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Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer
Background: Cervical cancer (CC) is a major health threat to females, and distal metastasis is common in patients with advanced CC. Anoikis is necessary for the development of distal metastases. Understanding the mechanisms associated with anoikis in CC is essential to improve its survival rate. Met...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067583/ https://www.ncbi.nlm.nih.gov/pubmed/37021052 http://dx.doi.org/10.3389/fphar.2023.1135626 |
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author | Liang, Hao Xiang, Lan Wu, Huan Liu, Yang Tian, Wei Zeng, Jianhua |
author_facet | Liang, Hao Xiang, Lan Wu, Huan Liu, Yang Tian, Wei Zeng, Jianhua |
author_sort | Liang, Hao |
collection | PubMed |
description | Background: Cervical cancer (CC) is a major health threat to females, and distal metastasis is common in patients with advanced CC. Anoikis is necessary for the development of distal metastases. Understanding the mechanisms associated with anoikis in CC is essential to improve its survival rate. Methods: The expression matrix of long non-coding RNAs (lncRNAs) from cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients was extracted from The Cancer Genome Atlas (TCGA), and highly relevant anoikis-related lncRNAs (ARLs) were identified by the single sample gene set enrichment analysis (ssGSEA) method. ARLs-related molecular subtypes were discerned based on prognosis-related ARLs. ARLs-related prognostic risk score (APR_Score) was calculated and risk model was constructed using LASSO COX and COX models. In addition, we also assessed immune cell activity in the immune microenvironment (TME) for both subtypes and APR_Score groups. A nomogram was utilized for predicting improved clinical outcome. Finally, this study also discussed the potential of ARLs-related signatures in predicting response to immunotherapy and small molecular drugs. Results: Three ARLs-related subtypes were identified from TCGA-CESC (AC1, AC2, and AC3), with AC3 patients having the highest ARG scores, higher angiogenesis scores, and the worst prognosis. AC3 had lower immune cell scores in TME but higher immune checkpoint gene expression and higher potential for immune escape. Next, we constructed a prognostic risk model consisting of 7-ARLs. The APR_Score exhibited a greater robustness as an independent prognostic indicator in predicting prognosis, and the nomogram was a valuable tool for survival prediction. ARLs-related signatures emerged as a potential novel indicator for immunotherapy and small molecular drug selection. Conclusion: We firstly constructed novel ARLs-related signatures capable of predicting prognosis and offered novel ideas for therapy response in CC patients. |
format | Online Article Text |
id | pubmed-10067583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100675832023-04-04 Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer Liang, Hao Xiang, Lan Wu, Huan Liu, Yang Tian, Wei Zeng, Jianhua Front Pharmacol Pharmacology Background: Cervical cancer (CC) is a major health threat to females, and distal metastasis is common in patients with advanced CC. Anoikis is necessary for the development of distal metastases. Understanding the mechanisms associated with anoikis in CC is essential to improve its survival rate. Methods: The expression matrix of long non-coding RNAs (lncRNAs) from cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients was extracted from The Cancer Genome Atlas (TCGA), and highly relevant anoikis-related lncRNAs (ARLs) were identified by the single sample gene set enrichment analysis (ssGSEA) method. ARLs-related molecular subtypes were discerned based on prognosis-related ARLs. ARLs-related prognostic risk score (APR_Score) was calculated and risk model was constructed using LASSO COX and COX models. In addition, we also assessed immune cell activity in the immune microenvironment (TME) for both subtypes and APR_Score groups. A nomogram was utilized for predicting improved clinical outcome. Finally, this study also discussed the potential of ARLs-related signatures in predicting response to immunotherapy and small molecular drugs. Results: Three ARLs-related subtypes were identified from TCGA-CESC (AC1, AC2, and AC3), with AC3 patients having the highest ARG scores, higher angiogenesis scores, and the worst prognosis. AC3 had lower immune cell scores in TME but higher immune checkpoint gene expression and higher potential for immune escape. Next, we constructed a prognostic risk model consisting of 7-ARLs. The APR_Score exhibited a greater robustness as an independent prognostic indicator in predicting prognosis, and the nomogram was a valuable tool for survival prediction. ARLs-related signatures emerged as a potential novel indicator for immunotherapy and small molecular drug selection. Conclusion: We firstly constructed novel ARLs-related signatures capable of predicting prognosis and offered novel ideas for therapy response in CC patients. Frontiers Media S.A. 2023-03-20 /pmc/articles/PMC10067583/ /pubmed/37021052 http://dx.doi.org/10.3389/fphar.2023.1135626 Text en Copyright © 2023 Liang, Xiang, Wu, Liu Tian and Zeng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Liang, Hao Xiang, Lan Wu, Huan Liu, Yang Tian, Wei Zeng, Jianhua Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer |
title | Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer |
title_full | Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer |
title_fullStr | Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer |
title_full_unstemmed | Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer |
title_short | Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer |
title_sort | anoikis-related long non-coding rna signatures to predict prognosis and small molecular drug response in cervical cancer |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067583/ https://www.ncbi.nlm.nih.gov/pubmed/37021052 http://dx.doi.org/10.3389/fphar.2023.1135626 |
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