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Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
TNF-Alpha Pathway Alternation Predicts Survival of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer
Anqi Lin1, Hongman Zhang1, Hui Meng1
1Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Abstract:
Translational research on immune checkpoint inhibitors (ICIs) has been underway. However, in the unselected population, only a few patients benefit from ICIs. Therefore, screening predictive markers of ICI efficacy has become the current focus of attention. We collected mutation and clinical data from an ICI-treated non-small cell lung cancer (NSCLC) cohort. Then, a univariate Cox regression model was used to analyze the relationship between tumor necrosis factor α signaling mutated (TNFα-MT) and the prognosis of immunotherapy for NSCLC. We retrospectively collected 36 NSCLC patients (local-cohort) from the Zhujiang Hospital of Southern Medical University and performed whole-exome sequencing (WES). The expression and mutation data of The Cancer Genome Atlas (TCGA)-NSCLC cohort were used to explore the association between TNFα-MT and the immune microenvironment. A local cohort was used to validate the association between TNFα-MT and immunogenicity. TNFα-MT was associated with significantly prolonged overall survival (OS) in NSCLC patients after receiving immunotherapy. Additionally, TNFα-MT is related to high immunogenicity (tumor mutational burden, neoantigen load, and DNA damage response signaling mutations) and enrichment of infiltrating immune cells. These results suggest that TNFα-MT may serve as a potential clinical biomarker for NSCLC patients receiving ICIs.
Insights
Tumor necrosis factor alpha signaling mutations (TNFα-MT) predict better outcomes for non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). This mutation is linked to higher tumor immunogenicity and improved survival, suggesting its potential as a predictive biomarker.
Area of Science:
- Oncology
- Immunology
- Genetics
Background:
- Immune checkpoint inhibitors (ICIs) show limited efficacy in unselected non-small cell lung cancer (NSCLC) populations.
- Identifying predictive biomarkers for ICI response is crucial for improving patient outcomes.
Purpose of the Study:
- To investigate the association between tumor necrosis factor alpha signaling mutations (TNFα-MT) and the efficacy of immunotherapy in NSCLC.
- To explore TNFα-MT as a potential predictive biomarker for ICI treatment in NSCLC.
Main Methods:
- Retrospective analysis of 36 NSCLC patients treated with ICIs, including whole-exome sequencing.
- Utilized The Cancer Genome Atlas (TCGA)-NSCLC cohort for expression and mutation data analysis.
- Employed univariate Cox regression to assess the relationship between TNFα-MT and overall survival (OS).
Main Results:
- TNFα-MT was significantly associated with prolonged OS in NSCLC patients receiving immunotherapy.
- TNFα-MT correlated with increased immunogenicity, including higher tumor mutational burden and neoantigen load.
- TNFα-MT was linked to enrichment of infiltrating immune cells in the tumor microenvironment.
Conclusions:
- TNFα-MT may serve as a promising predictive biomarker for NSCLC patients undergoing ICI therapy.
- The presence of TNFα-MT suggests a more immunogenic tumor profile, potentially explaining improved response to immunotherapy.
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