Identification of a novel signature in progression of non-small cell lung cancer based on HdWGCNA and in vitro validation

Sep 22, 2026

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Non-small cell lung cancer remains a major cause of cancer-related mortality, yet the mechanisms underlying its progression and tumor-intrinsic behavior are not fully resolved. Using single-cell RNA sequencing from GEO, high-dimensional weighted gene co-expression network analysis identified gene modules linked to NSCLC clinical stages. A prognostic three-gene signature was built and evaluated with bulk RNA-seq from TCGA-LUAD, revealing worse overall survival in high-risk patients and distinct immune microenvironment features. In vitro assays further showed SEC61G promotes tumor proliferation and migration via WNT/β-catenin signaling.

LanguageEnglish

CategoryHealthcare

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Pages12

Reading Time30 min

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Abstract

Background

Methods

Results

Keywords

Zhang et al. BMC Medical Genomics (2026) 19:54 [https://doi.org/10.1186/s12920-026-02328-3](https://doi.org/10.1186/s12920-026-02328-3) BMC Medical Genomics RESEARCH Open Access Identification of a novel signature in progression of non-small cell lung cancer based on HdWGCNA and in vitro validation Kunpeng Zhang 1,2†, Wenqiang Xia3†, Yi Li4†, Bowen Shi3* and Weiwei Yang 1,2* Abstract Background Lung cancer is the predominant contributor to cancer-induced mortality, with non-small cell lung cancer (NSCLC) constituting the majority. However, the intricacies of tumorigenesis and progression in this context remain incompletely understood. Methods Utilizing single-cell RNA sequencing data retrieved from the GEO database, we performed highdimensional weighted gene co-expression network analysis to identify pivotal gene modules exhibiting the highest correlation with the clinical stages of NSCLC patients. Subsequently, we formulated a novel prognostic three-gene signature, subjecting it to thorough analysis using bulk RNA sequencing data obtained from theTCGA-LUAD dataset. Results A tumor-intrinsic prognostic signature, comprising SEC61G, NPTN, and ALDOA, emerged from our investigation. The risk score derived from this gene signature revealed significantly poorer overall survival among patients in the high-risk group. Patients in different risk groups exhibited distinct immune statuses, with those in the low-risk group likely to benefit more from immunotherapy. Furthermore, in vitro experiments demonstrated that SEC61G facilitates tumor proliferation and migration with the activation ofthe WNT/β-Catenin signaling pathway. Conclusion Our study unveiled a novel tumor-intrinsic gene signature, shedding light on improved prognostication for NSCLC and facilitating risk-stratified management. Keywords HdWGCNA, Immune microenvironment, Immunotherapy, Non-small cell lung cancer, Prognostic signature †Kunpeng Zhang, Wenqiang Xia andYi Li contributed equally to this work. *Correspondence: Bowen Shi [bowen_shi@126.com](bowen_shi@126.com)[ ](bowen_shi@126.com)Weiwei Yang [CaylaYang@126.com](CaylaYang@126.com) 1Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China 2Shanghai Engineering Research Center of Lung Transplantation, Shanghai, China 3Department of Thoracic Surgery, Naval Medical Center, Shanghai, China 4Department of Orthopaedic, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China Background Lung cancer is the second most prevalent malignancy globally, representing the primary cause of cancer-related mortality [1]. Non-small cell lung cancer (NSCLC), constituting the predominant form of lung cancer, with lung adenocarcinoma (LAUD) emerging as the prevailing histologic subtype within NSCLC [2]. In recent years, immunotherapy has brought significant clinical advantages to patients with NSCLC. Immunomodulatory interventions targeting PD-1 or PD-L1 signaling have exhibited substantial success across various cancers by fostering anti-tumor immune responses [3]. Despite significant © The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceed

FAQs

What data sources were used to build and validate the prognostic signature?

Single-cell RNA sequencing data were retrieved from GEO, and high-dimensional weighted gene co-expression network analysis was performed. The resulting prognostic signature was then analyzed using bulk RNA sequencing data from TCGA-LUAD.

Which genes compose the tumor-intrinsic prognostic signature?

The signature consists of SEC61G, NPTN, and ALDOA.

How does the signature relate to patient prognosis and immune status?

Patients in the high-risk group showed significantly poorer overall survival. Low-risk patients exhibited immune statuses suggesting a greater likelihood of benefiting from immunotherapy.

Sep 22, 2026

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