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A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients

PURPOSE: We aimed to establish a cholesterogenic gene signature to predict the prognosis of young breast cancer (BC) patients and then verified it using cell line experiments. METHODS: In the bioinformatic section, transcriptional data and corresponding clinical data of young BC patients (age ≤ 45 y...

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Autores principales: Li, Xiaoping, Zhou, Chaorong, Qiu, Chaoran, Li, Weiwen, Yu, Qihe, Huang, Hui, Zhang, Yiwen, Zhang, Xin, Ren, Liangliang, Huang, Xin, Zhou, Qinghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9393010/
https://www.ncbi.nlm.nih.gov/pubmed/35999846
http://dx.doi.org/10.7717/peerj.13922
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author Li, Xiaoping
Zhou, Chaorong
Qiu, Chaoran
Li, Weiwen
Yu, Qihe
Huang, Hui
Zhang, Yiwen
Zhang, Xin
Ren, Liangliang
Huang, Xin
Zhou, Qinghua
author_facet Li, Xiaoping
Zhou, Chaorong
Qiu, Chaoran
Li, Weiwen
Yu, Qihe
Huang, Hui
Zhang, Yiwen
Zhang, Xin
Ren, Liangliang
Huang, Xin
Zhou, Qinghua
author_sort Li, Xiaoping
collection PubMed
description PURPOSE: We aimed to establish a cholesterogenic gene signature to predict the prognosis of young breast cancer (BC) patients and then verified it using cell line experiments. METHODS: In the bioinformatic section, transcriptional data and corresponding clinical data of young BC patients (age ≤ 45 years) were downloaded from The Cancer Genome Atlas (TCGA) database for training set. Differentially expressed genes (DEGs) were compared between tumour tissue (n = 183) and normal tissue (n = 30). By using univariate Cox regression and multi COX regression, a five-cholesterogenic-gene signature was established to predict prognosis. Subgroup analysis and external validations of GSE131769 from the Gene Expression Omnibus (GEO) were performed to verify the signature. Subsequently, in experiment part, cell experiments were performed to further verify the biological roles of the five cholesterogenic genes in BC. RESULTS: In the bioinformatic section, a total of 97 upregulated genes and 124 downregulated cholesterogenic genes were screened as DEGs in the TCGA for training the model. A risk scoring signature contained five cholesterogenic genes (risk score = −1.169 × GRAMD1C −0.992 × NFKBIA + 0.432 × INHBA + 0.261 × CD24 −0.839 × ACSS2) was established, which could differentiate the prognosis of young BC patients between high-risk and low-risk group (<0.001). The prediction value of chelesterogenic gene signature in excellent with AUC was 0.810 in TCGA dataset. Then the prediction value of the signature was verified in GSE131769 with P = 0.033. In experiment part, although the downregulation of CD24, GRAMD1C and ACSS2 did not significantly affect cell viability, NFKBIA downregulation promoted the viability, colony forming ability and invasion capability of BC cells, while INHBA downregulation had the opposite effects. CONCLUSION: The five-cholesterogenic-gene signature had independent prognostic value and robust reliability in predicting the prognosis of young BC patients. The cell experiment results suggested that NFKBIA played a protective role, while INHBA played the pro-cancer role in breast cancer.
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spelling pubmed-93930102022-08-22 A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients Li, Xiaoping Zhou, Chaorong Qiu, Chaoran Li, Weiwen Yu, Qihe Huang, Hui Zhang, Yiwen Zhang, Xin Ren, Liangliang Huang, Xin Zhou, Qinghua PeerJ Bioinformatics PURPOSE: We aimed to establish a cholesterogenic gene signature to predict the prognosis of young breast cancer (BC) patients and then verified it using cell line experiments. METHODS: In the bioinformatic section, transcriptional data and corresponding clinical data of young BC patients (age ≤ 45 years) were downloaded from The Cancer Genome Atlas (TCGA) database for training set. Differentially expressed genes (DEGs) were compared between tumour tissue (n = 183) and normal tissue (n = 30). By using univariate Cox regression and multi COX regression, a five-cholesterogenic-gene signature was established to predict prognosis. Subgroup analysis and external validations of GSE131769 from the Gene Expression Omnibus (GEO) were performed to verify the signature. Subsequently, in experiment part, cell experiments were performed to further verify the biological roles of the five cholesterogenic genes in BC. RESULTS: In the bioinformatic section, a total of 97 upregulated genes and 124 downregulated cholesterogenic genes were screened as DEGs in the TCGA for training the model. A risk scoring signature contained five cholesterogenic genes (risk score = −1.169 × GRAMD1C −0.992 × NFKBIA + 0.432 × INHBA + 0.261 × CD24 −0.839 × ACSS2) was established, which could differentiate the prognosis of young BC patients between high-risk and low-risk group (<0.001). The prediction value of chelesterogenic gene signature in excellent with AUC was 0.810 in TCGA dataset. Then the prediction value of the signature was verified in GSE131769 with P = 0.033. In experiment part, although the downregulation of CD24, GRAMD1C and ACSS2 did not significantly affect cell viability, NFKBIA downregulation promoted the viability, colony forming ability and invasion capability of BC cells, while INHBA downregulation had the opposite effects. CONCLUSION: The five-cholesterogenic-gene signature had independent prognostic value and robust reliability in predicting the prognosis of young BC patients. The cell experiment results suggested that NFKBIA played a protective role, while INHBA played the pro-cancer role in breast cancer. PeerJ Inc. 2022-08-18 /pmc/articles/PMC9393010/ /pubmed/35999846 http://dx.doi.org/10.7717/peerj.13922 Text en ©2022 Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Li, Xiaoping
Zhou, Chaorong
Qiu, Chaoran
Li, Weiwen
Yu, Qihe
Huang, Hui
Zhang, Yiwen
Zhang, Xin
Ren, Liangliang
Huang, Xin
Zhou, Qinghua
A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients
title A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients
title_full A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients
title_fullStr A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients
title_full_unstemmed A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients
title_short A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients
title_sort cholesterogenic gene signature for predicting the prognosis of young breast cancer patients
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9393010/
https://www.ncbi.nlm.nih.gov/pubmed/35999846
http://dx.doi.org/10.7717/peerj.13922
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