What question did this study set out to answer?

To evaluate how integrating genomics, proteomics, and metabolomics improves the prediction of immune checkpoint inhibitor response in non-small cell lung cancer.

December 1, 2025Lung Cancer Targets and TherapyOpen Access

Integrated Multi-Omics Approaches for Predicting Immune Checkpoint Inhibitor Response in NSCLC – Insights From Genomics, Proteomics, and Metabolomics

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Implication

Systematic review uncovers multi-omics biomarkers of immune checkpoint inhibitor efficacy in NSCLC, highlighting pathways for personalized stratification.

Key Points

To evaluate how integrating genomics, proteomics, and metabolomics improves the prediction of immune checkpoint inhibitor response in non-small cell lung cancer.
Systematic search across PubMed, ClinicalTrials.gov, and Google Scholar from 2016 through January 2025.
Identified and reviewed 51 eligible studies comprising 33 genomic, 9 proteomic, and 9 metabolomic investigations.
Evaluated included studies using a standardized 0–14 evidence rubric assessing effect robustness, validation, cohort size, and clinical endpoint relevance.
Genomic resistance to immune checkpoint inhibitors is linked to EGFR mutations, ALK/RET/ROS1 fusions, and KRAS co-mutations with STK11, KEAP1, or SMARCA4 in immune-cold tumors, whereas KRAS/TP53 co-mutations, NOTCH alterations, and BRAF V600E correlate with immune-hot signatures and responsiveness.
Proteomic markers predicting treatment benefit include CXCL9, CXCL10, apoptotic regulators (CASP8, FASLG), and soluble checkpoint proteins, whereas acute-phase proteins (SAA1/2, S100A8/9) correspond with resistance.
Metabolomic profiling links elevated baseline tryptophan, histidine, and short-chain fatty acids to favorable outcomes, whereas increased 3-hydroxyanthranilic acid, pyruvate, and immunosuppressive IDO pathway metabolites correlate with resistance.

Cite This Study

A 2025 study studied this question.

synapsesocial.com/papers/6a8160be9ec2426b2722ec12 https://doi.org/10.2147/lctt.s539777

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Implication

Systematic review uncovers multi-omics biomarkers of immune checkpoint inhibitor efficacy in NSCLC, highlighting pathways for personalized stratification.

Integrated Multi-Omics Approaches for Predicting Immune Checkpoint Inhibitor Response in NSCLC – Insights From Genomics, Proteomics, and Metabolomics

Discussion

Member takes

Implication

Key Points

Cite This Study

Integrated Multi-Omics Approaches for Predicting Immune Checkpoint Inhibitor Response in NSCLC – Insights From Genomics, Proteomics, and Metabolomics

Discussion

Member takes

Implication

Key Points

Cite This Study

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