Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer.

Although immunotherapy with PD-(L)1 blockade is routine for lung cancer, little is known about acquired resistance. Among 1,201 patients with non-small cell lung cancer (NSCLC) treated with PD-(L)1 blockade, acquired resistance is common, occurring in >60% of initial responders. Acquired resistance shows differential expression of inflammation and interferon (IFN) signaling. Relapsed tumors can be separated by upregulated or stable expression of IFNγ response genes. Upregulation of IFNγ response genes is associated with putative routes of resistance characterized by signatures of persistent IFN signaling, immune dysfunction, and mutations in antigen presentation genes which can be recapitulated in multiple murine models of acquired resistance to PD-(L)1 blockade after in vitro IFNγ treatment. Acquired resistance to PD-(L)1 blockade in NSCLC is associated with an ongoing, but altered IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance may inform therapeutic strategies to effectively reprogram and reverse acquired resistance.

Outcomes of Combination Platinum-Doublet Chemotherapy and Anti-PD(L)-1 Blockade in KRASG12C-Mutant Non-Small Cell Lung Cancer.

BACKGROUND: Direct KRASG12C inhibitors are approved for patients with non-small cell lung cancers (NSCLC) in the second-line setting. The standard-of-care for initial treatment remains immune checkpoint inhibitors, commonly in combination with platinum-doublet chemotherapy (chemo-immunotherapy). Outcomes to chemo-immunotherapy in this subgroup have not been well described. Our goal was to define the clinical outcomes to chemo-immunotherapy in patients with NSCLC with KRASG12C mutations. PATIENTS AND METHODS: Through next-generation sequencing, we identified patients with advanced NSCLC with KRAS mutations treated with chemo-immunotherapy at 2 institutions. The primary objective was to determine outcomes and determinants of response to first-line chemo-immunotherapy among patients with KRASG12C by evaluating objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). We assessed the impact of coalterations in STK11/KEAP1 on outcomes. As an exploratory objective, we compared the outcomes to chemo-immunotherapy in KRASG12C versus non-G12C groups. RESULTS: One hundred and thirty eight patients with KRASG12C treated with first-line chemo-immunotherapy were included. ORR was 41% (95% confidence interval (CI), 32-41), median PFS was 6.8 months (95%CI, 5.5-10), and median OS was 15 months (95%CI, 11-28). In a multivariable model for PFS, older age (P = .042), squamous cell histology (P = .008), poor ECOG performance status (PS) (P < .001), and comutations in KEAP1 and STK11 (KEAP1MUT/STK11MUT) (P = .015) were associated with worse PFS. In a multivariable model for OS, poor ECOG PS (P = .004) and KEAP1MUT/STK11MUT (P = .009) were associated with worse OS. Patients with KRASG12C (N = 138) experienced similar outcomes to chemo-immunotherapy compared to patients with non-KRASG12C (N = 185) for both PFS (P = .2) and OS (P = .053). CONCLUSIONS: We define the outcomes to first-line chemo-immunotherapy in patients with KRASG12C, which provides a real-world benchmark for clinical trial design involving patients with KRASG12C mutations. Outcomes are poor in patients with specific molecular coalterations, highlighting the need to develop more effective frontline therapies.

Efficacy of PD-(L)1 blockade monotherapy compared with PD-(L)1 blockade plus chemotherapy in first-line PD-L1-positive advanced lung adenocarcinomas: a cohort study.

