Human lung cancer harbors spatially organized stem-immunity hubs associated with response to immunotherapy.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7+PD-1+CD8+ T cells, activated CCR7+LAMP3+ dendritic cells and CCL19+ fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10+ macrophages and TCF7-CD8+ T cells as well as between mature regulatory dendritic cells and TCF7+CD4+ and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11 + macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7 + LAMP3 + dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

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.

Immunogenicity and Reactogenicity of SARS-CoV-2 Vaccines in Patients With Cancer: The CANVAX Cohort Study.

PURPOSE: The immunogenicity and reactogenicity of SARS-CoV-2 vaccines in patients with cancer are poorly understood. METHODS: We performed a prospective cohort study of adults with solid-organ or hematologic cancers to evaluate anti-SARS-CoV-2 immunoglobulin A/M/G spike antibodies, neutralization, and reactogenicity ≥ 7 days following two doses of mRNA-1273, BNT162b2, or one dose of Ad26.COV2.S. We analyzed responses by multivariate regression and included data from 1,638 healthy controls, previously reported, for comparison. RESULTS: Between April and July 2021, we enrolled 1,001 patients; 762 were eligible for analysis (656 had neutralization measured). mRNA-1273 was the most immunogenic (log10 geometric mean concentration [GMC] 2.9, log10 geometric mean neutralization titer [GMT] 2.3), followed by BNT162b2 (GMC 2.4; GMT 1.9) and Ad26.COV2.S (GMC 1.5; GMT 1.4; P < .001). The proportion of low neutralization (< 20% of convalescent titers) among Ad26.COV2.S recipients was 69.9%. Prior COVID-19 infection (in 7.1% of the cohort) was associated with higher responses (P < .001). Antibody titers and neutralization were quantitatively lower in patients with cancer than in comparable healthy controls, regardless of vaccine type (P < .001). Receipt of chemotherapy in the prior year or current steroids were associated with lower antibody levels and immune checkpoint blockade with higher neutralization. Systemic reactogenicity varied by vaccine and correlated with immune responses (P = .002 for concentration, P = .016 for neutralization). In 32 patients who received an additional vaccine dose, side effects were similar to prior doses, and 30 of 32 demonstrated increased antibody titers (GMC 1.05 before additional dose, 3.17 after dose). CONCLUSION: Immune responses to SARS-CoV-2 vaccines are modestly impaired in patients with cancer. These data suggest utility of antibody testing to identify patients for whom additional vaccine doses may be effective and appropriate, although larger prospective studies are needed.

Low peripheral blood derived neutrophil-to-lymphocyte ratio (dNLR) is associated with increased tumor T-cell infiltration and favorable outcomes to first-line pembrolizumab in non-small cell lung cancer.

BACKGROUND: An elevated peripheral blood derived neutrophil-to-lymphocyte ratio (dNLR) is a negative prognostic marker for patients with non-small cell lung cancer (NSCLC) receiving chemotherapy and immune checkpoint inhibitors. Whether dNLR is also associated with clinical outcomes to first-line pembrolizumab among patients with NSCLC and a programmed cell death ligand 1 (PD-L1) Tumor Proportion Score (TPS) of ≥50% is uncertain. How dNLR relates to the tumor immune microenvironment is also unclear. METHODS: In two participating academic centers, we retrospectively analyzed the dNLR (defined as the absolute neutrophil count/white cell count - absolute neutrophil count) prior to initiation of first-line pembrolizumab in patients with metastatic NSCLC and a PD-L1 TPS ≥50% and lacking genomic alterations in EGFR and ALK. An unbiased recursive partitioning algorithm was used to investigate an optimal dNLR cut-off with respect to objective response rate (ORR). Multiplexed immunofluorescence for CD8+, FOXP3+, PD-1+, and PD-L1 was performed on a separate cohort of NSCLCs to determine the immunophenotype associated with dNLR. RESULTS: A total of 221 patients treated with first-line pembrolizumab were included in this study. The optimal dNLR cut-off to differentiate treatment responders from non-responders was 2.6. Compared with patients with a dNLR ≥2.6 (n=97), patients with dNLR <2.6 (n=124) had a significantly higher ORR (52.4% vs 24.7%, p<0.001), a significantly longer median progression-free survival (mPFS 10.4 vs 3.4 months, HR 0.48, 95% CI 0.35 to 0.66, p<0.001), and a significantly longer median overall survival (mOS 36.6 vs 9.8 months, HR 0.34, 95% CI 0.23 to 0.49, p<0.001). After adjusting for age, sex, tobacco use, performance status, histology, serum albumin level, oncogenic driver status, and PD-L1 distribution (50%-89% vs ≥90%), a dNLR <2.6 was confirmed to be an independent predictor of longer mPFS (HR 0.47, 95% CI 0.33 to 0.67, p<0.001) and mOS (HR 0.32, 95% CI 0.21 to 0.49, p<0.001). Among advanced NSCLC samples with a PD-L1 TPS of ≥50%, those with a dNLR <2.6 had significantly higher numbers of tumor-associated CD8+, FOXP3+, PD-1 +immune cells, and PD-1 +CD8+T cells than those with a dNLR ≥2.6. CONCLUSIONS: Among patients with NSCLC and a PD-L1 TPS ≥50%, a low dNLR has a distinct immune tumor microenvironment and more favorable outcomes to first-line pembrolizumab.

