Multi-omics profiling reveals tumor microenvironment characteristics linked to immunotherapy response and prognosis in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) patients frequently develop resistance to immunotherapy, underscoring the need for novel predictive biomarkers and a deeper understanding of the underlying mechanisms. In this study, we integrated bulk and single-cell transcriptomic analyses across 31 datasets to elucidate the immune infiltration features distinguishing immunotherapy responders from non-responders. We identified elevated infiltration of ZNF683 + CD8 + T cells as a crucial subset enriched in responders, with ZNF683 expression serving as a robust indicator of immunotherapy responsiveness. By screening 296 algorithm combinations, a ZNF683 + CD8 + T cell-related Riskscore (ZNFRS) was constructed using the optimal StepCox[forward] + Ridge combination, which demonstrated superior prognostic capability for lung adenocarcinoma patients. High-ZNFRS tumors exhibited a "cold" tumor microenvironment (TME) characterized by reduced immune infiltration, immunotherapy resistance, and enhanced SPP1 signaling. In vivo experiments revealed that anti-SPP1 treatment suppressed tumor growth, restored CD8 + T cell effector function, inhibited M2-like macrophage polarization, and significantly enhanced the efficacy of anti-PD-1 therapy. Our findings highlight ZNF683 as a promising biomarker for immunotherapy response and establish the ZNFRS as a robust prognostic indicator. Furthermore, targeting the SPP1 pathway, identified as a key driver of immunosuppression in high-risk patients, represents a viable strategy to enhance anti-PD-1 therapy efficacy in NSCLC.

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Publication Details

Journal
npj Precision Oncology
Published
2026-05-11
DOI
https://doi.org/10.1038/s41698-026-01474-2
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-omics profiling reveals tumor microenvironment characteristics linked to immunotherapy response and prognosis in non-small cell lung cancer

Menglong Zhang, Fancai Lai, Liangyu Zhang, Xi Zhang et al.
npj Precision Oncology
Cancer Immunotherapy and Biomarkers
article

Multi-omics profiling reveals tumor microenvironment characteristics linked to immunotherapy response and prognosis in non-small cell lung cancer

Menglong Zhang, Fancai Lai, Liangyu Zhang, Xi Zhang, Junkai Wen, Jianshen Zeng, Y Y Lin, Bin Zheng, Zhiyi Tian, Zhenyuan Yang
article en

Abstract

Non-small cell lung cancer (NSCLC) patients frequently develop resistance to immunotherapy, underscoring the need for novel predictive biomarkers and a deeper understanding of the underlying mechanisms. In this study, we integrated bulk and single-cell transcriptomic analyses across 31 datasets to elucidate the immune infiltration features distinguishing immunotherapy responders from non-responders. We identified elevated infiltration of ZNF683 + CD8 + T cells as a crucial subset enriched in responders, with ZNF683 expression serving as a robust indicator of immunotherapy responsiveness. By screening 296 algorithm combinations, a ZNF683 + CD8 + T cell-related Riskscore (ZNFRS) was constructed using the optimal StepCox[forward] + Ridge combination, which demonstrated superior prognostic capability for lung adenocarcinoma patients. High-ZNFRS tumors exhibited a "cold" tumor microenvironment (TME) characterized by reduced immune infiltration, immunotherapy resistance, and enhanced SPP1 signaling. In vivo experiments revealed that anti-SPP1 treatment suppressed tumor growth, restored CD8 + T cell effector function, inhibited M2-like macrophage polarization, and significantly enhanced the efficacy of anti-PD-1 therapy. Our findings highlight ZNF683 as a promising biomarker for immunotherapy response and establish the ZNFRS as a robust prognostic indicator. Furthermore, targeting the SPP1 pathway, identified as a key driver of immunosuppression in high-risk patients, represents a viable strategy to enhance anti-PD-1 therapy efficacy in NSCLC.

npj Precision OncologyVol. 10(1)
Fujian University of Traditional Chinese Medicine (CN), Fujian Medical University (CN), Education Department of Fujian Province (CN), First Affiliated Hospital of Fujian Medical University (CN), Union Hospital (CN), Fuzhou University (CN)
Fujian Provincial Health Technology Project
Good health and well-being
Openalex Percentile: Top 8%
Cancer Immunotherapy and Biomarkers
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