BACKGROUND: Single-agent PD-(L)1 blockade (IO) alone or in combination with chemotherapy (Chemotherapy-IO) is approved first-line therapies in patients with advanced lung adenocarcinomas (LUADs) with PD-L1 expression ≥1%. These regimens have not been compared prospectively. The primary objective was to compare first-line efficacies of single-agent IO to Chemotherapy-IO in patients with advanced LUADs. Secondary objectives were to explore if clinical, pathological, and genomic features were associated with differential response to Chemotherapy-IO versus IO. METHODS: This was a multicenter retrospective cohort study. Inclusion criteria were patients with advanced LUADs with tumor PD-L1 ≥1% treated with first-line Chemotherapy-IO or IO. To compare the first-line efficacies of single-agent IO to Chemotherapy-IO, we conducted inverse probability weighted Cox proportional hazards models using estimated propensity scores. RESULTS: The cohort analyzed included 866 patients. Relative to IO, Chemotherapy-IO was associated with improved objective response rate (ORR) (44% vs 35%, p=0.007) and progression-free survival (PFS) in patients with tumor PD-L1≥1% (HR 0.84, 95% CI 0.72 to 0.97, p=0.021) or PD-L1≥50% (ORR 55% vs 38%, p<0.001; PFS HR 0.68, 95% CI 0.53 to 0.87, p=0.002). Using propensity-adjusted analyses, only never-smokers in the PD-L1≥50% subgroup derived a differential survival benefit from Chemotherapy-IO vs IO (p=0.013). Among patients with very high tumor PD-L1 expression (≥90%), there were no differences in outcome between treatment groups. No genomic factors conferred differential survival benefit to Chemotherapy-IO versus IO. CONCLUSIONS: While the addition of chemotherapy to PD-(L)1 blockade increases the probability of initial response, never-smokers with tumor PD-L1≥50% comprise the only population identified that derived an apparent survival benefit with treatment intensification.

Clinical and Molecular Features of Long-term Response to Immune Checkpoint Inhibitors in Patients with Advanced Non-Small Cell Lung Cancer.

PURPOSE: We sought to identify features of patients with advanced non-small cell lung cancer (NSCLC) who achieve long-term response (LTR) to immune checkpoint inhibitors (ICI), and how these might differ from features predictive of short-term response (STR). EXPERIMENTAL DESIGN: We performed a multicenter retrospective analysis of patients with advanced NSCLC treated with ICIs between 2011 and 2022. LTR and STR were defined as response ≥ 24 months and response < 12 months, respectively. Tumor programmed death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), next-generation sequencing (NGS), and whole-exome sequencing (WES) data were analyzed to identify characteristics enriched in patients achieving LTR compared with STR and non-LTR. RESULTS: Among 3,118 patients, 8% achieved LTR and 7% achieved STR, with 5-year overall survival (OS) of 81% and 18% among LTR and STR patients, respectively. High TMB (≥50th percentile) enriched for LTR compared with STR (P = 0.001) and non-LTR (P < 0.001). Whereas PD-L1 ≥ 50% enriched for LTR compared with non-LTR (P < 0.001), PD-L1 ≥ 50% did not enrich for LTR compared with STR (P = 0.181). Nonsquamous histology (P = 0.040) and increasing depth of response [median best overall response (BOR) -65% vs. -46%, P < 0.001] also associated with LTR compared with STR; no individual genomic alterations were uniquely enriched among LTR patients. CONCLUSIONS: Among patients with advanced NSCLC treated with ICIs, distinct features including high TMB, nonsquamous histology, and depth of radiographic improvement distinguish patients poised to achieve LTR compared with initial response followed by progression, whereas high PD-L1 does not.

The GENIE BPC NSCLC Cohort: A Real-World Repository Integrating Standardized Clinical and Genomic Data for 1,846 Patients with Non-Small Cell Lung Cancer.

PURPOSE: We describe the clinical and genomic landscape of the non-small cell lung cancer (NSCLC) cohort of the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) Biopharma Collaborative (BPC). EXPERIMENTAL DESIGN: A total of 1,846 patients with NSCLC whose tumors were sequenced from 2014 to 2018 at four institutions participating in AACR GENIE were randomly chosen for curation using the PRISSMM data model. Progression-free survival (PFS) and overall survival (OS) were estimated for patients treated with standard therapies. RESULTS: In this cohort, 44% of tumors harbored a targetable oncogenic alteration, with EGFR (20%), KRAS G12C (13%), and oncogenic fusions (ALK, RET, and ROS1; 5%) as the most frequent. Median OS (mOS) on first-line platinum-based therapy without immunotherapy was 17.4 months [95% confidence interval (CI), 14.9-19.5 months]. For second-line therapies, mOS was 9.2 months (95% CI, 7.5-11.3 months) for immune checkpoint inhibitors (ICI) and 6.4 months (95% CI, 5.1-8.1 months) for docetaxel ± ramucirumab. In a subset of patients treated with ICI in the second-line or later setting, median RECIST PFS (2.5 months; 95% CI, 2.2-2.8) and median real-world PFS based on imaging reports (2.2 months; 95% CI, 1.7-2.6) were similar. In exploratory analysis of the impact of tumor mutational burden (TMB) on survival on ICI treatment in the second-line or higher setting, TMB z-score harmonized across gene panels was associated with improved OS (univariable HR, 0.85; P = 0.03; n = 247 patients). CONCLUSIONS: The GENIE BPC cohort provides comprehensive clinicogenomic data for patients with NSCLC, which can improve understanding of real-world patient outcomes.

