of tissue exhaustion. The study was approved by the ethical committee of Rabin Medical Center (approval no. 0391-14 RMC). The clinicopathologic data were collected from patients' medical and electronic charts.

HC-Based NGS Cancer Gene Tests

HC-based NGS was performed off-site on tumor samples with FoundationOne (Foundation Medicine, Inc., Cambridge, MA)18 or on blood samples using a liquid biopsy approach with Guardant360 (Guardant Health Inc., Redwood City, CA) if the tissue sample had been exhausted.20 (For extended information on these HC-based NGS technologies, see the Supplementary Data). Both assays were paid either out of pocket or by private insurance coverage. An effort was made to financially assist patients who could not fund tests.

Standard Molecular Pathology Tests

EGFR mutations were assessed with real-time PCR or narrow-spectrum NGS assays (amplicon-based hotspot NGS). ALK rearrangements were assessed with immunohistochemistry and/or FISH (for extended information on these methods, see the Supplementary Data).

Gene Analysis

This study focused on GAs with potential clinical relevance. Initial analysis (level 1) included GAs associated with U.S. Food and Drug Administration–approved anticancer therapies (including off-label drugs) for all cancer types. A subsequent analysis (level 2) included GAs with appropriate evidence-based targeted agents with antidriver activity in lung cancer, as recommended by the National Comprehensive Cancer Network (NCCN) guidelines for NSCLC.23 GAs associated with investigational treatments were not included in the current analysis, although one patient went on to participate in a driver-based clinical trial.

Results

Patient Characteristics

The analysis included 101 patients with advanced lung cancer. Patient characteristics are summarized in Table 1. Patients' median age at diagnosis was 63 years (range 20–84), 94% of patients had their lung cancer diagnosed at stage III to IV, 53% were women, 45% were never-smokers, and 85% had adenocarcinoma. Routine molecular analysis for EGFR mutations and ALK rearrangement was performed in 86 and 72 patients, respectively. In general, no alterations were detected except in five cases of inconclusive EGFR alterations and one case of inconclusive ALK rearrangement. In 15 patients (14.9%), HC-based NGS testing was performed before routine molecular testing. In 52 patients (51.5%), HC-based NGS was performed before initiation of first-line therapy, and in 49 (48.5%) it was performed after treatment failure.

Table 1

Patient, Tumor, and Molecular Testing Characteristics

 

Characteristics of the Study Population (N = 101) Numerical Value
Sex, n (%)
 Female 54 (53.5)
 Male 47 (46.5)
Age at diagnosis, y
 Median (range) 63 (20–84)
Stage at diagnosis, n (%)
 IV 79 (78.2)
 III (A/B) 16 (15.8)
 I (A/B) or II (A/B) 6 (5.9)
Cigarette smoking status, n (%)
 Never 45 (44.6)
 Ever 53 (52.5)
 Average pack-years 38
 Unknown 3 (3.0)
Histopathologic type, n (%)
 Adenocarcinoma 86 (85.1)
 Other 15 (14.9)
Source of sample for HC-based NGS analysis, n (%)
 Tumor sample (solid tissue) 82 (81.2)
 Blood circulating cell-free DNA 19 (18.8)
Prior testing using standard molecular methods,a n (%)
EGFR 86 (85.2)
ALK 72 (71.3)
Timing of HC-based NGS testing, n (%)
 Before first-line therapy 52 (51.5)
 After treatment failure 49 (48.5)

a The results of testing of all patients were found to be negative except in five cases in which they were inconclusive for EGFR mutation and in one case in which they were inconclusive for ALK rearrangement.

ALK, anaplastic lymphoma receptor tyrosine kinase gene; HC, hybrid capture; NGS, next-generation sequencing.

Genomic Findings

Tissue HC-based NGS was performed in 82 patients (81.2%) and liquid HC-based NGS was performed in 19 (18.8%). For the tissue assay, biopsy specimens were obtained from the lungs of 40 patients and from metastases of 42 patients. At level 1 analysis, at least one actionable GA was detected in 84 patients (83.2%), including in 73 of the 82 patients with tissue HC-based NGS (89.0%), and in 11 of the 19 patients with liquid HC-based NGS (57.9%). Overall, in 23 patients (22.8%) HC-based NGS detected two actionable GAs, and in six patients (5.9%) it detected three or more actionable GAs. At level 2 analysis, actionable driver GAs were identified in 50 patients (49.5%). The most common genes with mutational or structural change (level 1) involved in the 121 GAs detected in 101 patients were KRAS (18.2%), EGFR (16.5%), RET (7.4%), serine/threonine kinase 11 gene (STK11) (7.4%), ALK (6.6%), ERBB2 (5.8%), and MET (5.8%). At level 2 analysis (Table 2), the most common actionable GAs in 101 patients were sensitizing EGFR mutations (15%), RET rearrangements (9%), ALK rearrangements (8%), and MET amplifications and/or exon 14 mutations (6%). The proportion of level 2 actionable GAs detected in patients who underwent HC-based NGS before first-line therapy (n = 52) was 54% and that detected in patients who underwent HC-based NGS after treatment failure 47% (n = 49). Interestingly, in 15 patients (14.9%), HC-based NGS detected a GA in EGFR or ALK after negative results of standard molecular testing. Moreover, four additional cases were identified as EGFR/ALK positive by previous standard methods, whereas different drivers were eventually identified by HC-based NGS. The possible reasons for these findings are discussed in the Discussion section.

