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Supplementary Figures S1-S6, Table S1-S3, and eMethods

Purpose:MET tyrosine kinase inhibitors (TKIs) can achieve modest clinical outcomes in MET exon 14–altered lung cancers, likely secondary to primary resistance. Mechanisms of primary resistance remain poorly characterized and comprehensive proteomic analyses have not previously been performed.Experimental Design:We performed hybrid capture-based DNA sequencing, targeted RNA sequencing, cell-free DNA sequencing, selected reaction monitoring mass spectrometry (SRM-MS), and immunohistochemistry on patient samples of MET exon 14–altered lung cancers treated with a MET TKI. Associations between overall response rate (ORR), progression-free survival (PFS), and putative genomic alterations and MET protein expression were evaluated.Results:Seventy-five of 168 MET exon 14–altered lung cancers received a MET TKI. Previously undescribed (zygosity, clonality, whole-genome duplication) and known (copy-number focality, tumor mutational burden, mutation region/type) genomic factors were not associated with ORR/PFS (P > 0.05). In contrast, MET expression was associated with MET TKI benefit. Only cases with detectable MET expression by SRM-MS (N = 15) or immunochemistry (N = 22) responded to MET TKI therapy, and cancers with H-score ≥ 200 had a higher PFS than cancers below this cutoff (10.4 vs. 5.5 months, respectively; HR, 3.87; P = 0.02).Conclusions:In MET exon 14–altered cancers treated with a MET TKI, a comprehensive analysis of previously unknown and known genomic factors did not identify a genomic mechanism of primary resistance. Instead, MET expression correlated with benefit, suggesting the potential role of interrogating the proteome in addition to the genome in confirmatory prospective trials.

Purpose: MET tyrosine kinase inhibitors (TKIs) can achieve modest clinical outcomes in MET exon 14–altered lung cancers, likely secondary to primary resistance. Mechanisms of primary resistance remain poorly characterized and comprehensive proteomic analyses have not previously been performed. Experimental Design: We performed hybrid capture-based DNA sequencing, targeted RNA sequencing, cell-free DNA sequencing, selected reaction monitoring mass spectrometry (SRM-MS), and immunohistochemistry on patient samples of MET exon 14–altered lung cancers treated with a MET TKI. Associations between overall response rate (ORR), progression-free survival (PFS), and putative genomic alterations and MET protein expression were evaluated. Results: Seventy-five of 168 MET exon 14–altered lung cancers received a MET TKI. Previously undescribed (zygosity, clonality, whole-genome duplication) and known (copy-number focality, tumor mutational burden, mutation region/type) genomic factors were not associated with ORR/PFS (P > 0.05). In contrast, MET expression was associated with MET TKI benefit. Only cases with detectable MET expression by SRM-MS (N = 15) or immunochemistry (N = 22) responded to MET TKI therapy, and cancers with H-score ≥ 200 had a higher PFS than cancers below this cutoff (10.4 vs. 5.5 months, respectively; HR, 3.87; P = 0.02). Conclusions: In MET exon 14–altered cancers treated with a MET TKI, a comprehensive analysis of previously unknown and known genomic factors did not identify a genomic mechanism of primary resistance. Instead, MET expression correlated with benefit, suggesting the potential role of interrogating the proteome in addition to the genome in confirmatory prospective trials.

Structured Abstract Background Patients with lung cancers may have disproportionately severe COVID-19 outcomes. Understanding the patient-specific and cancer-specific features that impact severity of COVID-19 may inform optimal cancer care during this pandemic. Patients and methods We examined consecutive patients with lung cancer and confirmed diagnosis of COVID-19 (n=102) at a single center from March 12-May 6, 2020. Thresholds of severity were defined a priori as hospitalization, ICU/intubation/DNI (a composite metric of severe disease including ICU stay, intubation and invasive mechanical ventilation, and/or transition to do not intubate [DNI]), or death. Recovery was defined as >14 days from COVID-19 test and >3 days since symptom resolution. HLA alleles were inferred from MSK-IMPACT (n=46) and compared to controls with lung cancer and no known non-COVID-19 (n=5166). Results COVID-19 was severe in patients with lung cancer (62% hospitalized, 25% died). Although severe, COVID-19 accounted for a minority of overall lung cancer-deaths during the pandemic (11% overall). Determinants of COVID-19 severity were largely patient-specific features, including smoking status and chronic obstructive pulmonary disease (Odds ratios for severe COVID-19 2.9, 95% CI 1.07-9.44 comparing the median [23.5 pack-years] to never and 3.87, 95% CI 1.35-9.68, respectively). Cancer-specific features, including prior thoracic surgery/radiation and recent systemic therapies did not impact severity. HLA supertypes were generally similar in mild or severe cases of COVID-19 compared to non-COVID-19 controls. Most patients recovered from COVID-19, including 25% patients initially requiring intubation. Among hospitalized patients, hydroxychloroquine did not improve COVID-19 outcomes. Conclusion COVID-19 is associated with high burden of severity in patients with lung cancer. Patient-specific features, rather than cancer-specific features or treatments, are the greatest determinants of severity., Highlights • COVID-19 is associated with high burden of severity in patients with lung cancer. • Patient-specific features, rather than cancer-specific features or treatments, are the greatest determinants of severity.