Impact of Aneuploidy and Chromosome 9p Loss on Tumor Immune Microenvironment and Immune Checkpoint Inhibitor Efficacy in NSCLC.

INTRODUCTION: Although gene-level copy number alterations have been studied as a potential biomarker of immunotherapy efficacy in NSCLC, the impact of aneuploidy burden and chromosomal arm-level events on immune checkpoint inhibitor (ICI) efficacy in NSCLC is uncertain. METHODS: Patients who received programmed cell death protein 1 or programmed death-ligand 1 (PD-L1) inhibitor at two academic centers were included. Across all 22 chromosomes analyzed, an arm was considered altered if at least 70% of its territory was either gained or deleted. Among nonsquamous NSCLCs which underwent targeted next-generation sequencing, we retrospectively quantified aneuploidy using the adjusted fraction of chromosomal arm alterations (FAA), defined as the number of altered chromosome arms divided by the number of chromosome arms assessed, adjusted for tumor purity. RESULTS: Among 2293 nonsquamous NSCLCs identified, the median FAA increased with more advanced cancer stage and decreased with higher PD-L1 tumor proportion score (TPS) levels (median FAA in TPS < 1%: 0.09, TPS 1%-49%: 0.08, TPS ≥ 50%: 0.05, p < 0.0001). There was a very weak correlation between FAA and tumor mutational burden when taken as continuous variables (R: 0.07, p = 0.0005). A total of 765 advanced nonsquamous NSCLCs with available FAA values were treated with ICIs. With decreasing FAA tertiles, there was a progressive improvement in objective response rate (ORR 15.1% in upper tertile versus 23.2% in middle tertile versus 28.4% in lowest tertile, p = 0.001), median progression-free survival (mPFS 2.5 versus 3.3 versus 4.1 mo, p < 0.0001), and median overall survival (mOS 12.5 versus 13.9 versus 16.4 mo, p = 0.006), respectively. In the arm-level enrichment analysis, chromosome 9p loss (OR = 0.22, Q = 0.0002) and chromosome 1q gain (OR = 0.43, Q = 0.002) were significantly enriched in ICI nonresponders after false discovery rate adjustment. Compared with NSCLCs without chromosome 9p loss (n = 452), those with 9p loss (n = 154) had a lower ORR (28.1% versus 7.8%, p < 0.0001), a shorter mPFS (4.1 versus 2.3 mo, p < 0.0001), and a shorter mOS (18.0 versus 9.6 mo, p < 0.0001) to immunotherapy. In addition, among NSCLCs with high PD-L1 expression (TPS ≥ 50%), chromosome 9p loss was associated with lower ORR (43% versus 6%, p < 0.0001), shorter mPFS (6.4 versus 2.6 mo, p = 0.0006), and shorter mOS (30.2 versus 14.3 mo, p = 0.0008) to immunotherapy compared with NSCLCs without 9p loss. In multivariable analysis, adjusting for key variables including FAA, chromosome 9p loss, but not 1q gain, retained a significant impact on ORR (hazard ratio [HR] = 0.25, p < 0.001), mPFS (HR = 1.49, p = 0.001), and mOS (HR = 1.47, p = 0.003). Multiplexed immunofluorescence and computational deconvolution of RNA sequencing data revealed that tumors with either high FAA levels or chromosome 9p loss had significantly fewer tumor-associated cytotoxic immune cells. CONCLUSIONS: Nonsquamous NSCLCs with high aneuploidy and chromosome 9p loss have a distinct tumor immune microenvironment and less favorable outcomes to ICIs.

Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer.

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts.

Lineage tracing reveals clonal progenitors and long-term persistence of tumor-specific T cells during immune checkpoint blockade.

Paired single-cell RNA and T cell receptor sequencing (scRNA/TCR-seq) has allowed for enhanced resolution of clonal T cell dynamics in cancer. Here, we report a scRNA/TCR-seq analysis of 187,650 T cells from 31 tissue regions, including tumor, adjacent normal tissues, and lymph nodes (LN), from three patients with non-small cell lung cancer after immune checkpoint blockade (ICB). Regions with viable cancer cells are enriched for exhausted CD8+ T cells, regulatory CD4+ T cells (Treg), and follicular helper CD4+ T cells (TFH). Tracking T cell clonotypes across tissues, combined with neoantigen specificity assays, reveals that TFH and tumor-specific exhausted CD8+ T cells are clonally linked to TCF7+SELL+ progenitors in tumor draining LNs, and progressive exhaustion trajectories of CD8+ T, Treg, and TFH cells with proximity to the tumor microenvironment. Finally, longitudinal tracking of tumor-specific CD8+ and CD4+ T cell clones reveals persistence in the peripheral blood for years after ICB therapy.

The ectonucleotidase CD39 identifies tumor-reactive CD8+ T cells predictive of immune checkpoint blockade efficacy in human lung cancer.

Improved identification of anti-tumor T cells is needed to advance cancer immunotherapies. CD39 expression is a promising surrogate of tumor-reactive CD8+ T cells. Here, we comprehensively profiled CD39 expression in human lung cancer. CD39 expression enriched for CD8+ T cells with features of exhaustion, tumor reactivity, and clonal expansion. Flow cytometry of 440 lung cancer biospecimens revealed weak association between CD39+ CD8+ T cells and tumoral features, such as programmed death-ligand 1 (PD-L1), tumor mutation burden, and driver mutations. Immune checkpoint blockade (ICB), but not cytotoxic chemotherapy, increased intratumoral CD39+ CD8+ T cells. Higher baseline frequency of CD39+ CD8+ T cells conferred improved clinical outcomes from ICB therapy. Furthermore, a gene signature of CD39+ CD8+ T cells predicted benefit from ICB, but not chemotherapy, in a phase III clinical trial of non-small cell lung cancer. These findings highlight CD39 as a proxy of tumor-reactive CD8+ T cells in human lung cancer.

Genomic Landscapes and Hallmarks of Mutant RAS in Human Cancers.

The RAS family of small GTPases represents the most commonly activated oncogenes in human cancers. To better understand the prevalence of somatic RAS mutations and the compendium of genes that are coaltered in RAS-mutant tumors, we analyzed targeted next-generation sequencing data of 607,863 mutations from 66,372 tumors in 51 cancer types in the AACR Project GENIE Registry. Bayesian hierarchical models were implemented to estimate the cancer-specific prevalence of RAS and non-RAS somatic mutations, to evaluate co-occurrence and mutual exclusivity, and to model the effects of tumor mutation burden and mutational signatures on comutation patterns. These analyses revealed differential RAS prevalence and comutations with non-RAS genes in a cancer lineage-dependent and context-dependent manner, with differences across age, sex, and ethnic groups. Allele-specific RAS co-mutational patterns included an enrichment in NTRK3 and chromatin-regulating gene mutations in KRAS G12C-mutant non-small cell lung cancer. Integrated multiomic analyses of 10,217 tumors from The Cancer Genome Atlas (TCGA) revealed distinct genotype-driven gene expression programs pointing to differential recruitment of cancer hallmarks as well as phenotypic differences and immune surveillance states in the tumor microenvironment of RAS-mutant tumors. The distinct genomic tracks discovered in RAS-mutant tumors reflected differential clinical outcomes in TCGA cohort and in an independent cohort of patients with KRAS G12C-mutant non-small cell lung cancer that received immunotherapy-containing regimens. The RAS genetic architecture points to cancer lineage-specific therapeutic vulnerabilities that can be leveraged for rationally combining RAS-mutant allele-directed therapies with targeted therapies and immunotherapy. SIGNIFICANCE: The complex genomic landscape of RAS-mutant tumors is reflective of selection processes in a cancer lineage-specific and context-dependent manner, highlighting differential therapeutic vulnerabilities that can be clinically translated.

