Preliminary construction and validation of a prognostic prediction model for cervical cancer based on tumor mechanics-related genes.

Authors

Lu Zhang, Haonan Fu, Yali Feng, Jianxin Tian, Xue Gao, Yuhong Shang

Published in

Frontiers in oncology. Volume 16. Pages 1841456. Epub Jun 03, 2026.

Abstract

Cervical cancer (CC) is the fourth most prevalent malignancy among women. The present study employed bioinformatics analyses to identify tumor mechanics-related genes (TMRGs), establish a prognostic model, and investigate the association of tumor stiffness with pivotal genes utilizing clinical samples.
mRNA data from the Genotype-Tissue Expression project (GTEx), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) were analyzed to identify tumor mechanics-related differentially expressed genes. A prognostic model was constructed via least absolute shrinkage and selection operator (LASSO) regression and validated in theGSE44001cohort. In the clinical component, individuals with CC were enrolled; the preoperative strain ratio (SR), reflecting tumor stiffness, was evaluated by strain elastography, and the expression of matrix metalloproteinase-1 (MMP1) in tumor tissues was evaluated using immunohistochemistry (IHC).
A prognostic model was constructed using seven key genes: MMP1, DES, ARSJ, NT5E, P4HA3, CLMP, and SMARCA1. This model efficiently stratified individuals into high- and low-risk subgroups. The two groups exhibited distinct gene mutation landscapes, varying degrees of immune cell infiltration, and differential responses to chemotherapy. Spearman correlation analysis indicated a moderate positive link between MMP1 IHC scores and SR values (r=0.418, P = 0.012).Compared to the low-expression group, individuals with high MMP1expressionexhibited significantly elevated SR values(P<0.05).
The TMRG-based prognostic model demonstrated notable discriminative capacity. Clinical validation revealed a preliminary association between tumor stiffness and MMP1 expression in CC tissues, offering a new perspective for risk stratification and clinical evaluation in this malignancy.

PMID:
42318471
Bibliographic data and abstract were imported from PubMed on 19 Jun 2026.

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