Table 2

Prevalence of Genomic Drivers and Impact on Treatment Decision

 

Characteristic n (%) Pts Receiving Targeted Therapy Based on Tissue HC-Based NGS, n (%) Pts Receiving Targeted Therapy Based on Liquid HC-Based NGS, n (%) Total Pts Receiving Targeted Therapy, n (%) Treated Pts Evaluable for Tumor Response Who Had an Objective Response, n (% ORR) Median Duration of Targeted Treatment, wk (Range) Pts with Ongoing Targeted Therapy, n (%)
Study population 101 (100) 37 of 82 (45) 6 of 19 (32) 43 of 101 (43) 22 of 34a (65) 26 (1–227) 14 of 43 (33)
 No drivers with FDA-approved treatments 17 (17) 1 of 9 (11) 0 of 8 (0) 1 of 17 (6) 1 of 1 (100) 34 (34) 0 of 1 (0)
 Any driver with FDA-approved treatment 84 (83) 36 of 73 (49) 6 of 11 (55) 42 of 84 (50) 21 of 33 (64) 26 (1–227) 14 of 42 (33)
 No NCCN-recommended drivers 34 (34) 5 of 30 (17) 0 of 4 (0) 5 of 34 (15) 0 of 2 (0) 6 (4–26) 0 of 5 (0)
 Any NCCN-recommended driver 50 (50) 31 of 43 (72) 6 of 7 (86) 37 of 50 (74) 21 of 31 (68) 30 (1–227) 14 of 37 (38)
EGFR sensitizingb 15 (15) 9 of 13 (69) 2 of 2 (100) 11 of 15 (73) 9 of 10 (90) 63 (22–124) 6 of 11 (55)
 Exon19 del 6 (6) 3 of 5 (60) 1 of 1 (100) 4 of 6 (67) 4 of 4 (100) 78 (47–124) 3 of 4 (75)
 L858R 5 (5) 3 of 4 (75) 1 of 1 (100) 4 of 5 (80) 4 of 4 (100) 63 (27–115) 1 of 4 (25)
 Otherc 7 (7) 4 of 6 (67) 1 of 1 (100) 5 of 7 (71) 3 of 4 (75) 47 (22–115) 4 of 5 (80)
RET rearrangement 9 (9) 4 of 7 (57) 2 of 2 (100) 6 of 9 (67) 1 of 4 (25) 11 (2–30) 1 of 6 (17)
KIF5B-RET rearrangement 7 (7) 4 of 6 (67) 1 of 1 (100) 5 of 7 (71) 1 of 4 (25) 13 (4–30) 0 of 5 (0)
CCDC6-RET rearrangement 1 (1) 0 of 0 (0) 1 of 1 (100) 1 of 1 (100) NA 2 (2) 1 of 1 (100)
PICALM-RET rearrangement 1 (1) 0 of 1 (0) 0 of 0 (0) 0 of 1 (0)
ALK rearrangement 8 (8) 7 of 8 (88) 0 of 0 (0) 7 of 8 (88) 5 of 6 (83) 93 (14–227) 4 of 7 (57)
EML4-ALK rearrangement 6 (6) 5 of 6 (86) 0 of 0 (0) 5 of 6 (83) 3 of 4 (75) 32 (14–139) 2 of 5 (40)
 Intron 19 rearrangement 2 (2) 2 of 2 (100) 0 of 0 (0) 2 of 2 (100) 2 of 2 (100) 160 (93–227) 2 of 2 (100)
MET amplification and/or exon 14 mutation 6 (6) 3 of 4 (75) 1 of 2 (50) 4 of 6 (67) 3 of 4 (75) 20 (13–32) 1 of 4 (25)
ERBB2 mutation 5 (5) 4 of 4 (100) 1 of 1 (100) 5 of 5 (100) 1 of 4 (25) 10 (1–58) 1 of 5 (20)
EGFR (nonsensitizing) 3 (3) 1 of 3 (33) 0 of 0 (100) 1 of 3 (33) 0 of 1 (0) 12 (12) 0 of 1 (0)
ROS1 rearrangement 3 (3) 2 of 3 (67) 0 of 0 (100) 2 of 3 (67) 2 of 2 (100) 97 (97) 1 of 2 (50)
CD74-ROS1 rearrangement 1 (1) 1 of 1 (100) 0 of 0 (100) 1 of 1 (100) 1 of 1 (100) 97 (97) 1 of 1 (100)
MYH9-ROS1 rearrangement 1 (1) 1 of 1 (100) 0 of 0 (100) 1 of 1 (100) 1 of 1 (100) NA 0 of 1 (0)
SDC4-ROS1 rearrangement 1 (1) 0 of 1 (0) 0 of 0 (100) 0 of 1 (0)
BRAF V600E mutation 1 (1) 1 of 1 (100) 0 of 0 (100) 1 of 1 (100) NA 2 (2) 0 of 1 (0)

a The ORR in patients previously tested for EGFR/ALK who are evaluable for tumor response is 62% (18 of 29).

b The sum of counts for the three EGFR categories differs from the head count of total EGFR sensitizing mutations because of three patients each harboring two EGFR mutations from different EGFR categories. For full details, please refer to Supplementary Table 1.

c Two patients who were each harboring two mutations of this category were counted by number of patients (n = 2).