Genetic Ancestry Correlates with Somatic Differences in a Real-World Clinical Cancer Sequencing Cohort.

Accurate ancestry inference is critical for identifying genetic contributors of cancer disparities among populations. Although methods to infer genetic ancestry have historically relied upon genome-wide markers, the adaptation to targeted clinical sequencing panels presents an opportunity to incorporate ancestry inference into routine diagnostic workflows. We show that global ancestral contributions and admixture of continental populations can be quantitatively inferred using markers captured by the MSK-IMPACT clinical panel. In a pan-cancer cohort of 45,157 patients, we observed differences by ancestry in the frequency of somatic alterations, recapitulating known associations and revealing novel associations. Despite the comparable overall prevalence of driver alterations by ancestry group, the proportion of patients with clinically actionable alterations was lower for African (30%) compared with European (33%) ancestry. Although this result is largely explained by population-specific cancer subtype differences, it reveals an inequity in the degree to which different populations are served by existing precision oncology interventions. SIGNIFICANCE: We performed a comprehensive analysis of ancestral associations with somatic mutations in a real-world pan-cancer cohort, including >5,000 non-European individuals. Using an FDA-authorized tumor sequencing panel and an FDA-recognized oncology knowledge base, we detected differences in the prevalence of clinically actionable alterations, potentially contributing to health care disparities affecting underrepresented populations. This article is highlighted in the In This Issue feature, p. 2483.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer.

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

Association of High Tumor Mutation Burden in Non-Small Cell Lung Cancers With Increased Immune Infiltration and Improved Clinical Outcomes of PD-L1 Blockade Across PD-L1 Expression Levels.

Importance: Although tumor mutation burden (TMB) has been explored as a potential biomarker of immunotherapy efficacy in solid tumors, there still is a lack of consensus about the optimal TMB threshold that best discriminates improved outcomes of immune checkpoint inhibitor therapy among patients with non-small cell lung cancer (NSCLC). Objectives: To determine the association between increasing TMB levels and immunotherapy efficacy across clinically relevant programmed death ligand-1 (PD-L1) levels in patients with NSCLC. Design, Setting, and Participants: This multicenter cohort study included patients with advanced NSCLC treated with immunotherapy who received programmed cell death-1 (PD-1) or PD-L1 inhibition in the Dana-Farber Cancer Institute (DFCI), Memorial Sloan Kettering Cancer Center (MSKCC), and in the Stand Up To Cancer (SU2C)/Mark Foundation data sets. Clinicopathological and genomic data were collected from patients between September 2013 and September 2020. Data analysis was performed from November 2021 to February 2022. Exposures: Treatment with PD-1/PD-L1 inhibition without chemotherapy. Main Outcomes and Measures: Association of TMB levels with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Results: In the entire cohort of 1552 patients with advanced NSCLC who received PD-1/PD-L1 blockade, the median (range) age was 66 (22-92) years, 830 (53.5%) were women, and 1347 (86.8%) had cancer with nonsquamous histologic profile. A regression tree modeling ORR as a function of TMB identified 2 TMB groupings in the discovery cohort (MSKCC), defined as low TMB (≤19.0 mutations per megabase) and high TMB (>19.0 mutations per megabase), which were associated with increasing improvements in ORR, PFS, and OS in the discovery cohort and in 2 independent cohorts (DFCI and SU2C/Mark Foundation). These TMB levels also were associated with significant improvements in outcomes of immunotherapy in each PD-L1 tumor proportion score subgroup of less than 1%, 1% to 49%, and 50% or higher. The ORR to PD-1/PD-L1 inhibition was as high as 57% in patients with high TMB and PD-L1 expression 50% or higher and as low as 8.7% in patients with low TMB and PD-L1 expression less than 1%. Multiplexed immunofluorescence and transcriptomic profiling revealed that high TMB levels were associated with increased CD8-positive, PD-L1-positive T-cell infiltration, increased PD-L1 expression on tumor and immune cells, and upregulation of innate and adaptive immune response signatures. Conclusions and Relevance: These findings suggest that increasing TMB levels are associated with immune cell infiltration and an inflammatory T-cell-mediated response, resulting in increased sensitivity to PD-1/PD-L1 blockade in NSCLC across PD-L1 expression subgroups.

