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Shared patterns of dysregulated gene expression across squamous cell carcinomas unveil predictors for prognosis and drug sensitivity
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  • Published: 10 March 2026

Shared patterns of dysregulated gene expression across squamous cell carcinomas unveil predictors for prognosis and drug sensitivity

  • Danke Wang1,
  • Xu Li1,
  • Jiaqi Zhou1,
  • Huangbo Yuan1,
  • Peipei Gao1,
  • Yucan Li1,
  • Yixin Zeng1,
  • Chen Suo2,3,4 &
  • …
  • Xingdong Chen1,2,5,6 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Cancer
  • Cancer genomics
  • Gene ontology
  • Transcriptomics

Abstract

Despite extensive multi-omics studies on squamous cell carcinomas (SCCs) across different organs, the shared transcriptional regulatory mechanisms that driving SCC remain unclear. This study systematically identified common and distinct transcriptomic alterations in SCCs, highlighting key genes and pathways with prognostic and therapeutic relevance. By integrating large-scale gene expression data from SCC tumors and adjacent normal tissues, we revealed dysregulated gene expression patterns (DGEPs) and quantified their similarity across SCCs through correlation and regression analyses. Gene co-expression network analysis identified SCC-associated modules and hub genes, whose biological and clinical significance was further explored through subtype analysis and prognostic modeling. Our findings show that SCCs from the head and neck, esophagus, and cervix share highly similar DGEPs and regulatory networks, whereas lung and skin SCCs exhibit more distinct molecular characteristics. Key processes such as epithelial-mesenchymal transition, extracellular matrix remodeling, and immune-related pathways were strongly linked to SCC prognosis. Moreover, a six-gene prognostic signature (COL1A1, MMP1, SERPINE1, KRT6A, IGF2BP3, and SPP1) demonstrated robust predictive power for clinical outcomes and therapy response. These findings provide insights into SCC progression and potential therapeutic targets.

Data and codes availability

All data used in this study can be downloaded from the public database. Raw gene expression microarray data can be downloaded from GEO database, accession numbers are recorded in Table S1. Raw RNA-seq data can be download from ENA (accession numbers are recorded in Table S2). Gene expression data matrix of tumor samples and clinical messages of SCC patients can be downloaded from TCGA (Projects of TCGA-ESCA, TCGA-CESC, TCGA-HNSC) database and GEO database (accession number: GSE5362575). Data Table S1–S4, preprocessed data and code required to reproduce the analyses presented in this study are publicly available at https://github.com/WangDanke/Shared_DGEP_SCCs. The repository contains comprehensive scripts covering raw data preprocessing, downstream analyses, and figure generation, as well as the finalized processed data matrices used in key analyses.

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Acknowledgements

Thanks to the efforts of all people involved in this work. Thanks to the GEO, ENA and TCGA databases for providing valuable datasets.

Funding

We acknowledge financial supports from the National Natural Science Foundation of China (grant numbers: 82073637, 82122060, 82473700), Science and Technology Innovation 2030 Major Projects (grant number: 2023ZD0510000), National Key Research and Development program of China (grant number: 2023YFC2508001), Shanghai Municipal Science and Technology Major Project (grant numbers: ZD2021CY001, 2023SHZDZX02).

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Authors and Affiliations

  1. State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 20032, China

    Danke Wang, Xu Li, Jiaqi Zhou, Huangbo Yuan, Peipei Gao, Yucan Li, Yixin Zeng & Xingdong Chen

  2. Fudan University Taizhou Institute of Health Sciences, Taizhou, 225300, Jiangsu, China

    Chen Suo & Xingdong Chen

  3. Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 20032, China

    Chen Suo

  4. Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 20032, China

    Chen Suo

  5. National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China

    Xingdong Chen

  6. Yiwu Research Institute of Fudan University, Yiwu, 322000, Zhejiang, China

    Xingdong Chen

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Contributions

Conceptualization: X.C., D.W., X.L.Methodology: D.W., X.L., J.Z., Y.H., P.G., C.S., X.C.Data collection and analysis: D.W.Supervision: X.C., C.S.Writing—original draft: D.W.Writing—review & editing: D.W., X.L., J.Z., Y.H., P.G., Y.L., YZ., C.S., X.C.

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Correspondence to Chen Suo or Xingdong Chen.

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Wang, D., Li, X., Zhou, J. et al. Shared patterns of dysregulated gene expression across squamous cell carcinomas unveil predictors for prognosis and drug sensitivity. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41052-x

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  • Received: 25 June 2025

  • Accepted: 17 February 2026

  • Published: 10 March 2026

  • DOI: https://doi.org/10.1038/s41598-026-41052-x

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Keywords

  • Squamous cell carcinomas
  • Transcriptome
  • Epithelial-mesenchymal transition
  • Immunosuppression
  • Survival
  • Drug
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