Dataset Information

The Landscape of Immunotherapy Resistance in NSCLC.

ABSTRACT: Lung cancer is the leading cause of cancer mortality worldwide. Immunotherapy has demonstrated clinically significant benefit for non-small-cell lung cancer, but innate (primary) or acquired resistance remains a challenge. Criteria for a uniform clinical definition of acquired resistance have been recently proposed in order to harmonize the design of future clinical trials. Several mechanisms of resistance are now well-described, including the lack of tumor antigens, defective antigen presentation, modulation of critical cellular pathways, epigenetic changes, and changes in the tumor microenvironment. Host-related factors, such as the microbiome and the state of immunity, have also been examined. New compounds and treatment strategies are being developed to target these mechanisms with the goal of maximizing the benefit derived from immunotherapy. Here we review the definitions of resistance to immunotherapy, examine its underlying mechanisms and potential corresponding treatment strategies. We focus on recently published clinical trials and trials that are expected to deliver results soon. Finally, we gather insights from recent preclinical discoveries that may translate to clinical application in the future.

SUBMITTER: Frisone D

PROVIDER: S-EPMC9066487 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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The Landscape of Immunotherapy Resistance in NSCLC.

Frisone Daniele D Friedlaender Alex A Addeo Alfredo A Tsantoulis Petros P

Frontiers in oncology 20220420

Lung cancer is the leading cause of cancer mortality worldwide. Immunotherapy has demonstrated clinically significant benefit for non-small-cell lung cancer, but innate (primary) or acquired resistance remains a challenge. Criteria for a uniform clinical definition of acquired resistance have been recently proposed in order to harmonize the design of future clinical trials. Several mechanisms of resistance are now well-described, including the lack of tumor antigens, defective antigen presentati ...[more]

PMID: 35515125

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Project description:Background: Lung cancer has the highest morbidity and mortality rate among types of malignant tumors, and as such, research into prolonging the survival time of patients is vital. The emergence of immune checkpoint inhibitors (ICIs) has greatly improved the survival of patients with non-small cell lung cancer (NSCLC), however, the lack of effective biomarkers to predict the prognosis of immunotherapy has made it difficult to maximize the benefits. T cell receptor (TCR) is one of the most important components for recognizing tumor cells, and with this study we aim to clarify the relationship between TCR coexpression and the prognosis of NSCLC patients receiving immunotherapy. Methods: Univariate COX regression, logistics regression, and KM survival analysis were used to evaluate the relationship between TCR coexpression and the prognosis of immunotherapy. Additionally, CIBERSORT, Gene Set Enrichment Analysis (GSEA), and single-sample GSEA (ssGSEA) algorithms were used to evaluate the tumor immune microenvironment (TIME) of NSCLC patients. Results: Univariate Cox regression analysis showed that the TCR coexpression signature can be used as a clinical prognostic indicator for NSCLC patients receiving immunotherapy (p = 0.0205). In addition, those in the NSCLC group with a high TCR coexpression signature had significantly improved progression-free survival (PFS) (p = 0.014). In the ICI treatment cohort (GSE35640). In addition, there was a high infiltration of CD8+T cells, activated memory CD4+T cells, and M1 macrophages in the TIME of those with a high TCR coexpression signature. The results of pathway enrichment analysis showed that patients with a high TCR coexpression signature had significantly activated signal pathways such as lymphocyte proliferation and activation, chemokine binding, and inflammatory cytokine production. Also, we found that patients with a high TCR coexpression signature had an elevated T cell inflammation gene expression profile (GEP). Conclusion: We show that the TCR coexpression signature may be useful as a new biomarker for the prognosis of NSCLC patients undergoing immunotherapy, with high signatures indicating better treatment response. Additionally, we found that patients with a high TCR coexpression signature had tumor immune microenvironments with beneficial anti-tumor characteristics.

Dataset Information

The Landscape of Immunotherapy Resistance in NSCLC.

Publications

The Landscape of Immunotherapy Resistance in NSCLC.

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