Systemic and Oligo-Acquired Resistance to PD-(L)1 Blockade in Lung Cancer.

PURPOSE: Clinical patterns and the associated optimal management of acquired resistance to PD-(L)1 blockade are poorly understood. EXPERIMENTAL DESIGN: All cases of metastatic lung cancer treated with PD-(L)1 blockade at Memorial Sloan Kettering were reviewed. In acquired resistance (complete/partial response per RECIST, followed by progression), clinical patterns were distinguished as oligo (OligoAR ≤ 3 lesions of disease progression) or systemic (sAR). We analyzed the relationships between patient characteristics, burden/location of disease, outcomes, and efficacy of therapeutic interventions. RESULTS: Of 1,536 patients, 312 (20%) had an initial response and 143 developed AR (9% overall, 46% of responders). OligoAR was the most common pattern (80/143, 56%). Baseline tumor mutational burden, depth of response, and duration of response were significantly increased in oligoAR compared with sAR (P < 0.001, P = 0.03, P = 0.04, respectively), whereas baseline PD-L1 and tumor burden were similar. Post-progression, oligoAR was associated with improved overall survival (median 28 months vs. 10 months, P < 0.001) compared with sAR. Within oligoAR, post-progression survival was greater among patients treated with locally-directed therapy (e.g., radiation, surgery; HR, 0.41; P = 0.039). Fifty-eight percent of patients with oligoAR treated with locally-directed therapy alone are progression-free at last follow-up (median 16 months), including 13 patients who are progression-free more than 2 years after local therapy. CONCLUSIONS: OligoAR is a common and distinct pattern of acquired resistance to PD-(L)1 blockade compared with sAR. OligoAR is associated with improved post-progression survival and some cases can be effectively managed with local therapies with durable benefit.

Germline Pathogenic Variants Impact Clinicopathology of Advanced Lung Cancer.

BACKGROUND: The genetic factors that modulate risk for developing lung cancer have not been fully defined. Here, we sought to determine the prevalence and clinical significance of germline pathogenic/likely pathogenic variants (PV) in patients with advanced lung cancer. METHODS: We studied clinical and tumor characteristics of germline PV in 5,118 patients who underwent prospective genomic profiling using paired tumor-normal tissue samples in 468 cancer genes. RESULTS: Germline PV in high/moderate-penetrance genes were observed in 222 (4.3%) patients; of these, 193 patients had PV in DNA damage repair (DDR) pathway genes including BRCA2 (n = 54), CHEK2 (n = 30), and ATM (n = 26) that showed high rate of biallelic inactivation in tumors. BRCA2 heterozygotes with lung adenocarcinoma were more likely to be never smokers and had improved survival compared with noncarriers. Fourteen patients with germline PV in lung cancer predisposing genes (TP53, EGFR, BAP1, and MEN1) were diagnosed at younger age compared with noncarriers, and of tumor suppressors, 75% demonstrated biallelic inactivation in tumors. A significantly higher proportion of germline PV in high/moderate-penetrance genes were detected in high-risk patients who had either a family history of any cancer, multiple primary tumors, or early age at diagnosis compared with unselected patients (10.5% vs. 4.1%; P = 1.7e-04). CONCLUSIONS: These data underscore the biological and clinical importance of germline mutations in highly penetrant DDR genes as a risk factor for lung cancer. IMPACT: The family members of lung cancer patients harboring PV in cancer predisposing genes should be referred for genetic counseling and may benefit from proactive surveillance.