Note: Of 43 patients treated with targeted therapy on the basis of the results of HC-based NGS, 37 were harboring NCCN-recommended drivers for lung cancer. The other six were treated on the basis of other genomic alterations: NF1 mutation, a high-volume EGFR amplification, KRAS mutation, an NTRK1 variant of unknown significance other than exon 14–activating MET mutation, and a MET variant of unknown significance.

Pts, patients; HC, hybrid capture; NGS, next-generation sequencing; ORR, objective response rate; FDA, U.S. Food and Drug Administration; NCCN, National Comprehensive Cancer Network; del, deletion; RET, ret proto-oncogene; KIF5B, kinesin family member 5B gene; CCDC6, coiled-coil domain containing 6 gene; NA, not available; PICALM, phosphatidylinositol binding clathrin assembly protein gene; ALK, anaplastic lymphoma receptor tyrosine kinase gene; EML4, echinoderm microtubule associated protein like 4 gene; MET, Mesenchymal-epithelial transition factor receptor tyrosine kinase gene; ERBB2, erb-b2 receptor tyrosine kinase 2 gene; CD74, CD74 molecule gene; MYH9, myosin heavy chain 9 gene; SDC4, syndecan 4 gene; NF1, neurofibromic 1; NTKR1, neurotrophic tyrosine kinase, receptor, type 1 gene.

HC-Based NGS and Changes in Treatment Decisions

After HC-based NGS, 43 patients (42.6%) received targeted therapies accordingly (see Table 2). Of these 43 patients, six were excluded from the decision impact analysis as they elected to undergo HC-based NGS before standard EGFR/ALK testing and their HC-based NGS assays detected EGFR/ALK GAs that could have been identified by standard testing. Thus, the calculated exclusive impact of post-PCR/FISH HC-based NGS testing was 36.6%, representing 37 of 101 patients with drivers that could not have been detected otherwise. In 19% of patients (seven of 37), targeted therapy was administered with a concurrent drug (e.g., erb-b2 receptor tyrosine kinase 2 tyrosine kinase inhibitors (TKIs) with chemotherapy [see Supplementary Table 1]). Tissue HC-based NGS had an impact rate of 45.1% (37 of 82 patients), and liquid HC-based NGS had an impact rate of 31.6% (six of 19). In addition to the 43 patients who received targeted therapy, two were prescribed targeted therapy but died before initiation of the treatment and two more died shortly before receiving the HC-based NGS report indicating a possible targeted therapy. Of the 43 patients treated with targeted therapy after HC-based NGS, 56% underwent HC-based NGS before first-line therapy and 44% underwent it after treatment failure.

Twelve patients had EGFR mutations and were treated with EGFR TKIs. Another 13 patients were treated with crizotinib: seven had alterations in the ALK gene, four had exon 14 mutations or amplifications in the MET gene, and two had ROS1 rearrangements. Six patients were treated for RET rearrangements with cabozantinib (n = 5) or alectinib (n = 1). Five patients had ERBB2 mutations and were treated with erb-b2 receptor tyrosine kinase 2 TKIs (trastuzumab, trastuzumab emtansine, or pertuzumab). One patient was treated with vemurafenib because of a V600E mutation in the BRAF gene. Another six patients were treated for GAs that were not considered druggable: a neurofibromin 1 gene (NF1) mutation (treated with everolimus), a high-volume EGFR amplification (×17, erlotinib), non–exon 14 MET mutation of an activating nature (crizotinib), MET (exon 13, E999K) and NTRK1 (S396L) variants of unknown significance (crizotinib), and a KRAS mutation. The patient with the KRAS mutation was enrolled in the SELECT-1 trial and received selumetinib (or placebo) together with docetaxel. This patient was omitted from the response analysis because the nature of the administered treatment was unknown. A full description of the treated patients and the administered drugs is provided in Supplementary Table 1. Of the 43 patients who were treated with targeted therapy, the 19 with ALK/EGFR alterations had their treatment reimbursed by the National Health Insurance Law. Another 23 patients received targeted treatment under off-label use and paid for it individually, were assisted through donations from pharmaceutical companies, or received reimbursement from private insurance companies. As already mentioned, one patient participated in a clinical trial.

Time to Treatment and HC-Based NGS

Median turnaround time for HC-based NGS, excluding shipment time, was 13 days (range 8–460), and treatment started a median of 8 days after receipt of the report (range 0–364). First-line treatment was started within a median of 44 days from diagnosis (range 32–48) in the group of patients who underwent HC-based NGS before their first-line treatment and within a median of 39 days (range 12–122) in the group that underwent HC-based NGS after first-line treatment. The difference between the two groups was found to be not significant (t test p = 0.202). In the latter group, the median time between initiation of first-line treatment and HC-based NGS was 169 days (range 22–1612).

