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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月11日

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  • Liangyu Zhang,
  • Jianshen Zeng,
  • Junkai Wen,
  • Zhenyuan Yang,
  • Zhiyi Tian,
  • Menglong Zhang,
  • Xun Zhang,
  • Bin Zheng,
  • Yilin Lin,
  • Fancai Lai

摘要

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.