A Definitive Prognostication System for Patients With Thoracic Malignancies Diagnosed With Coronavirus Disease 2019: An Update From the TERAVOLT Registry.

INTRODUCTION: Patients with thoracic malignancies are at increased risk for mortality from coronavirus disease 2019 (COVID-19), and a large number of intertwined prognostic variables have been identified so far. METHODS: Capitalizing data from the Thoracic Cancers International COVID-19 Collaboration (TERAVOLT) registry, a global study created with the aim of describing the impact of COVID-19 in patients with thoracic malignancies, we used a clustering approach, a fast-backward step-down selection procedure, and a tree-based model to screen and optimize a broad panel of demographics and clinical COVID-19 and cancer characteristics. RESULTS: As of April 15, 2021, a total of 1491 consecutive eligible patients from 18 countries were included in the analysis. With a mean observation period of 42 days, 361 events were reported with an all-cause case fatality rate of 24.2%. The clustering procedure screened 73 covariates in 13 clusters. A further multivariable logistic regression for the association between clusters and death was performed, resulting in five clusters significantly associated with the outcome. The fast-backward step-down selection procedure then identified the following seven major determinants of death: Eastern Cooperative Oncology Group-performance status (ECOG-PS) (OR = 2.47, 1.87-3.26), neutrophil count (OR = 2.46, 1.76-3.44), serum procalcitonin (OR = 2.37, 1.64-3.43), development of pneumonia (OR = 1.95, 1.48-2.58), C-reactive protein (OR = 1.90, 1.43-2.51), tumor stage at COVID-19 diagnosis (OR = 1.97, 1.46-2.66), and age (OR = 1.71, 1.29-2.26). The receiver operating characteristic analysis for death of the selected model confirmed its diagnostic ability (area under the receiver operating curve = 0.78, 95% confidence interval: 0.75-0.81). The nomogram was able to classify the COVID-19 mortality in an interval ranging from 8% to 90%, and the tree-based model recognized ECOG-PS, neutrophil count, and c-reactive protein as the major determinants of prognosis. CONCLUSIONS: From 73 variables analyzed, seven major determinants of death have been identified. Poor ECOG-PS was found to have the strongest association with poor outcome from COVID-19. With our analysis, we provide clinicians with a definitive prognostication system to help determine the risk of mortality for patients with thoracic malignancies and COVID-19.

A Scalable Quality Assurance Process for Curating Oncology Electronic Health Records: The Project GENIE Biopharma Collaborative Approach.

PURPOSE: The American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative is a multi-institution effort to build a pan-cancer repository of genomic and clinical data curated from the electronic health record. For the research community to be confident that data extracted from electronic health record text are reliable, transparency of the approach used to ensure data quality is essential. MATERIALS AND METHODS: Four institutions participating in AACR's Project GENIE created an observational cohort of patients with cancer for whom tumor molecular profiling data, therapeutic exposures, and treatment outcomes are available and will be shared publicly with the research community. A comprehensive approach to quality assurance included assessments of (1) feasibility of the curation model through pressure test cases; (2) accuracy through programmatic queries and comparison with source data; and (3) reproducibility via double curation and code review. RESULTS: Assessments of feasibility resulted in critical modifications to the curation directives. Queries and comparison with source data identified errors that were rectified via data correction and curator retraining. Assessment of intercurator reliability indicated a reliable curation model. CONCLUSION: The transparent quality assurance processes for the GENIE BPC data ensure that the data can be used for analyses that support clinical decision making and advances in precision oncology.

Diminished Efficacy of Programmed Death-(Ligand)1 Inhibition in STK11- and KEAP1-Mutant Lung Adenocarcinoma Is Affected by KRAS Mutation Status.

