Prospective Comprehensive Molecular Characterization of Lung Adenocarcinomas for Efficient Patient Matching to Approved and Emerging Therapies

Abstract

Tumor genetic testing is standard of care for patients with advanced lung adenocarcinoma, but the fraction of patients who derive clinical benefit remains undefined. Here, we report the experience of 860 patients with metastatic lung adenocarcinoma analyzed prospectively for mutations in >300 cancer-associated genes. Potentially actionable genetic events were stratified into one of four levels based upon published clinical or laboratory evidence that the mutation in question confers increased sensitivity to standard or investigational therapies. Overall, 37.1% (319/860) of patients received a matched therapy guided by their tumor molecular profile. Excluding alterations associated with standard-of-care therapy, 14.4% (69/478) received matched therapy, with a clinical benefit of 52%. Use of matched therapy was strongly influenced by the level of preexistent clinical evidence that the mutation identified predicts for drug response. Analysis of genes mutated significantly more often in tumors without known actionable mutations nominated STK11 and KEAP1 as possible targetable mitogenic drivers.Significance: An increasing number of therapies that target molecular alterations required for tumor maintenance and progression have demonstrated clinical activity in patients with lung adenocarcinoma. The data reported here suggest that broader, early testing for molecular alterations that have not yet been recognized as standard-of-care predictive biomarkers of drug response could accelerate the development of targeted agents for rare mutational events and could result in improved clinical outcomes. Cancer Discov; 7(6); 596-609. ©2017 AACR.See related commentary by Liu et al., p. 555This article is highlighted in the In This Issue feature, p. 539.

Conflict of interest statement

Conflicts of interest: DM Hyman is a consultant/advisory board member for Atara, Chugai, CytomX and has received research funding from LOXO, AstraZeneca and PUMA. M Ladanyi is a consultant/advisory board member for NCCN/AstraZeneca and has received research funding from LOXO. GJ Riely has been a consultant for Genentech and Novartis and receives research funding from Novartis, Pfizer, and Ariad. No potential conflicts of interest were reported by other authors.

©2017 American Association for Cancer Research.

Figures

Figure 1. Potentially actionable oncogenic drivers identified by MSK-IMPACT testing

A. Spectrum of oncogenic drivers assigned to 860 patients with lung adenocarcinoma identified by MSK-IMPACT. B. Comparison of selected gene alteration frequencies in the MSK-IMPACT and TCGA cohorts. C. Oncoprint of select gene alterations identified by MSK-IMPACT in patients with a level 1–4 alterations or those with no actionable mutation (Unknown Mitogenic Driver).

Figure 2

Figure 2A. Use of matched therapy (MT) correlates strongly with the level of evidence that the mutation identified predicts for drug response. A. Use of Matched Therapy (MT), immunotherapy (IT) and clinical trial participation in patients with level 1–4 alterations or in the unknown mitogenic driver (UMD) cohorts. B: Use of matched therapy and immunotherapy and clinical benefit from matched therapy in patients whose tumors harbored alterations in select level 1–4 genes.

Figure 3. Use of matched therapy and clinical benefit in patients with known activating mutations in EGFR

(Top) Frequency of known activating and resistance mutations in EGFR identified by MSK-IMPACT. (Bottom) Use of matched therapy, chemotherapy, immunotherapy, clinical trial enrollment and clinical benefit from matched therapy as a function of the specific EGFR mutation identified in the patient’s tumor.

Figure 4. Potential driver alterations in the unknown mitogenic driver (UMD) cohort

A. Estimated purity analysis by FACETS in samples with Level 1–4 alteration to the UMD sample set. B. Oncoprint of the most common gene alterations in 103 patients with no actionable Level 1–4 driver mutations with a comparative frequency of select recurrently altered genes in the UMD cohort level 1–4 samples according to smoking history. P values were calculated using Fisher’s exact test C. Distribution of missense mutations in KEAP1 detected by MSK-IMPACT (upper panel): x-axis represents amino acid potions and y-axis represents number of samples mutated. The PFAM domains were also displayed as context. Protein structure analysis revealing that KEAP1 missense mutations identified in lung adenocarcinoma patients (the ones with side chains displayed) clustered the interaction interface with Nrf2 (nuclear factor erythroid 2-related factor 2). Nrf2 peptide is colored in green.