Response to Targeted Therapy and Treatment Duration

Best response to targeted therapy after HC-based NGS, as measured using the Response Evaluation Criteria in Solid Tumors, is summarized in Table 2 and Figure 1. Of the 43 patients treated upon receipt of the results of HC-based NGS, 34 were evaluable for tumor response. The overall response rate was 64.7% (62% if excluding patients not previously tested). Five patients (14.7%) experienced a systemic complete response (CR); 17 (50%) experienced a partial response (PR), three of whom achieved a metabolic CR; nine (26.5%) experienced stable disease; and three (8.8%) experienced progressive disease. For 13 patients, tumor response evaluation was also available for previous lines of therapy before targeted treatment (Fig. 2). In these cases, targeted therapy achieved better disease control than did previous lines (77% versus 54%, respectively). Among the 15 patients in whom HC-based NGS detected a GA in EGFR or ALK after negative results of standard molecular testing, 12 were treated with targeted therapies, and CR or PR was reported in eight (67%). Duration of targeted treatment ranged from 1 to 227 weeks at time of analysis (Fig. 3). Median survival was not reached at the time of analysis; 21 of 43 patients treated with targeted therapy were still alive, with a mean follow-up from diagnosis of stage IV disease of 18 months (range 1–58 months).

gr1

Figure 1

Percentage of best response in 34 patients who received targeted therapy according to hybrid capture (HC)-based next-generation sequencing (NGS) results. Each bar represents one patient. Number of previous lines and genomic information guiding the targeted therapy in each case are elaborated. Nine of 43 patients not evaluable for tumor response at the time of tumor response were omitted. *Nonsensitizing EGFR mutation. NTRK1, neurotrophic tyrosine kinase receptor type 1 gene; VUS, variant of unknown sequence; ERBB2, erb-b2 receptor tyrosine kinase 2 gene; RET, ret proto-oncogene; MET, Mesenchymal-epithelial transition factor receptor tyrosine kinase gene; NF1, neurofibromin 1 gene; ALK, anaplastic lymphoma receptor tyrosine kinase gene.

 

gr2

Figure 2

Percentage of best response for 13 patients in previous treatment lines versus in targeted therapy. Of 43 patients treated with targeted therapy after hybrid capture–based next-generation sequencing results, 23 had previous lines of treatment and 13 were evaluable for tumor response. Each vertical section represents one patient, encompassing one or two previous lines of treatment. Patient number and genomic information guiding the targeted therapy in each case is elaborated. The results of standard testing of all patients for EGFR/ALK alterations before hybrid capture–based next-generation sequencing were negative. ALK, anaplastic lymphoma receptor tyrosine kinase gene; ERBB2, erb-b2 receptor tyrosine kinase 2 gene; MET, Mesenchymal-epithelial transition factor receptor tyrosine kinase gene; NTRK1, neurotrophic tyrosine kinase receptor type 1 gene; RET, ret proto-oncogene; PLD, platinum doublet; PLT, platinum triplet (i.e., platinum doublet with bevacizumab); Peme., pemetrexed; Nivo., Nivolumab; Tra., trastuzumab; Per., pertuzumab; Vin., vinorelbine; Pac., paclitaxel; TDM1, trastuzumab emtansine, NA, not available.

 

gr3

Figure 3

Treatment duration with targeted therapy for hybrid capture (HC)-based next-generation sequencing (NGS)-identified drivers (weeks). Of 43 patients treated with targeted therapy after receipt of HC-based NGS results, 41 had available data on duration of targeted treatment. Each bar represents one patient, and the number of weeks of treatment is stated to the right of the bar. If initial targeted therapy was immediately followed by another targeted therapy addressing the same gene, the duration was measured as a whole for the sum of the durations of the treatment. *Other than exon 14 activating MET mutation. **Nonsensitizing EGFR mutation. ***EGFR high-volume amplification (×17). ALK, anaplastic lymphoma receptor tyrosine kinase gene; ERBB2, erb-b2 receptor tyrosine kinase 2 gene; MET, Mesenchymal-epithelial transition factor receptor tyrosine kinase gene; VUS, variation of unknown sequence; NTRK1, neurotrophic tyrosine kinase receptor type 1 gene; RET, ret proto-oncogene; NF1, neurofibromin 1 gene.

 

TMB and Response to Immunotherapy

During the study period, 33 patients received immunotherapy (either nivolumab [n = 20] or pembrolizumab [n = 13]), 13 of whom were carrying a KRAS mutation. Disease control rate for the whole group was 32% (eight of 25 patients evaluable for tumor response). Data on tumor mutation burden (TMB) was available for 80 patients on whom tissue HC-based NGS was performed. Patients who were identified by HC-based NGS as not carrying any treatment-associated driver (n = 17) (level 1 analysis) had the highest mean TMB (11.8 ± 5 mutations/MB]) and the highest overall response rate to immunotherapy (33%). Among KRAS mutation carriers, the average TMB was 6.7 ± 4, and the immunotherapy objective response rate was 10%. As demonstrated by Rizvi et al.,24 our results also showed that a higher TMB was associated, although not significantly, with improved objective response to immunotherapy, with a mean TMB of 9.6 ± 0.8 in patients with a PR as compared with a mean TMB of 5.8 ± 5 in patients with stable or progressive disease (p = 0.27). Immunotherapy response rates according to driver type and TMB data are listed in Table 3.