INTRODUCTION: STK11 and KEAP1 mutations (STK11 mutant [STK11MUT] and KEAP1MUT) are among the most often mutated genes in lung adenocarcinoma (LUAD). Although STK11MUT has been associated with resistance to programmed death-(ligand)1 (PD-[L]1) inhibition in KRASMUT LUAD, its impact on immunotherapy efficacy in KRAS wild-type (KRASWT) LUAD is currently unknown. Whether KEAP1MUT differentially affects outcomes to PD-(L)1 inhibition in KRASMUT and KRASWT LUAD is also unknown. METHODS: Clinicopathologic and genomic data were collected from September 2013 to September 2020 from patients with advanced LUAD at the Dana-Farber Cancer Institute/Massachusetts General Hospital cohort and the Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center cohort. Clinical outcomes to PD-(L)1 inhibition were analyzed according to KRAS, STK11, and KEAP1 mutation status in two independent cohorts. The Cancer Genome Atlas transcriptomic data were interrogated to identify differences in tumor gene expression and tumor immune cell subsets, respectively, according to KRAS/STK11 and KRAS/KEAP1 comutation status. RESULTS: In the combined cohort (Dana-Farber Cancer Institute/Massachusetts General Hospital + Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center) of 1261 patients (median age = 61 y [range: 22-92], 708 women [56.1%], 1065 smokers [84.4%]), KRAS mutations were detected in 536 cases (42.5%), and deleterious STK11 and KEAP1 mutations were found in 20.6% (260 of 1261) and 19.2% (231 of 1202) of assessable cases, respectively. In each independent cohort and in the combined cohort, STK11 and KEAP1 mutations were associated with significantly worse progression-free (STK11 hazard ratio [HR] = 2.04, p < 0.0001; KEAP1 HR = 2.05, p < 0.0001) and overall (STK11 HR = 2.09, p < 0.0001; KEAP1 HR = 2.24, p < 0.0001) survival to immunotherapy uniquely among KRASMUT but not KRASWT LUADs. Gene expression ontology and immune cell enrichment analyses revealed that the presence of STK11 or KEAP1 mutations results in distinct immunophenotypes in KRASMUT, but not in KRASWT, lung cancers. CONCLUSIONS: STK11 and KEAP1 mutations confer worse outcomes to immunotherapy among patients with KRASMUT but not among KRASWT LUAD. Tumors harboring concurrent KRAS/STK11 and KRAS/KEAP1 mutations display distinct immune profiles in terms of gene expression and immune cell infiltration.

Implications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies.

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.

Intra- and inter-reader agreement of iRECIST and RECIST 1.1 criteria for the assessment of tumor response in patients receiving checkpoint inhibitor immunotherapy for lung cancer.

OBJECTIVES: To investigate the inter- and intra-reader agreement of immune Response Evaluation Criteria in Solid Tumors (iRECIST) and Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) in patients with lung cancer treated with immunotherapy. MATERIALS AND METHODS: This retrospective study included 85 patients with lung cancer treated with PD-1 blockade. Four radiologists evaluated computed topography (CT) scans before and after initiation of immunotherapy using iRECIST and RECIST 1.1. Weighted kappa (k) with equal weights was used to assess the intra-reader agreement between 2 repeated reads on overall response at all time points, best overall response, and the response at the time point of progression, as well as the intra-reader agreement between iRECIST and RECIST. The inter-reader agreement was calculated using Light's kappa. RESULTS: Intra-reader agreement for overall response at all time points, best overall response, and time point of progression was substantial to almost perfect for both iRECIST and RECIST 1.1 (k = 0.651-0.983). Inter-reader agreement was substantial for iRECIST (κ = 0.657-0.742) while RECIST 1.1 was moderate to substantial (κ = 0.587-0.686). The level of inter-reader agreement was not higher on repeat read for iRECIST (κ = 0.677-0.709 and κ = 0.657-0.742 for first and second read, respectively) as well as for RECIST 1.1 (κ = 0.587-0.659 and κ = 0.633-0.686 for first and second read, respectively). Almost perfect agreement was observed between RECIST 1.1 and iRECIST at first (κ = 0.813-0.923) and second read (κ = 0.841-0.912). CONCLUSION: The inter- and intra-reader agreement of iRECIST is high and similar to RECIST 1.1 in patients with lung cancer treated with immunotherapy.