Importance Real-world data sets that combine clinical and genomic data may be subject to left truncation (when potential study participants are not included because they have already passed the milestone of interest at the time of study recruitment). The lapse between diagnosis and molecular testing can present analytic challenges and threaten the validity and interpretation of survival analyses. Observations Effects of ignoring left truncation when estimating overall survival are illustrated using data from the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE BPC), and a straightforward risk-set adjustment approach is described. Ignoring left truncation results in overestimation of overall survival: unadjusted median survival estimates from diagnosis among patients with stage IV non-small cell lung cancer or stage IV colorectal cancer were overestimated by more than 1 year. Conclusions and relevance Clinicogenomic data are a valuable resource for evaluation of real-world cancer outcomes and should be analyzed using appropriate methods to maximize their potential. Analysts must become adept at application of appropriate statistical methods to ensure valid, meaningful, and generalizable research findings.

Although cancer immunotherapy with PD-(L)1 blockade is now routine treatment for patients with lung cancer, remarkably little is known about acquired resistance. We examined 1,201 patients with NSCLC treated with PD-(L)1 blockade to clinically characterize acquired resistance, finding it to be common (occurring in more than 60% of initial responders), with persistent but diminishing risk over time, and with distinct metastatic and survival patterns compared to primary resistance. To examine the molecular phenotype and potential mechanisms of acquired resistance, we performed whole transcriptome and exome tumor profiling in a subset of NSCLC patients (n=29) with acquired resistance. Systematic immunogenomic analysis revealed that tumors with acquired resistance generally had enriched signals of inflammation (including IFNγ signaling and inferred CD8+ T cells) and could be separated into IFNγ upregulated and stable subsets. IFNγ upregulated tumors had putative routes of resistance with signatures of dysfunctional interferon signaling and mutations in antigen presentation genes. Transcriptomic profiling of cancer cells from a murine model of acquired resistance to PD-(L)1 blockade also showed evidence of dysfunctional interferon signaling and acquired insensitivity to in vitro interferon gamma treatment. In summary, we characterized clinical and molecular features of acquired resistance to PD-(L)1 blockade in NSCLC and found evidence of ongoing but dysfunctional IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance informs therapeutic strategies to effectively reprogram and reverse acquired resistance.

BackgroundWe conducted the first trial of neoadjuvant PD-1 blockade in resectable non-small cell lung cancer (NSCLC), finding nivolumab monotherapy to be safe and feasible with an encouraging rate of pathologic response. Building on these results, and promising data for nivolumab plus ipilimumab (anti-CTLA-4) in advanced NSCLC, we expanded our study to include an arm investigating neoadjuvant nivolumab plus ipilimumab.MethodsPatients with resectable stage IB (≥4 cm)–IIIA (American Joint Committee on Cancer Tumor Node Metastases seventh edition), histologically confirmed, treatment-naïve NSCLC received nivolumab 3 mg/kg intravenously plus ipilimumab 1 mg/kg intravenously 6 weeks prior to planned resection. Nivolumab 3 mg/kg was given again approximately 4 and 2 weeks preoperatively. Primary endpoints were safety and feasibility with a planned enrollment of 15 patients. Pathologic response was a key secondary endpoint.ResultsWhile the treatment regimen was feasible per protocol, due to toxicity, the study arm was terminated early by investigator consensus after 9 of 15 patients were enrolled. All patients received every scheduled dose of therapy and were fit for planned surgery; however, 6 of 9 (67%) experienced treatment-related adverse events (TRAEs) and 3 (33%) experienced grade ≥3 TRAEs. Three of 9 patients (33%) had biopsy-confirmed tumor progression precluding definitive surgery. Of the 6 patients who underwent resection, 3 are alive and disease-free, 2 experienced recurrence and are actively receiving systemic treatment, and one died postoperatively due to acute respiratory distress syndrome. Two patients who underwent resection had tumor pathologic complete responses (pCRs) and continue to remain disease-free over 24 months since surgery. Pathologic response correlated with pre-treatment tumor PD-L1 expression, but not tumor mutation burden. Tumor KRAS/STK11 co-mutations were identified in 5 of 9 patients (59%), of whom two with disease progression precluding surgery had tumor KRAS/STK11/KEAP1 co-mutations.ConclusionsThough treatment was feasible, due to toxicity the study arm was terminated early by investigator consensus. In light of this, and while the long-term disease-free status of patients who achieved pCR is encouraging, further investigation of neoadjuvant nivolumab plus ipilimumab in patients with resectable NSCLC requires the identification of predictive biomarkers that enrich for response.