Table 3

Best Response in 33 Patients Treated with Immunotherapy

 

Characteristic Average TMB mut/MBa Pts Treated with Immunotherapy, n (%) Treated Pts Evaluable for Tumor Response Who Had an Objective Response, n (% ORR) Disease Control Rate (Treated Pts Evaluable for Tumor Response Whose Disease Was Controlled), n (%) Median Treatment Duration (Range) wk Pts with Ongoing Therapy, n (%)
Total 7.1 ± 7.0 33 of 101 (33) 3 of 25 (12) 8 of 25 (32) 15 (1–31) 6 of 33 (18)
No level 1 drivers (with FDA-approved treatments) 11.8 ± 5.1 6 of 17 (35) 2 of 6 (33) 4 of 6 (67) 19 (1–30) 3 of 6 (50)
No level 2 drivers (NCCN-recommended) 9.8 ± 8.2 27 of 51 (53) 3 of 21 (14) 8 of 21 (38) 16 (1–31) 6 of 27 (22)
KRAS muts only, amps excluded 6.7 ± 4.1 13b of 22 (59) 1 of 10 (10) 4 of 10 (40) 15 (1–31) 1 of 13 (8)
BRAF all muts 6.7 ± 5.9 0 of 2 (0)
EGFR sensitizing and other muts, amps excluded 6.1 ± 6.6 1 of 18 (6) NA NA 2 (2) 0 of 0 (0)
ROS1 5.0 ± 5.6 0 of 3 (0)
MET, including all types of known muts and amps 4.5 ± 2.8 0 of 7 (0)
ERBB2 muts only, amps excluded 3.8 ± 1.2 2 of 5 (40) 0 of 1 (0) 0 of 1 (0) NA 0 of 0 (0)
RET 3.5 ± 3.6 4b of 9 (44) 0 of 4 (0) 1 of 4 (25) 11 (1–26) 0 of 0 (0)
ALK 3.3 ± 3.4 0 of 8 (0)
Response type Average TMB mut/MB n (with available TMB data), n (%)
 PR 9.6 ± 0.8 2 of 18 (11)
 Stable disease 3.6 ± 2.5 2 of 18 (11)
 PD 6.1 ± 4.8 14 of 18 (78)

a Average TMB was calculated on the basis of tissue hybrid capture–based next-generation sequencing data, with two patients from this group lacking TMB data (n = 80).

b One patient was a carrier of two concomitant drivers: a RET fusion and a KRAS mutation. He was counted twice as part of the treated patients in the KRAS and RET groups.

Note: Types of immunotherapy administered are nivolumab (13 of 33 patients) and pembrolizumab (20 of 33 patients); two patients received nivolumab with a concomitant drug: crizotinib (KRAS + NTRK1 VUS carrier, response not evaluated because of patient death) and neratinib (ERBB2 carrier, PD). Upper part of table represents response rates with regard to driver status. Lower part of table shows mean TMB with respect to response type.

TMB, tumor mutation burden; mut, mutation; amp, amplification; MB, megabyte; Pts, patients; ORR, objective response rate; FDA, U.S. Food and Drug Administration; NCCN, National Comprehensive Cancer Network; MET, Mesenchymal-epithelial transition factor receptor tyrosine kinase gene; ERBB2, erb-b2 receptor tyrosine kinase 2 gene; RET, RET proto-oncogene; ALK, anaplastic lymphoma receptor tyrosine kinase gene; PR, partial response; PD, progressive disease.

Discussion

The diagnostic landscape in NSCLC is evolving rapidly, with new tumor profiling tests becoming available every year. The importance of performing multiplex genetic testing is already well established, and although it is recommended by the National Comprehensive Cancer Network (NCCN), it has yet to be widely adopted.

Despite its strengths,25 and 26 HC-based NGS has several limitations, and its efficacy as a practical tool in therapeutic decision making is yet to be thoroughly evaluated. At present, the technological power of HC-based NGS has surpassed the bioinformatic capabilities required to fully understand the genetic findings. Moreover, many GAs are not clinically applicable in the absence of specific targeted treatments that can block the involved oncogenic pathway. In this study, GAs associated with U.S. Food and Drug Administration–approved therapies were assessed, and although presumably targetable drivers were identified in 83% of patients (in level 1 analysis), only half of those patients were actually treated with targeted therapy. A leading example contributing to the creation of this gap is the KRAS gene, which was the most abundant driver. Another limitation is the difficulty of prioritizing drivers for targeted therapy when multiple drivers are present. However, compared with other molecular diagnostic methods, including amplicon-based NGS, HC-based NGS offers the ability to detect the full spectrum of clinically relevant GAs (point mutations, small insertions and deletions, copy number alterations, and genomic rearrangements/fusions) in a single assay, avoiding the need for FISH or other techniques and thereby saving precious tumor tissue and time. In addition, HC-based NGS permits the capture of large intronic regions in which rearrangements or fusions can be detected, and it offers statistically meaningful representation of gene amplifications and deletions, so that numerous types of cancer genome alterations can be enriched from a single sample.26 The possibility of identifying and potentially treating previously unknown oncogenic GAs is another advantage of HC-based NGS, as performed in our study. Compared with data from amplicon-based NGS, the data on the impact of HC–based NGS on clinical decisions in lung cancer are limited, and further investigation is warranted. Recently, Takeda et al. prospectively applied amplicon-based NGS panels that cover both mutational hotspots in 22 genes related to lung and colon tumorigenesis, and 72 major variants of ALK, RET, ROS1, and NTRK1 fusion transcripts.27 Actionable genetic alterations were identified in 40% of the 110 study patients, and 21% received targeted therapy, most of whom (83%) bore an EGFR or ALK driver. Notably, as in the Takeda et al. study,27 prior standard EGFR and ALK testing was not performed, (or used for comparison), and the real advantage of NGS over standard genomic testing is yet to be evaluated. Other groups have also developed amplicon-based NGS methods,28, 29, and 30 as compared with the more complex and expensive HC-based NGS. Drilon et al. used HC-based NGS to evaluate 31 patients in whom previous testing for alterations in 11 oncogenic genes by non-NGS methods had yielded negative results.31 Actionable GAs associated with a targeted drug according to NCCN guidelines were identified in eight patients (26%), six of whom eventually received targeted therapy.

