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Background <p>Non-small cell lung cancer (NSCLC) is a prevalent and lethal malignancy. Although targeted therapies have improved clinical outcomes for patients with driver gene mutations, significant variability in treatment efficacy and the frequent development of acquired resistance remain significant challenges. There is an urgent need to identify reliable predictive biomarkers. This study aimed to evaluate the association between key molecular indicators—interferon-γ (IFN-γ), Ki-67, driver gene mutation abundance (MA), and lung cancer-specific combined tumor markers (LCTM)—and response to targeted therapy in advanced NSCLC, to develop a predictive model for personalized treatment.</p> Methods <p>In this retrospective study, 132 patients with advanced or locally advanced NSCLC harboring driver gene mutations (confirmed by NGS) and receiving targeted therapy were enrolled. Demographic and clinical data were collected, including serum levels of five tumor markers (CEA, NSE, SCCA, CYFRA21-1, Pro-GRP), Ki-67 expression, IFN-γ levels, and MA. Radiographic responses were assessed at 1, 3, and 6 months according to RECIST criteria. Statistical analyses included chi-square tests, Kaplan-Meier survival analysis, and multivariate Cox regression to evaluate associations between biomarkers and treatment response.</p> Results <p>The overall response rate was 52.5%. Response rates were significantly higher in patients with ≤ 2 LCTM components (76.8% vs. &gt; 2, p &lt; 0.001) and low Ki-67 expression (&lt; 5%, 72.4% vs. high, p = 0.013). Multivariate analysis confirmed LCTM (HR = 1.849, p = 0.026) and Ki-67 (HR = 1.768, p = 0.016) as independent predictors. Higher IFN-γ and lower MA were associated with favorable trends in responders.</p> Conclusion <p>High IFN-γ expression, low Ki-67 and MA levels, and ≤ 2 elevated LCTM components constitute a favorable biomarker profile for predicting response to targeted therapy in advanced NSCLC. These biomarkers could aid in predicting early response and therapeutic stratification. The proposed “driver-clone-dependent clone” co-regulation mechanism underscores the clinical value of multi-biomarker evaluation. Further multi-center prospective studies are warranted for validation.</p> Graphical Abstract <p></p>

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Prognostic and predictive value of a novel immuno-proliferative biomarker signature for targeted therapy efficacy in non-small cell lung cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月9日

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  • Wei Wei,
  • Hongzhen Wang,
  • Xin Han,
  • Rujun Lin,
  • Xiaolei Zhang,
  • Ruixiang Gao

摘要

Background

Non-small cell lung cancer (NSCLC) is a prevalent and lethal malignancy. Although targeted therapies have improved clinical outcomes for patients with driver gene mutations, significant variability in treatment efficacy and the frequent development of acquired resistance remain significant challenges. There is an urgent need to identify reliable predictive biomarkers. This study aimed to evaluate the association between key molecular indicators—interferon-γ (IFN-γ), Ki-67, driver gene mutation abundance (MA), and lung cancer-specific combined tumor markers (LCTM)—and response to targeted therapy in advanced NSCLC, to develop a predictive model for personalized treatment.

Methods

In this retrospective study, 132 patients with advanced or locally advanced NSCLC harboring driver gene mutations (confirmed by NGS) and receiving targeted therapy were enrolled. Demographic and clinical data were collected, including serum levels of five tumor markers (CEA, NSE, SCCA, CYFRA21-1, Pro-GRP), Ki-67 expression, IFN-γ levels, and MA. Radiographic responses were assessed at 1, 3, and 6 months according to RECIST criteria. Statistical analyses included chi-square tests, Kaplan-Meier survival analysis, and multivariate Cox regression to evaluate associations between biomarkers and treatment response.

Results

The overall response rate was 52.5%. Response rates were significantly higher in patients with ≤ 2 LCTM components (76.8% vs. > 2, p < 0.001) and low Ki-67 expression (< 5%, 72.4% vs. high, p = 0.013). Multivariate analysis confirmed LCTM (HR = 1.849, p = 0.026) and Ki-67 (HR = 1.768, p = 0.016) as independent predictors. Higher IFN-γ and lower MA were associated with favorable trends in responders.

Conclusion

High IFN-γ expression, low Ki-67 and MA levels, and ≤ 2 elevated LCTM components constitute a favorable biomarker profile for predicting response to targeted therapy in advanced NSCLC. These biomarkers could aid in predicting early response and therapeutic stratification. The proposed “driver-clone-dependent clone” co-regulation mechanism underscores the clinical value of multi-biomarker evaluation. Further multi-center prospective studies are warranted for validation.

Graphical Abstract