Obtaining information regarding cancer recurrence from a retrospective, EHR-based dataset poses several challenges primarily due to the lack of structured data. Patients are at risk for cancer recurrence beginning at a time point at which they are characterized as having no evidence of disease. The absence of cancer may be indicated on a radiology report or a medical oncologist assessment, requiring manual review and interpretation of potentially ambiguous free text. Further, the recurrence event itself can be defined based on several distinct data sources including pathology, imaging, clinician assessments, or tumor markers. The likelihood of ascertaining recurrence is dependent on the frequency and type of surveillance performed and varies based on tumor type and based on clinicians' thresholds for pursuing workup of borderline or suspicious findings; if follow up assessments are infrequent, there are fewer opportunities to detect recurrence. Given these challenges, there is currently no standardized approach to evaluating cancer recurrence in EHR data, impeding analyses of rare molecular tumor subtypes in multi-institutional linked clinico-genomic databases. For this analysis, we leveraged the AACR Project GENIE Biopharma Collaborative data based on the PRISSMM curation model to develop an algorithm for identifying recurrence among patients diagnosed with stage I-III non-small cell lung cancer or with stage I-III colorectal cancer. This algorithm involves using curated pathology report data to identify a definitive surgery as the time at which patients have completed curative intent treatment. Subsequent imaging reports, pathology reports, medical oncologist assessments and tumor marker data are then evaluated in order to characterize the timing of specific recurrence events. We will present the real-world recurrence algorithm, its underlying rationale and discuss applications of recurrence endpoints. Beyond enabling estimates of recurrence-free survival, identifying cancer recurrence will allow for estimation of progression-free survival among stage I-III patients in addition to estimation of PFS among de novo stage IV patients. Estimating PFS in a large cohort of patients with linked phenomic and genomic data has historically been a limitation of these types of datasets. Overcoming this limitation will allow for precision medicine advances in oncology by facilitating data pooling across institutions and enabling examination of rare molecular subtypes in relation to clinically meaningful endpoints. Citation Format: Jessica A. Lavery, Samantha Brown, Eva Lepisto, Michele L. Lenoue-Newton, Caroline McCarthy, Hira Rizvi, Celeste Yu, Kenneth L. Kehl, Shawn M. Sweeney, Julia E. Rudolph, Nikolaus Schultz, Brooke Mastrogiacomo, Ritika Kundra, Jeremy Warner, Philippe Bedard, Gregory J. Riely, Katherine S. Panageas, Deborah Schrag, AACR Project GENIE Consortium. Defining real-world recurrence in the AACR Project GENIE Biopharma Collaborative Data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2619.

