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Background <p>Non-small cell lung cancer (NSCLC), the predominant subtype of lung cancer, contributes greatly to cancer-related mortality worldwide. Although inhibitors of programmed cell death protein 1 (PD-1) and its ligand PD-L1 have markedly improved patient outcomes, treatment resistance remains a substantial clinical challenge, underscoring the need for more effective predictive biomarkers. This study aimed to identify novel biomarkers for predicting treatment efficacy and clinical prognosis by systematically analyzing serum protein profiles of patients with divergent immunotherapy responses using four-dimensional data-independent acquisition (4D-DIA) proteomics integrated with the DB4000 platform.</p> Results <p>A total of 49 differentially expressed proteins were identified between treatment-resistant and treatment-sensitive patients, with Slit Guidance Ligand 1 (SLIT1) exhibiting the most pronounced downregulation (log₂[fold-change] ≈ − 2.29, <i>P</i> = 0.0419). In an independent validation cohort, enzyme-linked immunosorbent assay indicated that SLIT1 expression was significantly higher in resistant patients than in sensitive patients (<i>P</i> &lt; 0.0001). Furthermore, elevated SLIT1 expression was independently associated with shorter progression-free survival. A prognostic model integrating SLIT1 with other clinical variables demonstrated excellent discriminative performance (area under the curve = 0.964, 95% confidence interval: 0.929–0.998). Single-cell transcriptomic analysis further revealed a significant enrichment of SLIT1 expression within myeloid-lineage cells, particularly in M2-polarized macrophages (<i>P</i> = 0.0396), suggesting its involvement in modulating an immunosuppressive tumor microenvironment that may underlie treatment resistance.</p> Conclusions <p>By employing an integrated multiomics framework, this study validated serum SLIT1 as a pivotal biomarker for predicting resistance to PD-1/PD-L1 inhibitors in patients with NSCLC and concurrently elucidated its correlation with an immunosuppressive tumor microenvironment. These findings not only offer a potential predictive tool for clinical application but also lay the groundwork for future mechanistic investigations and the development of optimized therapeutic strategies.</p>

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Identification and validation of serum SLIT1 as a biomarker for predicting anti-PD-1/PD-L1 resistance 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14日

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  • Huisi Qiu,
  • Cong Peng,
  • Ziao Gao,
  • Huafeng Luo,
  • Ying Wei,
  • Yuanfeng Huang,
  • Danyang Chen,
  • Ying Song,
  • Kai Luo,
  • Hao Liu,
  • Xin Lin,
  • Qian Wang

摘要

Background

Non-small cell lung cancer (NSCLC), the predominant subtype of lung cancer, contributes greatly to cancer-related mortality worldwide. Although inhibitors of programmed cell death protein 1 (PD-1) and its ligand PD-L1 have markedly improved patient outcomes, treatment resistance remains a substantial clinical challenge, underscoring the need for more effective predictive biomarkers. This study aimed to identify novel biomarkers for predicting treatment efficacy and clinical prognosis by systematically analyzing serum protein profiles of patients with divergent immunotherapy responses using four-dimensional data-independent acquisition (4D-DIA) proteomics integrated with the DB4000 platform.

Results

A total of 49 differentially expressed proteins were identified between treatment-resistant and treatment-sensitive patients, with Slit Guidance Ligand 1 (SLIT1) exhibiting the most pronounced downregulation (log₂[fold-change] ≈ − 2.29, P = 0.0419). In an independent validation cohort, enzyme-linked immunosorbent assay indicated that SLIT1 expression was significantly higher in resistant patients than in sensitive patients (P < 0.0001). Furthermore, elevated SLIT1 expression was independently associated with shorter progression-free survival. A prognostic model integrating SLIT1 with other clinical variables demonstrated excellent discriminative performance (area under the curve = 0.964, 95% confidence interval: 0.929–0.998). Single-cell transcriptomic analysis further revealed a significant enrichment of SLIT1 expression within myeloid-lineage cells, particularly in M2-polarized macrophages (P = 0.0396), suggesting its involvement in modulating an immunosuppressive tumor microenvironment that may underlie treatment resistance.

Conclusions

By employing an integrated multiomics framework, this study validated serum SLIT1 as a pivotal biomarker for predicting resistance to PD-1/PD-L1 inhibitors in patients with NSCLC and concurrently elucidated its correlation with an immunosuppressive tumor microenvironment. These findings not only offer a potential predictive tool for clinical application but also lay the groundwork for future mechanistic investigations and the development of optimized therapeutic strategies.