Integrated proteomics of FFPE tissues reveals that upregulation of GALNT2 and SEC24A across cervical disease stages correlates with aggressive phenotype and poor prognosis.
4 affiliations
- 1Department of Pathology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, No. 7, Weiwu Road, Jinshui District, Zhengzhou, Henan, China.
- 2Department of Pathology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
- 3Department of Outpatient Hysteroscopy Diagnosis and Treatment, The Fifth Affiliated Hospital of Zhengzhou University, No. 3 Kangfu Qianjie, Erqi District, Zhengzhou, Henan, China. [email protected].
- 4Department of Pathology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, No. 7, Weiwu Road, Jinshui District, Zhengzhou, Henan, China. [email protected].
Abstract
Objective
The objective of this investigation is to elucidate the molecular mechanisms underlying cervical carcinogenesis, encompassing the transition from precancerous lesions to invasive carcinoma, through the analysis of proteomic alterations and the identification of key driver proteins.Methods
A comprehensive high-throughput proteomic analysis was conducted on 66 Formalin-Fixed, Paraffin-Embedded (FFPE) tissue samples, which included normal cervix (NC), high-grade squamous intraepithelial lesion (HSIL), and cervical cancer (CC). The employed bioinformatics methodologies included differential expression analysis, unsupervised clustering, Weighted Gene Co-expression Network Analysis (WGCNA), and multi-criteria screening based on consistent upregulation, prognostic relevance, module co-expression, and corroboration from existing literature. Validation was performed utilizing immunohistochemistry and external transcriptomic data from the TCGA-CESC cohort (n = 304).Results
The analysis successfully identified over 9,000 proteins, revealing significant heterogeneity among the NC, HSIL, and CC groups. The differential expression analysis demonstrated a notable increase in glycolytic metabolism alongside a decrease in oxidative phosphorylation as the disease progresses from NC to HSIL and then to CC, coupled with dynamic reprogramming of immune-related pathways, including the complement cascade. Unsupervised clustering identified three distinct molecular subtypes, each characterized by unique metabolic and immune microenvironmental features. These subtypes were independently validated in the TCGA-CESC transcriptomic cohort, which recapitulated the prognostic gradient and confirmed the progressive upregulation of GALNT2 across the subtypes. WGCNA identified modules significantly associated with clinicopathological parameters, such as tumor size, differentiation, and invasion depth. Through integrated screening, GALNT2 and SEC24A were identified as critical candidate driver proteins; their elevated expression was correlated with poorer patient survival, with immunohistochemistry and transcriptomic data confirming their progressive upregulation throughout the carcinogenic process.Conclusion
This study offers a comprehensive proteomic overview of cervical cancer progression and identifies GALNT2 and SEC24A as crucial regulators of metabolic-immune interactions, thereby providing novel mechanistic insights and potential therapeutic targets for cervical cancer.
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BibTeX
@article{xie2026integrated,
title = {{Integrated proteomics of FFPE tissues reveals that upregulation of GALNT2 and SEC24A across cervical disease stages correlates with aggressive phenotype and poor prognosis.}},
author = {Qi Xie and Jingjing Wei and Yanling Zhang and Muyi Zhang and Kang Han and Shimeng Liu and Hongxiao Wang and Yuxue Zhang and Xiaoya Sun},
journal = {BMC cancer},
year = {2026},
month = aug,
doi = {10.1186/s12885-026-16745-1},
url = {https://europepmc.org/article/MED/43009853},
note = {CC BY},
}
RIS
TY - JOUR
TI - Integrated proteomics of FFPE tissues reveals that upregulation of GALNT2 and SEC24A across cervical disease stages correlates with aggressive phenotype and poor prognosis.
AU - Qi Xie
AU - Jingjing Wei
AU - Yanling Zhang
AU - Muyi Zhang
AU - Kang Han
AU - Shimeng Liu
AU - Hongxiao Wang
AU - Yuxue Zhang
AU - Xiaoya Sun
PY - 2026
DA - 2026/08/13
JO - BMC cancer
DO - 10.1186/s12885-026-16745-1
UR - https://europepmc.org/article/MED/43009853
AB - Objective The objective of this investigation is to elucidate the molecular mechanisms underlying cervical carcinogenesis, encompassing the transition from precancerous lesions to invasive carcinoma, through the analysis of proteomic alterations and the identification of key driver proteins.Methods A comprehensive high-throughput proteomic analysis was conducted on 66 Formalin-Fixed, Paraffin-Embedded (FFPE) tissue samples, which included normal cervix (NC), high-grade squamous intraepithelial lesion (HSIL), and cervical cancer (CC). The employed bioinformatics methodologies included differential expression analysis, unsupervised clustering, Weighted Gene Co-expression Network Analysis (WGCNA), and multi-criteria screening based on consistent upregulation, prognostic relevance, module co-expression, and corroboration from existing literature. Validation was performed utilizing immunohistochemistry and external transcriptomic data from the TCGA-CESC cohort (n = 304).Results The analysis successfully identified over 9,000 proteins, revealing significant heterogeneity among the NC, HSIL, and CC groups. The differential expression analysis demonstrated a notable increase in glycolytic metabolism alongside a decrease in oxidative phosphorylation as the disease progresses from NC to HSIL and then to CC, coupled with dynamic reprogramming of immune-related pathways, including the complement cascade. Unsupervised clustering identified three distinct molecular subtypes, each characterized by unique metabolic and immune microenvironmental features. These subtypes were independently validated in the TCGA-CESC transcriptomic cohort, which recapitulated the prognostic gradient and confirmed the progressive upregulation of GALNT2 across the subtypes. WGCNA identified modules significantly associated with clinicopathological parameters, such as tumor size, differentiation, and invasion depth. Through integrated screening, GALNT2 and SEC24A were identified as critical candidate driver proteins; their elevated expression was correlated with poorer patient survival, with immunohistochemistry and transcriptomic data confirming their progressive upregulation throughout the carcinogenic process.Conclusion This study offers a comprehensive proteomic overview of cervical cancer progression and identifies GALNT2 and SEC24A as crucial regulators of metabolic-immune interactions, thereby providing novel mechanistic insights and potential therapeutic targets for cervical cancer.
SN - 1471-2407
ER -