Studies linking genomic and phenomic data are subject to selection biases, including delayed entry or immortal time bias. Delayed entry can be problematic for time-to-event analyses, but utilization of appropriate statistical methods to account for delayed entry are underutilized. Delayed entry commonly occurs when genomic sequencing results are obtained after the start time for survival estimation. To evaluate the impact of left truncation on overall survival (OS) estimates, we explored outcomes in patients with de novo stage IV non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) from the AACR GENIE Biopharma Collaborative, who had genomic sequencing within a specified timeframe. We analyzed OS from diagnosis and from start of the most common first-line regimen, carboplatin/pemetrexed for NSCLC (N = 212 patients) and FOLFOX for CRC (N = 369 patients). We compared median OS using standard Kaplan-Meier methods to median OS using left truncation methods to account for delayed entry. All NSCLC and CRC patients underwent genomic sequencing after their diagnosis date. Among NSCLC patients on carboplatin/pemetrexed, 41% and among CRC patients on FOLFOX, 14% had sequencing determined after starting first-line regimen. The survfit function in R package survival was used, and the absolute differences and percent differences in median OS estimates were calculated. Failure to account for delayed entry leads to an overestimation of OS, regardless of cohort and start date. Adjusting survival outcomes using left truncation methods reduces the influence of some aspects of selection bias and results in better estimates of time to event outcomes. Analyses from these cohorts can provide meaningful insights about survival outcomes outside the clinical trial setting and may support trial design and reliable selection of control arms. As such, it is imperative that analytic methods to account for the inflated survival estimates are incorporated. EstimateCRC Stage IV (N = 658)NSCLC Stage IV (N = 722)Unadjusted Median (IQR) Overall Survival from Diagnosis (Years)3.2 (2.9, 3.4)2.3 (2.0, 2.5)Median (IQR) Overall Survival from Diagnosis in Years, Adjusting for Delayed Entry2.1 (1.9, 2.4)1.3 (1.1, 1.6)Difference in Medians (Years)1.11.0% Difference in Medians34%44%EstimateCRC Stage IV (N = 369)NSCLC Stage IV (N = 212)Unadjusted Median (IQR) Overall Survival from Most Common First-Line Regimen (Years)2.9 (2.6, 3.4)1.3 (1.0, 1.6)Median (IQR) Overall Survival from Most Common First-Line Regimen in Years, Adjusting for Delayed Entry2.1 (1.8, 2.5)0.9 (0.7, 1.2)Difference in Medians (Years)0.80.4% Difference in Medians28%31% Citation Format: Samantha Brown, Jessica A. Lavery, Eva M. Lepisto, Caroline McCarthy, Hira Rizvi, Celeste Yu, Kenneth L. Kehl, Shawn M. Sweeney, Julia E. Rudolph, Nikolaus Schultz, Ritika Kundra, Brooke Mastrogiacomo, Phillipe Bedard, Jeremy L. Warner, Gregory J. Riely, Deborah Schrag, Katherine S. Panageas, The AACR Project GENIE Consortium. Ignoring left truncation in overall survival within real-world genomic-phenomic data leads to inflated survival estimates [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2620.

8556 Background: While immune checkpoint inhibitors (ICI) are a standard option for patients with malignant pleural mesotheliomas (MPM), there is limited data on the rate of immune related adverse events (irAEs) and effects on clinical outcomes. Methods: 61 patients with MPM who received ICI between January 2016 and October 2020 were assessed and followed through November 2020. irAEs (CTCAE v5.0) were noted along with the time from ICI start to irAE onset. Patients were grouped into irAE ever versus never. Clinicopathologic characteristics, prior treatments, and investigator assessed clinical benefit rate (CBR; partial response [PR] + stable disease [SD]) were compared by Fisher’s Exact and Mann-Whitney Tests. Overall survival (OS) and investigator assessed progression free survival (PFS) from ICI start were compared using Kaplan Meier. In consented patients (n = 56), next generation sequencing (MSK-IMPACT) was performed with HLA genotyping analysis by POLYSOLVER software and alleles for the three major MHC class I (HLA-A, -B, -C) genes were obtained from whole exome recapture. Results: Most patients were male (72%), smokers (55%), > 70 years old (median 72, range 34-90), and had epithelioid histology (67%). No patients had baseline autoimmune disease. The median line of prior systemic therapies to ICI start was 2 (range 1-5). 17 patients (28%) developed an irAE on therapy including 7 (11%) with grade 3 to 5 events (pneumonitis, myositis, pancreatitis, nephritis, encephalitis and adrenal insufficiency). The median time from ICI start to irAE was 2.5 months (range 2 days – 5.8 months). There was no association with dual ICI (n = 6) vs single agent (n = 11) and sooner onset (2.1 vs 4.0 months; p = 0.10) nor higher grade (median grade 2 vs 3; p = 0.31) of irAEs. 1 patient developed grade 5 pneumonitis with onset 2 days after initial dose of dual-ICI. Comparing patients with irAEs to those without, there was no difference in distribution of epithelioid histology (n = 10 vs 31; p = 0.54), median age (71 vs 72 years old; p = 0.43), nor prior thoracic radiation (n = 5 vs 11; p = 0.75).There was no difference in HLA type nor the fraction of HLA alleles of individual genes amongst the groups. Patients who had an irAE were on ICI longer than those that did not (median time on ICI 5.4 vs 0.9 months, respectively; p = 0.02). OS was higher in patients with irAEs compared to those without (21.1 vs 4.7 months; p = 0.003) as was PFS (6.8 vs 1.7 months; p = 0.01). There was a significant increase in the CBR between those that had an irAE (65%; 5 PR, 6 SD) and those that did not (27%; 2 PR, 10 SD; p = 0.006). Conclusions: 28% of patients with MPM who received ICIs developed an irAE and onset tended to be early in the course of treatment. There was no clear predictive clinicopathologic feature that correlated with the occurrence of irAE. There was a significant increase in OS, PFS, and CBR in patients that had an irAE compared to those that did not.