This study provides a retrospective view on the clinical use of HC-based NGS technologies for lung cancer diagnosis in the real-life setting. Special emphasis was put on patients with EGFR/ALK-negative results and a clinical presentation suggesting that they might have a genomic driver. HC-based NGS before standard molecular testing was preferred in the case of a limited amount of tissue sample, as was the case for 15% of patients in our study, in which the treating physician used HC-based NGS upfront to prevent tissue exhaustion and the potential need for another biopsy. We also used HC-based NGS of cfDNA for 19 tissue-exhausted patients, alleviating the need for an additional invasive biopsy.20 and 32 In this study, we demonstrated that in addition to standard molecular testing (for EGFR/ALK mutation), HC-based NGS resulted in a changed treatment strategy for 37% of patients (n = 37). In 32 of these 37 cases (86%), the chosen treatment replaced chemotherapy, thus being more effective and less toxic and offering potential for improved quality of life and survival.7, 10, 12, and 33 Although defining clinical benefit from treatment in lung cancer may be challenging, in our study, 65% of the patients treated with targeted therapy achieved an objective CR or PR (62% if patients not previously tested are excluded). This rate is evidence of the high accuracy of HC-based NGS, and it is even more impressive considering that almost half of the treated patients (21 of 43 [48.8%]) received targeted therapy after failure of first-line treatment. As expected, patients with EGFR/ALK mutation had better response rates than did patients with other drivers, with rates of CR or PR of 82% (14 of 17) and 47% (eight of 17), respectively. The use of tissue for HC-based NGS is presumably preferable if available. In our cohort, a higher fraction of tissue biopsies resulted in changed treatment strategies (37 of 82 [45%]) compared with liquid biopsies (six of 19 [32%]), although the difference was not significant.

Our results suggest that broad use of HC-based NGS in lung cancer may provide a key for therapeutic decision making and that negative results by standard molecular tests (e.g., PCR and FISH) should not preclude HC-based NGS testing when the probability of identifying a targetable driver is high (e.g., adenocarcinoma in a young patient with a history of a small amount of or never smoking). However, guidelines from the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology recommend performing molecular testing based on histologic type, irrespective of clinical characteristics (e.g., smoking history, sex, and race).34

Our study demonstrated a high rate of false-negative results of standard molecular testing for EGFR and ALK mutations (15% [n = 15], with 12 of those patients (80%) treated with targeted therapy after HC-based NGS). This could be explained in a number of ways. First, technical failures and sensitivity issues can explain seven of the 15 GAs that were covered by standard assays but missed. Second, eight of 15 patients carried an EGFR/ALK mutation that could not have been picked up by the standard real-time PCR/FISH assays used (see Supplementary Table 1). For example, two of five patients who were identified by HC-based NGS as having an ALK rearrangement after previous negative FISH results had intron 19 rearrangement (i.e., lack of translocation). One patient, who had a high-volume EGFR amplification (×17), was exceptionally treated by EGFR TKIs and was included in this group. It is also noteworthy that four patients who were identified as EGFR/ALK positive by standard testing experienced progressive disease when treated with EGFR TKIs or an ALK TKI. In two of these four patients, HC-based NGS detected ALK and MET GAs, and both responded to the appropriate targeted drug.

One of the current challenges in clinically deploying HC-based NGS is financial. In our clinical setting, the cost of one assay of tissue HC-based NGS in 2015 was approximately $5274, whereas liquid HC-based NGS cost $4838. The compared total cost of testing individually for other drivers in addition to EGFR/ALK in cases in which a CR or PR was reached (ERBB2, ROS1, RET, and MET) was approximately $4300. Aside from cost, parallel gene testing using HC-based NGS might be more modest in terms of tissue consumption compared with sequential driver testing. In our setting, the amount of tissue required for tissue HC-based NGS is roughly 10 times greater than the amount required for standard testing of one driver (e.g., EGFR testing using real-time PCR). An HC-based NGS assay testing for more than 10 drivers would therefore be more tissue economic than testing for each of the drivers separately.

Another potential use of HC-based NGS is in estimating response to immunotherapy. Our results confirm previous data24 showing a possible association between response to immunotherapy and TMB. Interestingly enough, we show here a higher TMB within the group that did not have treatment-associated drivers and in patients with KRAS mutations. These groups were possibly also associated with better response to immunotherapy.

