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Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy

BACKGROUND: Renal cell carcinoma (RCC) is the most common kidney cancer in adults. According to the histological features, it could be divided into several subtypes, of which the most common one is kidney renal clear cell carcinoma (KIRC), which contributed to more than 90% of cases for RCC and usua...

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Autores principales: Xiong, Xi, Chen, Chen, Yang, Jun, Ma, Li, Wang, Xiong, Zhang, Wei, Yuan, Yuan, Peng, Min, Li, Lili, Luo, Pengcheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684726/
https://www.ncbi.nlm.nih.gov/pubmed/36439501
http://dx.doi.org/10.3389/fonc.2022.1024956
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author Xiong, Xi
Chen, Chen
Yang, Jun
Ma, Li
Wang, Xiong
Zhang, Wei
Yuan, Yuan
Peng, Min
Li, Lili
Luo, Pengcheng
author_facet Xiong, Xi
Chen, Chen
Yang, Jun
Ma, Li
Wang, Xiong
Zhang, Wei
Yuan, Yuan
Peng, Min
Li, Lili
Luo, Pengcheng
author_sort Xiong, Xi
collection PubMed
description BACKGROUND: Renal cell carcinoma (RCC) is the most common kidney cancer in adults. According to the histological features, it could be divided into several subtypes, of which the most common one is kidney renal clear cell carcinoma (KIRC), which contributed to more than 90% of cases for RCC and usually ends with a dismal outcome. Previous studies suggested that basement membrane genes (BMGs) play a pivotal role in tumor development. However, the significance and prognostic value of BMGs in KIRC still wrap in the mist. METHODS: KIRC data were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. A prognostic risk score (PRS) model based on BMGs was established using univariate and least absolute shrinkage and selection operator (LASSO) and the Cox regression analysis was performed for prognostic prediction. The Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, receiver operating characteristic (ROC) curves, nomogram, and calibration curves were utilized to evaluate and validate the PRS model. All KIRC cases were divided into the high-risk score (HRS) group and the low-risk score (LRS) group according to the median risk scores. In addition, single-sample gene set enrichment analysis (ssGSEA), immune analysis, tumor microenvironment (TME) analysis, principal component analysis (PCA), and half-maximal inhibitory concentration (IC50) were also applied. Expression levels of BMGs were confirmed by qRT-PCR in both human renal cancer cell lines and tissues. RESULTS: We established the BMGs-based prognostic model according to the following steps. Within the TCGA cohort, patients’ prognosis of the HRS group was significantly worse than that of the LRS group, which was consistent with the analysis results of the GEO cohort. PCA patterns were significantly distinct for LRS and HRS groups and pathological features of the HRS group were more malignant compared with the LRS group. Correlation analysis of the PRS model and TME features, such as immune cell scores, stromal cell scores, and ESTIMATE values, revealed a higher immune infiltration in the HRS group compared with the LRS group. The chemotherapeutic response was also evaluated in KIRC treatment. It showed that the HRS group exhibited stronger chemoresistance to chemotherapeutics like FR-180204, GSK1904529A, KIN001-102, and YM201636. The therapeutic reactivity of the other 27 chemotherapeutic agents was summarized as well. Furthermore, the FREM2 level was measured in both human kidney tissues and associated cell lines, which suggested that lower FREM2 expression prompts a severer pathology and clinical ending. CONCLUSIONS: Our study showed that KIRC is associated with a unique BMG expression pattern. The risk scores related to the expression levels of 10 BMGs were assessed by survival status, TME, pathological features, and chemotherapeutic resistance. All results suggested that FREM2 could be a potential candidate for KIRC prognosis prediction. In this study, we established a valid model and presented new therapeutic targets for the KIRC prognosis prediction as well as the clinical treatment recommendation, and finally, facilitated precision tumor therapy for every single individual.
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spelling pubmed-96847262022-11-25 Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy Xiong, Xi Chen, Chen Yang, Jun Ma, Li Wang, Xiong Zhang, Wei Yuan, Yuan Peng, Min Li, Lili Luo, Pengcheng Front Oncol Oncology BACKGROUND: Renal cell carcinoma (RCC) is the most common kidney cancer in adults. According to the histological features, it could be divided into several subtypes, of which the most common one is kidney renal clear cell carcinoma (KIRC), which contributed to more than 90% of cases for RCC and usually ends with a dismal outcome. Previous studies suggested that basement membrane genes (BMGs) play a pivotal role in tumor development. However, the significance and prognostic value of BMGs in KIRC still wrap in the mist. METHODS: KIRC data were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. A prognostic risk score (PRS) model based on BMGs was established using univariate and least absolute shrinkage and selection operator (LASSO) and the Cox regression analysis was performed for prognostic prediction. The Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, receiver operating characteristic (ROC) curves, nomogram, and calibration curves were utilized to evaluate and validate the PRS model. All KIRC cases were divided into the high-risk score (HRS) group and the low-risk score (LRS) group according to the median risk scores. In addition, single-sample gene set enrichment analysis (ssGSEA), immune analysis, tumor microenvironment (TME) analysis, principal component analysis (PCA), and half-maximal inhibitory concentration (IC50) were also applied. Expression levels of BMGs were confirmed by qRT-PCR in both human renal cancer cell lines and tissues. RESULTS: We established the BMGs-based prognostic model according to the following steps. Within the TCGA cohort, patients’ prognosis of the HRS group was significantly worse than that of the LRS group, which was consistent with the analysis results of the GEO cohort. PCA patterns were significantly distinct for LRS and HRS groups and pathological features of the HRS group were more malignant compared with the LRS group. Correlation analysis of the PRS model and TME features, such as immune cell scores, stromal cell scores, and ESTIMATE values, revealed a higher immune infiltration in the HRS group compared with the LRS group. The chemotherapeutic response was also evaluated in KIRC treatment. It showed that the HRS group exhibited stronger chemoresistance to chemotherapeutics like FR-180204, GSK1904529A, KIN001-102, and YM201636. The therapeutic reactivity of the other 27 chemotherapeutic agents was summarized as well. Furthermore, the FREM2 level was measured in both human kidney tissues and associated cell lines, which suggested that lower FREM2 expression prompts a severer pathology and clinical ending. CONCLUSIONS: Our study showed that KIRC is associated with a unique BMG expression pattern. The risk scores related to the expression levels of 10 BMGs were assessed by survival status, TME, pathological features, and chemotherapeutic resistance. All results suggested that FREM2 could be a potential candidate for KIRC prognosis prediction. In this study, we established a valid model and presented new therapeutic targets for the KIRC prognosis prediction as well as the clinical treatment recommendation, and finally, facilitated precision tumor therapy for every single individual. Frontiers Media S.A. 2022-11-10 /pmc/articles/PMC9684726/ /pubmed/36439501 http://dx.doi.org/10.3389/fonc.2022.1024956 Text en Copyright © 2022 Xiong, Chen, Yang, Ma, Wang, Zhang, Yuan, Peng, Li and Luo 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 Oncology
Xiong, Xi
Chen, Chen
Yang, Jun
Ma, Li
Wang, Xiong
Zhang, Wei
Yuan, Yuan
Peng, Min
Li, Lili
Luo, Pengcheng
Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy
title Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy
title_full Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy
title_fullStr Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy
title_full_unstemmed Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy
title_short Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy
title_sort characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684726/
https://www.ncbi.nlm.nih.gov/pubmed/36439501
http://dx.doi.org/10.3389/fonc.2022.1024956
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