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Background <p>Immune checkpoint inhibitors (ICIs) plus chemotherapy have become the first-line standard therapy for non-oncogene addicted advanced non-small cell lung cancer (NSCLC) patients. There is a lack of reliable biomarkers to predict treatment outcomes. This study aimed to identify relevant lipids that can predict treatment outcomes in NSCLC patients receiving first-line ICIs plus chemotherapy via lipidomics.</p> Method <p>We recruited non-oncogene addicted advanced NSCLC patients receiving first-line ICI plus chemotherapy to participate in this study. According to the progression free survival (PFS) criteria, these patients were categorized into a response (R) group (PFS ≥ 12 months) and a non-response (NR) group (PFS &lt; 12 months). Plasma samples were collected from patients before the start of treatment for untargeted lipidomics and semi-targeted lipidomics analysis.</p> Results <p>A total of 49 patients were included in this study. We screened 13 differential lipids according to <i>P</i> &lt; 0.05 and AUC &gt; 0.7. Multivariate logistic regression further identified FA-18:2 (linoleic acid, LA), PE-P-34:2, and PI-40:4 as independent predictors. The triple-lipid biomarker panel demonstrated showed good predictive performance with an AUC of 0.878. We further investigated the role of LA, a pivotal lipid involved in immune regulation, in animal and cellular models and explored its potential in enhancing NSCLC immunotherapy. Our results showed that LA synergistically enhanced PD-1 inhibitor efficacy in the Lewis lung cancer mouse model, significantly suppressing tumor growth, and downregulating PD-L1 protein expression in both tumor cells and tumor tissues.</p> Conclusion <p>We established the lipidomics-based predictive model for the efficacy of non-oncogene addicted advanced NSCLC patients treated with first-line chemotherapy plus ICI and elucidated a novel mechanism whereby LA potentiates immunotherapy by regulating the PD-L1 pathway. These findings provide dual theoretical foundations for personalized treatment strategies and the development of immunoadjuvants.</p>

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Lipidomics reveals biomarkers of the efficacy of first-line ICI therapy combined with chemotherapy in NSCLC

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月10日

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  • Jia Yu,
  • Hanyan Xu,
  • Fen Xiong,
  • Xiling Liu,
  • Meng Lingfei,
  • Hongchang Gao,
  • Yuping Li

摘要

Background

Immune checkpoint inhibitors (ICIs) plus chemotherapy have become the first-line standard therapy for non-oncogene addicted advanced non-small cell lung cancer (NSCLC) patients. There is a lack of reliable biomarkers to predict treatment outcomes. This study aimed to identify relevant lipids that can predict treatment outcomes in NSCLC patients receiving first-line ICIs plus chemotherapy via lipidomics.

Method

We recruited non-oncogene addicted advanced NSCLC patients receiving first-line ICI plus chemotherapy to participate in this study. According to the progression free survival (PFS) criteria, these patients were categorized into a response (R) group (PFS ≥ 12 months) and a non-response (NR) group (PFS < 12 months). Plasma samples were collected from patients before the start of treatment for untargeted lipidomics and semi-targeted lipidomics analysis.

Results

A total of 49 patients were included in this study. We screened 13 differential lipids according to P < 0.05 and AUC > 0.7. Multivariate logistic regression further identified FA-18:2 (linoleic acid, LA), PE-P-34:2, and PI-40:4 as independent predictors. The triple-lipid biomarker panel demonstrated showed good predictive performance with an AUC of 0.878. We further investigated the role of LA, a pivotal lipid involved in immune regulation, in animal and cellular models and explored its potential in enhancing NSCLC immunotherapy. Our results showed that LA synergistically enhanced PD-1 inhibitor efficacy in the Lewis lung cancer mouse model, significantly suppressing tumor growth, and downregulating PD-L1 protein expression in both tumor cells and tumor tissues.

Conclusion

We established the lipidomics-based predictive model for the efficacy of non-oncogene addicted advanced NSCLC patients treated with first-line chemotherapy plus ICI and elucidated a novel mechanism whereby LA potentiates immunotherapy by regulating the PD-L1 pathway. These findings provide dual theoretical foundations for personalized treatment strategies and the development of immunoadjuvants.