2032 Background: 30-50% of patients with non-early NSCLC will eventually develop BM, with a median survival of less than one year from BM diagnosis. There are no widely accepted clinical risk models for development of BM in patients without them at baseline. We predicted the binary risk of BM using clinical and genetic factors from a large multi-institutional cohort. Methods: Stage II-IV NSCLC patients from the AACR Project GENIE Biopharma Consortium dataset were eligible. This consisted of 4 academic institutions who curated clinical data of patients who had somatic next-generation tumor sequencing (NGS) between 2015-2017. We excluded patients who had BM at baseline, died within 30 days of NSCLC diagnosis, or did not undergo brain imaging. Covariates included demographics, anticancer therapies (received up to 90 days prior to BM development and within 5 years from NSCLC diagnosis), and NGS data; radiotherapy (RT) data were not available. NGS features included mutations and copy number alterations. These features were restricted to those classified as oncogenic by OncoKB. Univariate feature selection with Fisher’s test (p

10535 Background: Homologous recombination is a major mechanism of defective DNA repair, but it remains uncertain whether homologous repair deficient (HRD) tumors have favorable prognosis or are more/less likely to respond to treatment than tumors lacking such mutations. Objective: To determine whether lung (NSCLC) and colorectal (CRC) HRD+ tumors have better survival or response to chemotherapy than HRD- tumors. Methods: Patients with de novo stage IV NSCLC or CRC who had next generation sequencing (NGS) between 2015-2018 from one of four cancer centers were identified. Records were curated using the PRISSMM framework to ascertain treatment, overall survival (OS) and progression free survival based on imaging (PFS-I) and oncologists’ notes (PFS-M). Each NSCLC or CRC tumor was categorized as HRD+ if NGS revealed an oncogenic/likely oncogenic mutation in: ATM, BAP1, BARD1, BLM, BRCA1, BRCA2, BRIP1, CHEK2, FAM175A, FANCA, FANCC, NBN, PALB2, RAD50, RAD51, RAD51C, RTEL1, or MRE11A based on the OncoKB database. The tumor was categorized as HRD- if no oncogenic mutation in any of these genes was evident and HRD indeterminate (HRD?) if no mutation was identified but the panel did not include all genes. OS, PFS-I and PFS-M from start of first line therapy were reported by HRD status. The percentage with a good response to first line therapy (≥2x the median) and exceptional response (≥3x the median) was estimated for each endpoint. Results: For NSCLC 4% were HRD+, 59% HRD- and 37% HRD?. For CRC there were 5% HRD+, 60% HRD- and 35% HRD?. There were no significant differences for any survival endpoint between patients who were HRD+ vs HRD- in univariable analyses. The proportion of good and exceptional responders to first line systemic chemotherapy also did not vary by HRD status, though patients with HRD+ CRC were potentially more likely to be exceptional responders. Similarly, no differences between HRD+ and HRD- tumors were apparent for the subgroup receiving platinum containing therapy. Conclusions: NSCLC and CRC patients with somatic mutations in HRD oncogenic genes did not differ from patients lacking such a mutation with respect to OS or PFS. CRC patients with HRD+ tumors may be more likely to be exceptional responders, but sample sizes are limited. By May, the analysis will include breast and pancreatic cancer cases.[Table: see text]