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

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 reliabl...

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Detalles Bibliográficos
Autores principales: Wang, Xingling, Wang, Jing, Yu, Mingxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957037/
https://www.ncbi.nlm.nih.gov/pubmed/35345518
http://dx.doi.org/10.1155/2022/1902289
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author Wang, Xingling
Wang, Jing
Yu, Mingxin
author_facet Wang, Xingling
Wang, Jing
Yu, Mingxin
author_sort Wang, Xingling
collection PubMed
description 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.
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spelling pubmed-89570372022-03-27 Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer Wang, Xingling Wang, Jing Yu, Mingxin Comput Math Methods Med Research Article 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. Hindawi 2022-03-18 /pmc/articles/PMC8957037/ /pubmed/35345518 http://dx.doi.org/10.1155/2022/1902289 Text en Copyright © 2022 Xingling Wang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Xingling
Wang, Jing
Yu, Mingxin
Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer
title Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer
title_full Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer
title_fullStr Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer
title_full_unstemmed Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer
title_short Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer
title_sort identification and validation of invasion-related molecular subtypes and prognostic features for cervical cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957037/
https://www.ncbi.nlm.nih.gov/pubmed/35345518
http://dx.doi.org/10.1155/2022/1902289
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