Purpose: Although clinical studies have shown promise for targeting programmed cell death protein-1 (PD-1) and ligand (PD-L1) signaling in non–small cell lung cancer (NSCLC), the factors that predict which subtype patients will be responsive to checkpoint blockade are not fully understood. Experimental Design: We performed an integrated analysis on the multiple-dimensional data types including genomic, transcriptomic, proteomic, and clinical data from cohorts of lung adenocarcinoma public (discovery set) and internal (validation set) database and immunotherapeutic patients. Gene set enrichment analysis (GSEA) was used to determine potentially relevant gene expression signatures between specific subgroups. Results: We observed that TP53 mutation significantly increased expression of immune checkpoints and activated T-effector and interferon-γ signature. More importantly, the TP53/KRAS comutated subgroup manifested exclusive increased expression of PD-L1 and a highest proportion of PD-L1+/CD8A+. Meanwhile, TP53- or KRAS-mutated tumors showed prominently increased mutation burden and specifically enriched in the transversion-high (TH) cohort. Further analysis focused on the potential molecular mechanism revealed that TP53 or KRAS mutation altered a group of genes involved in cell-cycle regulating, DNA replication and damage repair. Finally, immunotherapeutic analysis from public clinical trial and prospective observation in our center were further confirmed that TP53 or KRAS mutation patients, especially those with co-occurring TP53/KRAS mutations, showed remarkable clinical benefit to PD-1 inhibitors. Conclusions: This work provides evidence that TP53 and KRAS mutation in lung adenocarcinoma may be served as a pair of potential predictive factors in guiding anti–PD-1/PD-L1 immunotherapy. Clin Cancer Res; 23(12); 3012–24. ©2016 AACR.

Patients with EGFR mutations showed unfavorable response to programmed cell death-1 (PD-1) blockade immunotherapy in non-small cell lung cancer (NSCLC). Yet the underlying association between EGFR mutation and immune resistance remains largely unclear. We performed an integrated analysis of PD-ligand 1(PD-L1)/CD8 expression and mutation profile based on the repository database and resected early-stage NSCLC in Guangdong Lung Cancer Institute (GLCI). Meanwhile, 2 pool-analyses were set to clarify the correlation between EGFR mutation and PD-L1 expression, and the association of EGFR status with response to anti-PD-1/L1 therapy. Pool-analysis of 15 public studies suggested that patients with EGFR mutations had decreased PD-L1 expression (odds ratio: 1.79, 95% CI: 1.10–2.93; P = 0.02). Analysis of The Cancer Genome Atlas (TCGA) and the GCLI cohort confirmed the inverse correlation between EGFR mutation and PD-L1 expression. Furthermore, patients with EGFR mutation showed a lack of T-cell infiltration and shrinking proportion of PD-L1⁺/CD8⁺ TIL (P = 0.034). Importantly, patients with EGFR mutations, especially the sensitive subtype, showed a significantly decreased mutation burden, based on analysis of the discovery and validation sets. Finally, a pool-analysis of 4 randomized control trials confirmed that patients with EGFR mutation did not benefit from PD-1/L1 inhibitors (Hazard ratio [HR] = 1.09, P = 0.51) while patients with EGFR wild-type did (HR = 0.73, P < 0.00001). This study provided evidence of a correlation between EGFR mutations and an uninflamed tumor microenvironment with immunological tolerance and weak immunogenicity, which caused an inferior response to PD-1 blockade in NSCLCs.

Purpose: Although tumor mutation burden (TMB) has been well known to predict the response to immune checkpoint inhibitors (ICIs), lacking of randomized clinical trial data has restricted its clinical application. This study aimed at exploring the significance and feasibility of biomarker combination based on TMB and copy number alteration (CNA) for the prognosis of each tumor and prediction for ICI therapy in metastatic pan-cancer milieu. Experimental Design: Non-ICI treated MSK pan-cancer cohort was used for prognosis analysis. Three independent immunotherapy cohorts including non-small cell lung cancer (NSCLC, n = 240), skin cutaneous melanoma (SKCM, n = 174) and mixed cancer (Dana-Farber, n=98) patients from previous studies were analyzed for efficacy of ICIs therapy. Results: TMB and CNA showed optimized combination for the prognosis of most metastatic cancer types, patients with TMB^lowCNA^low showed better survival. In the predictive analysis, both TMB and CNA were independent predictive factors for ICI therapy. Remarkably, when TMB and CNA were jointly analyzed, those with TMB^highCNA^low showed favorable responses to ICI therapy. Meanwhile, TMB^highCNA^low as a new biomarker showed better prediction for ICI efficacy compared with either TMB-high or CNA-low alone. Furthermore, analysis of the non-ICI treated MSK pan-cancer cohort supported that the joint stratification of TMB and CNA can be used to categorize tumors into distinct sensitivity to ICI therapy across pan-tumors. Conclusions: The combination of TMB and CNA can jointly stratify multiple metastatic tumors into groups with different prognosis and heterogenous clinical responses to ICI treatment. Patients with TMB^highCNA^low cancer can be an optimal subgroup for ICI therapy.

Microsatellite instability (MSI) has been approved as a pan-cancer biomarker for immune checkpoint blockade (ICB) therapy. However, current MSI identification methods are not available for all patients. We proposed an ensemble multiple instance deep learning model to predict microsatellite status based on histopathology images, and interpreted the pathomics-based model with multi-omics correlation.

Chemotherapy and radiotherapy predominantly improve the clinical outcomes of patients with human papillomavirus (HPV)-related head and neck squamous cell carcinoma (HNSCC). Whether this superiority goes on when treated with immune checkpoint inhibitors is still unclear. This study sought to determine the predictive value and potential mechanisms of HPV status for the treatment of programmed cell death 1 (PD-1)/ligand 1(PD-L1) inhibitors. We conducted an integrated analysis of the relationships between HPV status and PD-L1, tumor mutation burden (TMB) and inflammation-related immune cells and molecules, based on the analysis of repository databases and resected HNSCC specimens. The pooled analysis of overall survival (OS) and objective response rate (ORR) suggested that HPV-positive patients benefited more from PD-1/PD-L1 inhibitors than HPV-negative patients (OS: hazard ratio (HR) = 0.71, p = 0.02; ORR: 21.9% vs 14.1%, odds ratio (OR) = 1.79, p = 0.01). Analysis of public databases and resected HNSCC specimens revealed that HPV status was independent of PD-L1 expression and TMB in HNSCC. However, HPV infection significantly increased T-cell infiltration, immune effector cell activation and the diversity of T-cell receptors. Notably, HPV-positivity correlated with increased immune cytolytic activity and a T-cell-inflamed gene expression profile. This work provides evidence that HPV status can be used to predict the effectiveness of PD-1 inhibitors in HNSCC, independently of PD-L1 expression and TMB, and probably results from an inflamed immune microenvironment induced by HPV infection.