Molecular typing of stage IB non-small-cell lung cancer for precision medicine

Background The optimal postoperative management of stage IB non-small-cell lung cancer (NSCLC) remains controversial due to significant heterogeneity. This study aimed to establish a molecular classification for stage IB NSCLC to guide precision medicine. Methods We performed consensus clustering of transcriptomic profiles from TCGA-NSCLC (training set, n=119) and validated in GSE31210 (n=53). Molecular subtypes were compared with stage IA/II patients for clinical significance. Differentially expressed genes were analyzed using LASSO regression to identify biomarkers. Functional studies were conducted using patient-derived organoids (PDOs), cell lines, and tissue specimens. Results Stage IB NSCLC was divided into two subtypes (IB1 and IB2) with significantly different disease-free survival (DFS). IB1 patients showed DFS similar to stage IA, while IB2 patients exhibited DFS comparable to stage II (especially IIB). Carboxypeptidase D (CPD) was identified as a key biomarker capable of distinguishing high- and low-risk patients (AUC=0.874 in validation). CPD was overexpressed in tumor tissues and promoted proliferation and migration in PDOs and cell lines. Conclusion This molecular classification effectively stratifies stage IB NSCLC into low-risk (IB1, observation suitable) and high-risk (IB2, adjuvant therapy warranted) subgroups. CPD serves as a promising biomarker for clinical risk stratification.

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Journal
Frontiers in Oncology
Published
2026-03-13
DOI
https://doi.org/10.3389/fonc.2026.1605054
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00
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article

Molecular typing of stage IB non-small-cell lung cancer for precision medicine

Yijun Zhou, G. Z. Li, Ying Feng, Xiaohong Ji et al.
Frontiers in Oncology
Ferroptosis and cancer prognosis
article

Molecular typing of stage IB non-small-cell lung cancer for precision medicine

Yijun Zhou, G. Z. Li, Ying Feng, Xiaohong Ji, J. Zhu, Y. Xiong, Shaowei Xin, Zitong Wan, Kaiqi Wei, Miaomiao Wen, Jiao Zhang, Jie Lei, Xiaoyan Li
article en

Abstract

Background The optimal postoperative management of stage IB non-small-cell lung cancer (NSCLC) remains controversial due to significant heterogeneity. This study aimed to establish a molecular classification for stage IB NSCLC to guide precision medicine. Methods We performed consensus clustering of transcriptomic profiles from TCGA-NSCLC (training set, n=119) and validated in GSE31210 (n=53). Molecular subtypes were compared with stage IA/II patients for clinical significance. Differentially expressed genes were analyzed using LASSO regression to identify biomarkers. Functional studies were conducted using patient-derived organoids (PDOs), cell lines, and tissue specimens. Results Stage IB NSCLC was divided into two subtypes (IB1 and IB2) with significantly different disease-free survival (DFS). IB1 patients showed DFS similar to stage IA, while IB2 patients exhibited DFS comparable to stage II (especially IIB). Carboxypeptidase D (CPD) was identified as a key biomarker capable of distinguishing high- and low-risk patients (AUC=0.874 in validation). CPD was overexpressed in tumor tissues and promoted proliferation and migration in PDOs and cell lines. Conclusion This molecular classification effectively stratifies stage IB NSCLC into low-risk (IB1, observation suitable) and high-risk (IB2, adjuvant therapy warranted) subgroups. CPD serves as a promising biomarker for clinical risk stratification.

Frontiers in OncologyVol. 16
Shanxi Medical University (CN), Chinese PLA General Hospital (CN), Chinese General Hospital College of Nursing and Liberal Arts (PH), Zhengzhou University (CN), United States Air Force (US), Shaanxi Provincial People's Hospital (CN), Zhoukou Normal University (CN), Logistics Management Institute (United States) (US), Tang Du Hospital (CN), Shanxi Provincial People’s Hospital (CN), Air Force Medical University (CN)
Good health and well-being
Openalex Percentile: Top 24%
Ferroptosis and cancer prognosis
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