Our study is restricted by its retrospective nature, by its relatively small sample size, and by its being a single-center study. In addition, the high percentage of never-smokers, the preponderance of female patients, and the relatively young median age of our patient group represent a selection bias with a high pretest probability for the existence of driver mutation. The results of large future prospective trials such as the National Lung Matrix Trial in the United Kingdom35 and the Molecular Analysis for Therapy Choice Program, which is being led by the U.S. National Cancer Institute,36 are thus eagerly anticipated. Nevertheless, the high impact of HC-based NGS on treatment strategy, and the high overall response rate observed in this study, highlight the need for identifying molecular drivers and support the implementation of HC-based NGS in lung cancer.

Supplementary Data

Download file

Supplementary Table 1

Download file

Supplementary Data

References

  • 1 W.A. Cooper, D.C. Lam, S.A. O'Toole, et al. Molecular biology of lung cancer. J Thorac Dis. 2013;5(suppl 5):S479-S490
  • 2 J.H. Schiller, D. Harrington, C.P. Belani, et al. Comparison of four chemotherapy regimens for advanced non-small-cell lung cancer. N Engl J Med. 2002;346:92-98 Crossref
  • 3 I.B. Weinstein. Cancer. Addiction to oncogenes—the Achilles heel of cancer. Science. 2002;297:63-64 Crossref
  • 4 R. Califano, A. Abidin, N.U. Tariq, et al. Beyond EGFR and ALK inhibition: unravelling and exploiting novel genetic alterations in advanced non-small cell lung cancer. Cancer Treat Rev. 2015;41:401-411 Crossref
  • 5 Shlomi D OA, M. Gottfried, et al. Better selection model for EML4-ALK fusion gene test in patients with non-small-cell lung cancer. J Cancer Ther. 2013;4:54-58
  • 6 J. Bar, A. Cyjon, D. Flex, et al. EGFR mutation testing practice in advanced non-small cell lung cancer. Lung. 2014;192:759-763 Crossref
  • 7 M. Pekar-Zlotin, F.R. Hirsch, L. Soussan-Gutman, et al. Fluorescence in situ hybridization, immunohistochemistry, and next-generation sequencing for detection of EML4-ALK rearrangement in lung cancer. Oncologist. 2015;20:316-322 Crossref
  • 8 N. Peled, A.B. Rozenblum. [Lung cancer treatment in 2015: advances and future outlook]. Harefuah. 2015;154:510-511 540 [in Hebrew]
  • 9 D.S. Tan, S.S. Yom, M.S. Tsao, et al. The International Association for the Study of Lung Cancer consensus statement on optimizing management of EGFR mutation-positive non-small cell lung cancer: status in 2016. J Thorac Oncol. 2016;11:946-963
  • 10 M.G. Kris, B.E. Johnson, L.D. Berry, et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA. 2014;311:1998-2006 Crossref
  • 11 P.L. Chia, P. Mitchell, A. Dobrovic, et al. Prevalence and natural history of ALK positive non-small-cell lung cancer and the clinical impact of targeted therapy with ALK inhibitors. Clin Epidemiol. 2014;6:423-432 Crossref
  • 12 A. Lopez-Chavez, A. Thomas, A. Rajan, et al. Molecular profiling and targeted therapy for advanced thoracic malignancies: a biomarker-derived, multiarm, multihistology phase II basket trial. J Clin Oncol. 2015;33:1000-1007 Crossref
  • 13 G.J. Korpanty, D.M. Graham, M.D. Vincent, et al. Biomarkers that currently affect clinical practice in lung cancer: EGFR, ALK, MET, ROS-1, and KRAS. Front Oncol. 2014;4:204
  • 14 E.L. Kwak, Y.J. Bang, D.R. Camidge, et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med. 2010;363:1693-1703 Crossref
  • 15 J.G. Paez, P.A. Jänne, J.C. Lee, et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science. 2004;304:1497-1500 Crossref
  • 16 J. Naidoo, A. Drilon. Molecular Diagnostic testing in non-small cell lung cancer. Am J Hematol Oncol. 2014;10:4-11
  • 17 F. Thomas, C. Desmedt, P. Aftimos, et al. Impact of tumor sequencing on the use of anticancer drugs. Curr Opin Oncol. 2014;26:347-356 Crossref
  • 18 G.M. Frampton, A. Fichtenholtz, G.A. Otto, et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat Biotechnol. 2013;31:1023-1031 Crossref
  • 19 M. Stroun, P. Anker, J. Lyautey, et al. Isolation and characterization of DNA from the plasma of cancer patients. Eur J Cancer Clin Oncol. 1987;23:707-712 Crossref
  • 20 R.B. Lanman, S.A. Mortimer, O.A. Zill, et al. Analytical and clinical validation of a digital sequencing panel for quantitative, highly accurate evaluation of cell-free circulating tumor DNA. PLoS One. 2015;10:e0140712
  • 21 H. Schwarzenbach, D.S. Hoon, K. Pantel. Cell-free nucleic acids as biomarkers in cancer patients. Nat Rev Cancer. 2011;11:426-437 Crossref
  • 22 S. Jones, V. Anagnostou, K. Lytle, et al. Personalized genomic analyses for cancer mutation discovery and interpretation. Sci Transl Med. 2015;7 283ra53
  • 23 National Comprehensive Cancer Network. NCCN guidelines for non–small cell lung cancer. https://www.nccn.org/professionals/physician_gls/f_guidelines.asp#site. Accessed May 1, 2016.
  • 24 N.A. Rizvi, M.D. Hellmann, A. Snyder, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348:124-128 Crossref
  • 25 J. Gagan, E.M. Van Allen. Next-generation sequencing to guide cancer therapy. Genome Med. 2015;7:80 Crossref
  • 26 J.M. Heuckmann, R.K. Thomas. A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine. Ann Oncol. 2015;26:1830-1837
  • 27 M. Takeda, K. Sakai, M. Terashima, et al. Clinical application of amplicon-based next-generation sequencing to therapeutic decision making in lung cancer. Ann Oncol. 2015;26:2477-2482
  • 28 K. Konig, M. Peifer, J. Fassunke, et al. Implementation of amplicon parallel sequencing leads to improvement of diagnosis and therapy of lung cancer patients. J Thorac Oncol. 2015;10:1049-1057 Crossref
  • 29 K.K. Deeb, C.M. Hohman, N.F. Risch, et al. Routine clinical mutation profiling of non-small cell lung cancer using next-generation sequencing. Arch Pathol Lab Med. 2015;139:913-921 Crossref
  • 30 N. Pfarr, A. Stenzinger, R. Penzel, et al. High-throughput diagnostic profiling of clinically actionable gene fusions in lung cancer. Genes Chromosomes Cancer. 2015;55:30-44
  • 31 A. Drilon, L. Wang, M.E. Arcila, et al. Broad, hybrid capture-based next-generation sequencing identifies actionable genomic alterations in lung adenocarcinomas otherwise negative for such alterations by other genomic testing approaches. Clin Cancer Res. 2015;21:3631-3639 Crossref
  • 32 C.P. Paweletz, A. Sacher, C.K. Raymond, et al. Bias-corrected targeted next-generation sequencing for rapid, multiplexed detection of actionable alterations in cell-free DNA from advanced lung cancer patients. Clin Cancer Res. 2016;22:915-922
  • 33 N. Peled, G. Palmer, F.R. Hirsch, et al. Next-generation sequencing identifies and immunohistochemistry confirms a novel crizotinib-sensitive ALK rearrangement in a patient with metastatic non-small-cell lung cancer. J Thorac Oncol. 2012;7:e14-e16 Crossref
  • 34 N.I. Lindeman, P.T. Cagle, M.B. Beasley, et al. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. J Thorac Oncol. 2013;8:823-859 Crossref
  • 35 G. Middleton, L.R. Crack, S. Popat, et al. The National Lung Matrix Trial: translating the biology of stratification in advanced non-small-cell lung cancer. Ann Oncol. 2015;26:2464-2469
  • 36 J. Abrams, B. Conley, M. Mooney, et al. National Cancer Institute's precision medicine initiatives for the new National Clinical Trials Network. Am Soc Clin Oncol Educ Book. 2014;:71-76 Crossref

