Development and Validation of a Gene Expression‐Based Prognostic Model for Patients With Small Cell Lung Cancer Treated With Chemotherapy
4 affiliations
- 1Department of Medical Oncology Sun Yat‐sen University Cancer Center Guangzhou China
- 2State Key Laboratory of Oncology in South China Guangdong Provincial Clinical Research Center for Cancer Sun Yat‐sen University Cancer Center Guangzhou China
- 3State Key Laboratory of Neurology and Oncology Drug Development Jiangsu Simcere Diagnostic Technology Co. Ltd Nanjing China
- 4Department of Intensive Care Unit Sun Yat‐sen University Cancer Center Guangzhou China
Abstract
Small cell lung cancer (SCLC) remains one of the most aggressive malignancies, with limited tools for predicting outcomes and guiding treatment. We developed an SCLC‐Predictive Risk Score (PRS) model for patients treated with chemotherapy using least absolute shrinkage and selection operator regression. The model comprised five genes and was developed in a training cohort of 50 patients using an innovative 795‐gene panel of tumor‐ and immune‐related genes analyzed on the NanoString nCounter platform. Gene expression was measured in routine clinical formalin‐fixed, paraffin‐embedded SCLC specimens, predominantly puncture specimens (36/50). The SCLC‐PRS model stratified patients into high‐risk (PRS‐H) and low‐risk (PRS‐L) groups; patients in the PRS‐H group had significantly worse overall survival (hazard ratio [HR] = 0.35, 95% confidence interval [CI]: 0.18–0.69; p = 0.002) and progression‐free survival (HR = 0.44, 95% CI: 0.23–0.84; p = 0.008). The prognostic performance of the model was externally validated in two independent cohorts (GSE60052, n = 38; George cohort, n = 47). Multivariate Cox analysis confirmed SCLC‐PRS as an independent prognostic factor. PRS‐L tumors exhibit a favorable tumor immune microenvironment, with increased CD45+ immune infiltration, reduced Tregs or exhausted CD8+ T cells, and upregulated antigen presentation (MHC‐I/II). Overall, the SCLC‐PRS model is an innovative, cross‐platform‐compatible, and clinically applicable prognostic tool with potential utility for risk stratification and personalized treatment.
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BibTeX
@article{liu2026development,
title = {{Development and Validation of a Gene Expression‐Based Prognostic Model for Patients With Small Cell Lung Cancer Treated With Chemotherapy}},
author = {Tingting Liu and Ting Zhou and Silang Mo and Minghui Ge and Wenjuan Ma and JianHua Zhan and Xueyuan Chen and Yuwen Yang and Yuanzhen Ma and Ningning Luo and Wanglong Deng and Yunjie Song and Ran Ding and Yan Huang and Yunpeng Yang and Wenfeng Fang and Dongsheng Chen and Li Zhang and Yuanyuan Zhao},
journal = {MedComm},
year = {2026},
month = nov,
doi = {10.1002/mco2.71118},
url = {https://europepmc.org/article/PMC/PMC13725213},
note = {CC BY},
}
RIS
TY - JOUR
TI - Development and Validation of a Gene Expression‐Based Prognostic Model for Patients With Small Cell Lung Cancer Treated With Chemotherapy
AU - Tingting Liu
AU - Ting Zhou
AU - Silang Mo
AU - Minghui Ge
AU - Wenjuan Ma
AU - JianHua Zhan
AU - Xueyuan Chen
AU - Yuwen Yang
AU - Yuanzhen Ma
AU - Ningning Luo
AU - Wanglong Deng
AU - Yunjie Song
AU - Ran Ding
AU - Yan Huang
AU - Yunpeng Yang
AU - Wenfeng Fang
AU - Dongsheng Chen
AU - Li Zhang
AU - Yuanyuan Zhao
PY - 2026
DA - 2026/11/01
JO - MedComm
DO - 10.1002/mco2.71118
UR - https://europepmc.org/article/PMC/PMC13725213
AB - Small cell lung cancer (SCLC) remains one of the most aggressive malignancies, with limited tools for predicting outcomes and guiding treatment. We developed an SCLC‐Predictive Risk Score (PRS) model for patients treated with chemotherapy using least absolute shrinkage and selection operator regression. The model comprised five genes and was developed in a training cohort of 50 patients using an innovative 795‐gene panel of tumor‐ and immune‐related genes analyzed on the NanoString nCounter platform. Gene expression was measured in routine clinical formalin‐fixed, paraffin‐embedded SCLC specimens, predominantly puncture specimens (36/50). The SCLC‐PRS model stratified patients into high‐risk (PRS‐H) and low‐risk (PRS‐L) groups; patients in the PRS‐H group had significantly worse overall survival (hazard ratio [HR] = 0.35, 95% confidence interval [CI]: 0.18–0.69; p = 0.002) and progression‐free survival (HR = 0.44, 95% CI: 0.23–0.84; p = 0.008). The prognostic performance of the model was externally validated in two independent cohorts (GSE60052, n = 38; George cohort, n = 47). Multivariate Cox analysis confirmed SCLC‐PRS as an independent prognostic factor. PRS‐L tumors exhibit a favorable tumor immune microenvironment, with increased CD45+ immune infiltration, reduced Tregs or exhausted CD8+ T cells, and upregulated antigen presentation (MHC‐I/II). Overall, the SCLC‐PRS model is an innovative, cross‐platform‐compatible, and clinically applicable prognostic tool with potential utility for risk stratification and personalized treatment.
SN - 2688-2663
ER -