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Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses

Kidney renal clear cell carcinoma (KIRC) is among the major causes of cancer-caused mortality around the world. Transient receptor potential channels (TRPs), due to their role in various human diseases, might become potential drug targets in cancer. The mRNA expression, copy number variation, single...

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Autores principales: Ren, Jie, Yuan, Qihang, Liu, Jifeng, Zhong, Lei, Li, Hanshuo, Wu, Guangzhen, Chen, Feng, Tang, Qizhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277847/
https://www.ncbi.nlm.nih.gov/pubmed/35831825
http://dx.doi.org/10.1186/s12920-022-01312-x
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author Ren, Jie
Yuan, Qihang
Liu, Jifeng
Zhong, Lei
Li, Hanshuo
Wu, Guangzhen
Chen, Feng
Tang, Qizhen
author_facet Ren, Jie
Yuan, Qihang
Liu, Jifeng
Zhong, Lei
Li, Hanshuo
Wu, Guangzhen
Chen, Feng
Tang, Qizhen
author_sort Ren, Jie
collection PubMed
description Kidney renal clear cell carcinoma (KIRC) is among the major causes of cancer-caused mortality around the world. Transient receptor potential channels (TRPs), due to their role in various human diseases, might become potential drug targets in cancer. The mRNA expression, copy number variation, single-nucleotide variation, prognostic values, drug sensitivity, and pathway regulation of TRPs were studied across cancer types. The ArrayExpress and The Cancer Genome Atlas (TCGA) databases were used to retrieve KIRC samples. Simultaneously, training, internal, and external cohorts were grouped. In KIRC, a prognostic signature with superior survival prediction in contrast with other well-established signatures was created after a stepwise screening of optimized genes linked to TRPs using univariate Cox, weighted gene co-expression network analysis, multivariate Cox, and least absolute shrinkage and selection operator regression analyses. Subsequent to the determination of risk levels, the variations in the expression of immune checkpoint genes, tumor mutation burden, and immune subtypes and response between low-risk and high-risk subgroups were studied using a variety of bioinformatics algorithms, including ESTIMATE, XCELL, EPIC, CIBERSORT-ABS, CIBERSORT, MCPCOUNTER, TIMER, and QUANTISEQ. Gene set enrichment analysis helped in the identification of abnormal pathways across the low- and high-risk subgroups. Besides, high-risk KIRC patients might benefit from ABT888, AZD6244, AZD7762, Bosutinib, Camptothecin, CI1040, JNK inhibitor VIII, KU55933, Lenalidomide, Nilotinib, PLX4720, RO3306, Vinblastine, and ZM.447439; however, low-risk populations might benefit from Bicalutamide, FH535, and OSI906. Finally, calibration curves were used to validate the nomogram with a satisfactory predictive survival probability. In conclusion, this research provides useful insight that can aid and guide clinical practice and scientific research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01312-x.
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spelling pubmed-92778472022-07-14 Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses Ren, Jie Yuan, Qihang Liu, Jifeng Zhong, Lei Li, Hanshuo Wu, Guangzhen Chen, Feng Tang, Qizhen BMC Med Genomics Research Kidney renal clear cell carcinoma (KIRC) is among the major causes of cancer-caused mortality around the world. Transient receptor potential channels (TRPs), due to their role in various human diseases, might become potential drug targets in cancer. The mRNA expression, copy number variation, single-nucleotide variation, prognostic values, drug sensitivity, and pathway regulation of TRPs were studied across cancer types. The ArrayExpress and The Cancer Genome Atlas (TCGA) databases were used to retrieve KIRC samples. Simultaneously, training, internal, and external cohorts were grouped. In KIRC, a prognostic signature with superior survival prediction in contrast with other well-established signatures was created after a stepwise screening of optimized genes linked to TRPs using univariate Cox, weighted gene co-expression network analysis, multivariate Cox, and least absolute shrinkage and selection operator regression analyses. Subsequent to the determination of risk levels, the variations in the expression of immune checkpoint genes, tumor mutation burden, and immune subtypes and response between low-risk and high-risk subgroups were studied using a variety of bioinformatics algorithms, including ESTIMATE, XCELL, EPIC, CIBERSORT-ABS, CIBERSORT, MCPCOUNTER, TIMER, and QUANTISEQ. Gene set enrichment analysis helped in the identification of abnormal pathways across the low- and high-risk subgroups. Besides, high-risk KIRC patients might benefit from ABT888, AZD6244, AZD7762, Bosutinib, Camptothecin, CI1040, JNK inhibitor VIII, KU55933, Lenalidomide, Nilotinib, PLX4720, RO3306, Vinblastine, and ZM.447439; however, low-risk populations might benefit from Bicalutamide, FH535, and OSI906. Finally, calibration curves were used to validate the nomogram with a satisfactory predictive survival probability. In conclusion, this research provides useful insight that can aid and guide clinical practice and scientific research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01312-x. BioMed Central 2022-07-13 /pmc/articles/PMC9277847/ /pubmed/35831825 http://dx.doi.org/10.1186/s12920-022-01312-x Text en © The Author(s) 2022 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
Ren, Jie
Yuan, Qihang
Liu, Jifeng
Zhong, Lei
Li, Hanshuo
Wu, Guangzhen
Chen, Feng
Tang, Qizhen
Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses
title Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses
title_full Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses
title_fullStr Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses
title_full_unstemmed Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses
title_short Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses
title_sort identifying the role of transient receptor potential channels (trps) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277847/
https://www.ncbi.nlm.nih.gov/pubmed/35831825
http://dx.doi.org/10.1186/s12920-022-01312-x
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