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Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma

Purpose: Several RAB family genes have been studied extensively and proven to play pivotal roles in the occurrence and development of certain cancers. Here, we explored commonly expressed RAB family genes in humans and their prognostic significance using bioinformatics, and then identified potential...

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Autores principales: Lin, Shitong, Cao, Canhui, Meng, Yifan, Wu, Ping, Gao, Peipei, Zhi, Wenhua, Peng, Ting, Wu, Peng, Gui, Lingli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7260355/
https://www.ncbi.nlm.nih.gov/pubmed/32432324
http://dx.doi.org/10.1042/BSR20201103
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author Lin, Shitong
Cao, Canhui
Meng, Yifan
Wu, Ping
Gao, Peipei
Zhi, Wenhua
Peng, Ting
Wu, Peng
Gui, Lingli
author_facet Lin, Shitong
Cao, Canhui
Meng, Yifan
Wu, Ping
Gao, Peipei
Zhi, Wenhua
Peng, Ting
Wu, Peng
Gui, Lingli
author_sort Lin, Shitong
collection PubMed
description Purpose: Several RAB family genes have been studied extensively and proven to play pivotal roles in the occurrence and development of certain cancers. Here, we explored commonly expressed RAB family genes in humans and their prognostic significance using bioinformatics, and then identified potential biomarkers of breast invasive carcinoma (BRCA). Materials and methods: The prognostic values (overall survival) of RAB family genes in BRCA were obtained using Gene Expression Profiling Interactive Analysis (GEPIA). The expression patterns of RAB family genes and their relationships with clinicopathological parameters in BRCA were measured using the ONCOMINE and UALCAN databases, respectively. Genetic mutations and survival analysis were investigated using the cBio Cancer Genomics Portal (c-BioPortal). Interacting genes of potential biomarkers were identified using STRING, and functional enrichment analyses were performed using FunRich v3.1.3. Results: In total, 64 RAB genes were identified and analyzed in our study. Results showed that RAB1B, RAB2A, and RAB18 were up-regulated and significantly associated with poor overall survival in BRCA. Furthermore, their higher expression was positively correlated with clinicopathological parameters (e.g. cancer stage and nodal metastasis status). DNA copy number amplifications and mRNA up-regulation were the main genetic mutations, and the altered group showed significantly poorer overall survival compared with the unaltered group. Functional enrichment analysis of RAB1B, RAB2A, and RAB18 indicated they were closely involved in GTPase activity. Conclusions: RAB1B, RAB2A, and RAB18 were up-regulated and significantly correlated with poor prognosis in BRCA. Thus, they could be applied as novel biomarkers of BRCA in future studies.
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spelling pubmed-72603552020-06-08 Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma Lin, Shitong Cao, Canhui Meng, Yifan Wu, Ping Gao, Peipei Zhi, Wenhua Peng, Ting Wu, Peng Gui, Lingli Biosci Rep Bioinformatics Purpose: Several RAB family genes have been studied extensively and proven to play pivotal roles in the occurrence and development of certain cancers. Here, we explored commonly expressed RAB family genes in humans and their prognostic significance using bioinformatics, and then identified potential biomarkers of breast invasive carcinoma (BRCA). Materials and methods: The prognostic values (overall survival) of RAB family genes in BRCA were obtained using Gene Expression Profiling Interactive Analysis (GEPIA). The expression patterns of RAB family genes and their relationships with clinicopathological parameters in BRCA were measured using the ONCOMINE and UALCAN databases, respectively. Genetic mutations and survival analysis were investigated using the cBio Cancer Genomics Portal (c-BioPortal). Interacting genes of potential biomarkers were identified using STRING, and functional enrichment analyses were performed using FunRich v3.1.3. Results: In total, 64 RAB genes were identified and analyzed in our study. Results showed that RAB1B, RAB2A, and RAB18 were up-regulated and significantly associated with poor overall survival in BRCA. Furthermore, their higher expression was positively correlated with clinicopathological parameters (e.g. cancer stage and nodal metastasis status). DNA copy number amplifications and mRNA up-regulation were the main genetic mutations, and the altered group showed significantly poorer overall survival compared with the unaltered group. Functional enrichment analysis of RAB1B, RAB2A, and RAB18 indicated they were closely involved in GTPase activity. Conclusions: RAB1B, RAB2A, and RAB18 were up-regulated and significantly correlated with poor prognosis in BRCA. Thus, they could be applied as novel biomarkers of BRCA in future studies. Portland Press Ltd. 2020-05-29 /pmc/articles/PMC7260355/ /pubmed/32432324 http://dx.doi.org/10.1042/BSR20201103 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
spellingShingle Bioinformatics
Lin, Shitong
Cao, Canhui
Meng, Yifan
Wu, Ping
Gao, Peipei
Zhi, Wenhua
Peng, Ting
Wu, Peng
Gui, Lingli
Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma
title Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma
title_full Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma
title_fullStr Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma
title_full_unstemmed Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma
title_short Comprehensive analysis of the value of RAB family genes in prognosis of breast invasive carcinoma
title_sort comprehensive analysis of the value of rab family genes in prognosis of breast invasive carcinoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7260355/
https://www.ncbi.nlm.nih.gov/pubmed/32432324
http://dx.doi.org/10.1042/BSR20201103
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