HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas

BACKGROUND: Gliomas are the most frequent type of central nervous system tumor, accounting for more than 70% of all malignant CNS tumors. Recent research suggests that the hyaluronan-mediated motility receptor (HMMR) could be a novel potential tumor prognostic marker. Furthermore, mounting data has...

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Autores principales: Zhu, Huaxin, Tan, Jiacong, Pan, Xinyi, Ouyang, Hengyang, Zhang, Zhixiong, Li, Meihua, Zhao, Yeyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903609/
https://www.ncbi.nlm.nih.gov/pubmed/36750807
http://dx.doi.org/10.1186/s12885-023-10596-w
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author Zhu, Huaxin
Tan, Jiacong
Pan, Xinyi
Ouyang, Hengyang
Zhang, Zhixiong
Li, Meihua
Zhao, Yeyu
author_facet Zhu, Huaxin
Tan, Jiacong
Pan, Xinyi
Ouyang, Hengyang
Zhang, Zhixiong
Li, Meihua
Zhao, Yeyu
author_sort Zhu, Huaxin
collection PubMed
description BACKGROUND: Gliomas are the most frequent type of central nervous system tumor, accounting for more than 70% of all malignant CNS tumors. Recent research suggests that the hyaluronan-mediated motility receptor (HMMR) could be a novel potential tumor prognostic marker. Furthermore, mounting data has highlighted the important role of ceRNA regulatory networks in a variety of human malignancies. The complexity and behavioural characteristics of HMMR and the ceRNA network in gliomas, on the other hand, remained unknown. METHODS: Transcriptomic expression data were collected from TCGA, GTEx, GEO, and CGGA database.The relationship between clinical variables and HMMR was analyzed with the univariate and multivariate Cox regression. Kaplan–Meier method was used to assess OS. TCGA data are analyzed and processed, and the correlation results obtained were used to perform GO, GSEA, and ssGSEA. Potentially interacting miRNAs and lncRNAs were predicted by miRWalk and StarBase. RESULTS: HMMR was substantially expressed in gliomas tissues compared to normal tissues. Multivariate analysis revealed that high HMMR expression was an independent predictive predictor of OS in TCGA and CGGA. Functional enrichment analysis found that HMMR expression was associated with nuclear division and cell cycle. Base on ssGSEA analysis, The levels of HMMR expression in various types of immune cells differed significantly. Bioinformatics investigation revealed the HEELPAR-hsa-let-7i-5p-RRM2 ceRNA network, which was linked to gliomas prognosis. And through multiple analysis, the good predictive performance of HELLPAR/RRM2 axis for gliomas patients was confirmed. CONCLUSION: This study provides multi-layered and multifaceted evidence for the importance of HMMR and establishes a HMMR-related ceRNA (HEELPAR-hsa-let-7i-5p-RRM2) overexpressed network related to the prognosis of gliomas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10596-w.
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spelling pubmed-99036092023-02-08 HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas Zhu, Huaxin Tan, Jiacong Pan, Xinyi Ouyang, Hengyang Zhang, Zhixiong Li, Meihua Zhao, Yeyu BMC Cancer Research BACKGROUND: Gliomas are the most frequent type of central nervous system tumor, accounting for more than 70% of all malignant CNS tumors. Recent research suggests that the hyaluronan-mediated motility receptor (HMMR) could be a novel potential tumor prognostic marker. Furthermore, mounting data has highlighted the important role of ceRNA regulatory networks in a variety of human malignancies. The complexity and behavioural characteristics of HMMR and the ceRNA network in gliomas, on the other hand, remained unknown. METHODS: Transcriptomic expression data were collected from TCGA, GTEx, GEO, and CGGA database.The relationship between clinical variables and HMMR was analyzed with the univariate and multivariate Cox regression. Kaplan–Meier method was used to assess OS. TCGA data are analyzed and processed, and the correlation results obtained were used to perform GO, GSEA, and ssGSEA. Potentially interacting miRNAs and lncRNAs were predicted by miRWalk and StarBase. RESULTS: HMMR was substantially expressed in gliomas tissues compared to normal tissues. Multivariate analysis revealed that high HMMR expression was an independent predictive predictor of OS in TCGA and CGGA. Functional enrichment analysis found that HMMR expression was associated with nuclear division and cell cycle. Base on ssGSEA analysis, The levels of HMMR expression in various types of immune cells differed significantly. Bioinformatics investigation revealed the HEELPAR-hsa-let-7i-5p-RRM2 ceRNA network, which was linked to gliomas prognosis. And through multiple analysis, the good predictive performance of HELLPAR/RRM2 axis for gliomas patients was confirmed. CONCLUSION: This study provides multi-layered and multifaceted evidence for the importance of HMMR and establishes a HMMR-related ceRNA (HEELPAR-hsa-let-7i-5p-RRM2) overexpressed network related to the prognosis of gliomas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-10596-w. BioMed Central 2023-02-07 /pmc/articles/PMC9903609/ /pubmed/36750807 http://dx.doi.org/10.1186/s12885-023-10596-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhu, Huaxin
Tan, Jiacong
Pan, Xinyi
Ouyang, Hengyang
Zhang, Zhixiong
Li, Meihua
Zhao, Yeyu
HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas
title HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas
title_full HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas
title_fullStr HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas
title_full_unstemmed HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas
title_short HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas
title_sort hellpar/rrm2 axis related to hmmr as novel prognostic biomarker in gliomas
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903609/
https://www.ncbi.nlm.nih.gov/pubmed/36750807
http://dx.doi.org/10.1186/s12885-023-10596-w
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