Mass spectrometry-based serum proteomic signature as a potential biomarker for survival in patients with non-small cell lung cancer receiving immunotherapy.

BACKGROUND: VeriStrat test is a serum assay which uses a mass spectrometry (MS)-based proteomic signature derived from machine learning. It is currently used as a prognostic marker for patients with non-small cell lung cancer (NSCLC) receiving chemotherapy. However, little is known about its role for NSCLC patients receiving immune checkpoint inhibitors (ICIs). METHODS: This is a retrospective study that includes 47 patients with advanced stage NSCLC without an activating EGFR mutation, who underwent the VeriStrat test from 2016 to 2018. Spectra from blood samples were evaluated to assign patients into the VeriStrat 'Good' (VS-G) or VeriStrat 'Poor' (VS-P) risk group. The clinical outcomes of 32 patients who received programmed cell death 1 (PD-1) inhibitors nivolumab or pembrolizumab were analyzed by VeriStrat status. RESULTS: The VS-G group demonstrated significantly higher progression-free survival (PFS) and overall survival (OS) compared to the VS-P group among overall NSCLC patients regardless of treatment (median PFS of 7.1 vs. 4.2 months, P=0.013, and median OS, not reached vs. 17.2 months, P=0.012). Among NSCLC patients treated with ICIs, VS-G classification was associated with significantly increased PFS in comparison to VS-P classification (median PFS of 6.2 vs. 3.0 months, P=0.012), while the differences in OS trended towards significance (median OS, not reached vs. 16.5 months P=0.076). Multivariate analysis showed that the VeriStrat status was significantly correlated with PFS and OS in NSCLC patients treated with ICIs (P=0.017, P=0.034, respectively). CONCLUSIONS: MS-based serum proteomic signature has potential as a biomarker for survival outcome in NSCLC patients receiving immunotherapy.

Clinical and Immunological Implications of Frameshift Mutations in Lung Cancer.

INTRODUCTION: Presently, programmed death ligand 1 is the most commonly used biomarker to predict response to immune checkpoint inhibitors (ICIs) in NSCLC. Owing to its several limitations, there is continuous search for more precise and reliable markers. Frameshift mutations by insertion or deletion (fsindels) are suggested to induce more immunogenic tumor-specific neoantigens, conferring better response to ICIs. Positive correlation of fsindels with ICI response has been studied in melanoma and renal cell carcinoma. We investigated the implication of fsindels in the clinical outcomes and immune landscape of patients with NSCLC treated with ICIs. METHODS: We utilized The Cancer Genome Atlas data set to analyze tumor mutational burden, neoantigen burden, and immune landscape in relation to fsindel status. In addition, utilizing the clinical data from 122 patients treated with ICIs, we evaluated the influence of fsindels on disease response rates and survival outcomes. RESULTS: A positive correlation between fsindel burden and tumor mutational burden and activated CD4/CD8 T-cell infiltration was shown. Presence of fsindels was also associated with significant prolongation of progression-free survival in patients treated with ICIs (median 6.2 versus 2.7 months [p = 0.01]). In addition, significant differences in the overall response rates (26% versus 12% [p = 0.04]) and disease control rates (68% versus 48% [p = 0.02]) were observed in patients with fsindels. CONCLUSION: Our findings suggest that fsindels may have a predictive role for ICI response in NSCLC.

Epithelial-mesenchymal transition (EMT) signature is inversely associated with T-cell infiltration in non-small cell lung cancer (NSCLC).

Epithelial-mesenchymal transition (EMT) is able to drive metastasis during progression of multiple cancer types, including non-small cell lung cancer (NSCLC). As resistance to immunotherapy has been associated with EMT and immune exclusion in melanoma, it is important to understand alterations to T-cell infiltration and the tumor microenvironment during EMT in lung adenocarcinoma and squamous cell carcinoma. We conducted an integrated analysis of the immune landscape in NSCLCs through EMT scores derived from a previously established 16 gene signature of canonical EMT markers. EMT was associated with exclusion of immune cells critical in the immune response to cancer, with significantly lower infiltration of CD4 T-cells in lung adenocarcinoma and CD4/CD8 T-cells in squamous cell carcinoma. EMT was also associated with increased expression of multiple immunosuppressive cytokines, including IL-10 and TGF-ß. Furthermore, overexpression of targetable immune checkpoints, such as CTLA-4 and TIM-3 were associated with EMT in both NSCLCs. An association may exist between immune exclusion and EMT in NSCLC. Further investigation is merited as its mechanism is not completely understood and a better understanding of this association could lead to the development of biomarkers that could accurately predict response to immunotherapy.