Footnotes

a Thoracic Cancer Service, Davidoff Cancer Center, Rabin Medical Center, Petah Tikva, Israel

b Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel

c Teva Pharmaceutical Industries Ltd., Shoam, Israel

Corresponding author. Address for correspondence: Nir Peled, MD, PhD, Thoracic Cancer Service, Davidoff Cancer Center, Kaplan St., Petah Tikva, 49100, Israel.

Drs. Rozenblum and Ilouze equally contributed to this work.

Disclosure: Mr. Dvir and Dr. Lior Soussan-Gutman are employees of Teva Pharmaceutical Industries Ltd. Dr. Dudnik is a consultant for Boehringer Ingelheim, Merck/Merck Sharp and Dohme, Roche Pharmaceuticals, and Astra Zeneca and has received payments for expenses. Dr. Peled is a consultant for Pfizer, Boehringer Ingelheim, Roche, Astra Zeneca, Merck Sharp and Dohme, Bristol-Myers Squib, Lilly, Novartis, and NovellusDx.

This work was performed in partial fulfillment of the doctor of medicine thesis requirements of the Sackler Faculty of Medicine, Tel Aviv University and was supported by Davidoff Cancer Center, Rabin Medical Center (Dr. Rozenblum).

Commentary by Nir Peled

Precision care in lung cancer has shifted survival and quality of life for many of our patients. With appropriate diagnosis, more than half of our NSCLC may be treated first without chemotherapy (combining targeted therapies and pembrolizumab for eligible patients). This study shows the strong impact of multiplex hybrid capturing NGS above the routine approved PCR-based or ALK IHC/FISH methods. Using hybrid capturing NGS had huge impact on treatment decision which was later translated to 66% response rate and oversall survival benefit. Mis-diagnosis of a driver mutation hits the patients twice. First, patients are treated by chemo- and not by targeted drugs, and later, by immunotherapies where its benefit in patients with a valid driver mutation is very low. In conclusion, the use of sensitive technology is highly important in lung cancer therapy (tissue or ctDNA) and we shell do any possible effort to bring the best technology to our patients.