Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer

Overview

Journal Comput Math Methods Med

Publisher Hindawi

Specialty Medical Informatics

Date 2022 Mar 29

PMID 35345518

Authors

Xingling Wang

Jing Wang

Mingxin Yu

Affiliations

Soon will be listed here.

Abstract

Background: As one of the main causes leading to female cancer deaths, cervical cancer shows malignant features of local infiltration and invasion into adjacent organs and tissues. This study was designed to categorize novel molecular subtypes according to cervical cancer invasion and screen reliable prognostic markers.

Methods: Invasion-related gene sets and expression profiles of invasion-related genes were collected from the CancerSEA database and The Cancer Genome Atlas (TCGA), respectively. Samples were clustered by nonnegative matrix factorization (NMF) to obtain different molecular subgroups, immune microenvironment characteristics of which were further systematically compared. Limma was employed to screen differentially expressed gene sets in different subtypes, followed by Lasso analysis for dimension reduction. Multivariate and univariate Cox regression analysis was performed to determine prognostic characteristics. The Kaplan-Meier test showed the prognostic differences of patients with different risks. Additionally, receiver operating characteristic (ROC) curves were applied to validate the prognostic model performance. A nomogram model was developed using clinical and prognostic characteristics of cervical cancer, and its prediction accuracy was reflected by calibration curve.

Results: This study filtered 19 invasion-related genes with prognosis significance in cervical cancer and 2 molecular subtypes (C1, C2). Specifically, the C1 subtype had an unfavorable prognosis, which was associated with the activation of the TGF-beta signaling pathway, focal adhesion, and PI3K-Akt signaling pathway. 875 differentially expressed genes were screened, and 8 key genes were finally retained by the dimension reduction analysis. An 8-gene signature was established as an independent factor predictive of the prognosis of cervical cancer. The signature performance was even stronger when combined with N stage.

Conclusion: Based on invasion-related genes, the present study categorized two cervical cancer subtypes with distinct TME characteristics and established an 8-gene marker that can accurately and independently predict the prognosis of cervical cancer.

Citing Articles

RNA-binding proteins signature is a favorable biomarker of prognosis, immunotherapy and chemotherapy response for cervical cancer.

Chen X, Dong X, Li H, Wu T, Liu H, Wu J Cancer Cell Int. 2024; 24(1):80.

PMID: 38383371 PMC: 10882920. DOI: 10.1186/s12935-024-03257-w.

Retracted: Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer.

Methods In Medicine C Comput Math Methods Med. 2023; 2023:9853237.

PMID: 37475921 PMC: 10356526. DOI: 10.1155/2023/9853237.

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