Clinical Acquired Resistance to KRASG12C Inhibition through a Novel KRAS Switch-II Pocket Mutation and Polyclonal Alterations Converging on RAS-MAPK Reactivation.

Mutant-selective KRASG12C inhibitors, such as MRTX849 (adagrasib) and AMG 510 (sotorasib), have demonstrated efficacy in KRAS G12C-mutant cancers, including non-small cell lung cancer (NSCLC). However, mechanisms underlying clinical acquired resistance to KRASG12C inhibitors remain undetermined. To begin to define the mechanistic spectrum of acquired resistance, we describe a patient with KRAS G12C NSCLC who developed polyclonal acquired resistance to MRTX849 with the emergence of 10 heterogeneous resistance alterations in serial cell-free DNA spanning four genes (KRAS, NRAS, BRAF, MAP2K1), all of which converge to reactivate RAS-MAPK signaling. Notably, a novel KRAS Y96D mutation affecting the switch-II pocket, to which MRTX849 and other inactive-state inhibitors bind, was identified that interferes with key protein-drug interactions and confers resistance to these inhibitors in engineered and patient-derived KRAS G12C cancer models. Interestingly, a novel, functionally distinct tricomplex KRASG12C active-state inhibitor RM-018 retained the ability to bind and inhibit KRASG12C/Y96D and could overcome resistance. SIGNIFICANCE: In one of the first reports of clinical acquired resistance to KRASG12C inhibitors, our data suggest polyclonal RAS-MAPK reactivation as a central resistance mechanism. We also identify a novel KRAS switch-II pocket mutation that impairs binding and drives resistance to inactive-state inhibitors but is surmountable by a functionally distinct KRASG12C inhibitor.See related commentary by Pinnelli and Trusolino, p. 1874.This article is highlighted in the In This Issue feature, p. 1861.

Deep Learning to Estimate RECIST in Patients with NSCLC Treated with PD-1 Blockade.

Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical trials, is increasingly recognized as an opportunity for discovery, to reduce disparities, and to contribute to regulatory approval. Maximal value of RWE may be facilitated through machine-learning techniques to integrate and interrogate large and otherwise underutilized datasets. In cancer research, an ongoing challenge for RWE is the lack of reliable, reproducible, scalable assessment of treatment-specific outcomes. We hypothesized a deep-learning model could be trained to use radiology text reports to estimate gold-standard RECIST-defined outcomes. Using text reports from patients with non-small cell lung cancer treated with PD-1 blockade in a training cohort and two test cohorts, we developed a deep-learning model to accurately estimate best overall response and progression-free survival. Our model may be a tool to determine outcomes at scale, enabling analyses of large clinical databases. SIGNIFICANCE: We developed and validated a deep-learning model trained on radiology text reports to estimate gold-standard objective response categories used in clinical trial assessments. This tool may facilitate analysis of large real-world oncology datasets using objective outcome metrics determined more reliably and at greater scale than currently possible.This article is highlighted in the In This Issue feature, p. 1.

Coronavirus Disease 2019 Infection in a Patient Population with Lung Cancer: Incidence, Presentation, and Alternative Diagnostic Considerations.

INTRODUCTION: Lung cancer is associated with severe coronavirus disease 2019 (COVID-19) infections. Symptom overlap between COVID-19 and lung cancer may complicate diagnostic evaluation. We aimed to investigate the incidence, symptoms, differential diagnosis, and outcomes of COVID-19 in patients with lung cancer. METHODS: To determine an at-risk population for COVID-19, we retrospectively identified patients with lung cancer receiving longitudinal care within a single institution in the 12 months (April 1, 2019 to March 31, 2020) immediately preceding the COVID-19 pandemic, including an "active therapy population" treated within the last 60 days of this period. Among patients subsequently referred for COVID-19 testing, we compared symptoms, laboratory values, radiographic findings, and outcomes of positive versus negative patients. RESULTS: Between April 1, 2019 and March 31, 2020, a total of 696 patients received longitudinal care, including 406 (58%) in the active therapy population. Among 55 patients referred for COVID-19 testing, 24 (44%) were positive for COVID-19, representing a cumulative incidence of 3.4% (longitudinal population) and 1.5% (active therapy population). Compared with patients who were COVID-19 negative, those who were COVID-19 positive were more likely to have a supplemental oxygen requirement (11% versus 54%, p = 0.005) and to have typical COVID-19 pneumonia imaging findings (5 versus 56%, p = 0.001). Otherwise, there were no marked differences in presenting symptoms. Among patients who were COVID-19 negative, alternative etiologies included treatment-related toxicity (26%), atypical pneumonia (22%), and disease progression (22%). A total of 16 patients positive for COVID-19 (67%) required hospitalization, and seven (29%) died from COVID-related complications. CONCLUSIONS: COVID-19 was infrequent in this lung cancer population, but these patients experienced high rates of morbidity and mortality. Oncologists should maintain a low threshold for COVID-19 testing in patients with lung cancer presenting with acute symptoms.