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Background <p>Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Despite advancements in treatment, drug resistance and limited therapeutic efficacy persist, underscoring the urgent need for novel and mechanistically informed therapeutic strategies. Identifying genetically supported drug targets may accelerate the development of precision therapies in NSCLC.</p> Methods <p>We implemented an integrative multi-omics framework combining single-cell RNA sequencing (scRNA-seq), genome-wide association studies (GWAS), and molecular quantitative trait locus (QTL) datasets including expression (eQTL), protein (pQTL), and DNA methylation (mQTL) QTLs. Druggable candidates were systematically evaluated using a suite of Mendelian randomization (MR) approaches—including summary data-based MR (SMR), generalized SMR (GSMR), and genetic risk score (GRS) analysis. Epigenetic regulation and downstream signaling were further explored through mediation MR analysis.</p> Results <p><i>C4BPA</i>, a complement-regulatory macromolecule, emerged as a risk factor for NSCLC across multiple MR models, with consistent findings validated at both transcriptomic and proteomic levels. Epigenetic activation of <i>C4BPA</i> via DNA methylation was observed, and <i>C4BPA</i> expression was shown to promote NSCLC progression through the inflammatory chemokine <i>CCL8</i> signaling axis. Sensitivity analyses confirmed the robustness of association inference.</p> Conclusions <p>Our findings identify <i>C4BPA</i> as a genetically validated and biologically plausible therapeutic target for NSCLC. This study demonstrates the power of integrating single-cell transcriptomics with population-scale omics and association inference to uncover actionable targets, offering a scalable framework for advancing precision oncology in lung cancer.</p>

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Identification of C4BPA as a genetically informed drug target in NSCLC: an integrative single-cell and multi-omics study based on the druggable genes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月6日

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  • Zhihan Xiao,
  • Xinji Liu,
  • Wei Tang,
  • Yan Lv,
  • Tongyu Zhang,
  • Xu Zhan,
  • Qihang Sun,
  • Willis Wasonga Omindo,
  • Qi Wang,
  • Ruijie Zhang,
  • Wei Ping,
  • Ni Zhang

摘要

Background

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Despite advancements in treatment, drug resistance and limited therapeutic efficacy persist, underscoring the urgent need for novel and mechanistically informed therapeutic strategies. Identifying genetically supported drug targets may accelerate the development of precision therapies in NSCLC.

Methods

We implemented an integrative multi-omics framework combining single-cell RNA sequencing (scRNA-seq), genome-wide association studies (GWAS), and molecular quantitative trait locus (QTL) datasets including expression (eQTL), protein (pQTL), and DNA methylation (mQTL) QTLs. Druggable candidates were systematically evaluated using a suite of Mendelian randomization (MR) approaches—including summary data-based MR (SMR), generalized SMR (GSMR), and genetic risk score (GRS) analysis. Epigenetic regulation and downstream signaling were further explored through mediation MR analysis.

Results

C4BPA, a complement-regulatory macromolecule, emerged as a risk factor for NSCLC across multiple MR models, with consistent findings validated at both transcriptomic and proteomic levels. Epigenetic activation of C4BPA via DNA methylation was observed, and C4BPA expression was shown to promote NSCLC progression through the inflammatory chemokine CCL8 signaling axis. Sensitivity analyses confirmed the robustness of association inference.

Conclusions

Our findings identify C4BPA as a genetically validated and biologically plausible therapeutic target for NSCLC. This study demonstrates the power of integrating single-cell transcriptomics with population-scale omics and association inference to uncover actionable targets, offering a scalable framework for advancing precision oncology in lung cancer.