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Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation
BACKGROUND: Anoikis is a programmed cell death process that was proven to be associated with cancer. Uroepithelial carcinoma of the bladder (BLCA) is a malignant disease of the urinary tract and has a strong metastatic potential. To determine whether anoikis-associated genes can predict the prognosi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232821/ https://www.ncbi.nlm.nih.gov/pubmed/37275895 http://dx.doi.org/10.3389/fimmu.2023.1122570 |
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author | Dong, Ying Xu, Chaojie Su, Ganglin Li, Yanfeng Yan, Bing Liu, Yuhan Yin, Tao Mou, Shuanzhu Mei, Hongbing |
author_facet | Dong, Ying Xu, Chaojie Su, Ganglin Li, Yanfeng Yan, Bing Liu, Yuhan Yin, Tao Mou, Shuanzhu Mei, Hongbing |
author_sort | Dong, Ying |
collection | PubMed |
description | BACKGROUND: Anoikis is a programmed cell death process that was proven to be associated with cancer. Uroepithelial carcinoma of the bladder (BLCA) is a malignant disease of the urinary tract and has a strong metastatic potential. To determine whether anoikis-associated genes can predict the prognosis of BLCA accurately, we evaluated the prognostic value of anoikis-associated genes in BLCA and constructed the best model to predict prognosis. METHOD: The BLCA transcriptome data were downloaded from TCGA and GEO databases, and genes with differential expression were selected and then clustered using non-negative matrix factorization (NMF). The genes with the most correlation with anoikis were screened and identified using univariate Cox regression, lasso regression, and multivariate Cox regression. The GEO dataset was used for external validation. Nomograms were created based on risk characteristics in combination with clinical variants and the performance of the model was validated with receiver operating characteristic (ROC) curves. The immunotherapeutic significance of this risk score was assessed using the immune phenomenon score (IPS). IC50 values of predictive chemotherapeutic agents were calculated. Finally, we used RT-qPCR to determine the mRNA expression of four genes, CALR, FASN, CASP6, and RAD9A. RESULT: We screened 406 tumor samples and 19 normal tissue samples from the TCGA database. Based on anoikis-associated genes, we classified patients into two subtypes (C1 and C2) using NMF method. Subsequently, nine core genes were screened by multiple methods after analysis, which were used to construct risk profiles. The design of nomograms based on risk profiles and clinical variables, ROC, and calibration curves confirmed that the model could well have the ability to predict the survival of BLCA patients at 1, 3, and 5 years. By predicting the IC50 values of chemotherapeutic drugs, it was learned that the high-risk group (HRG) was more susceptible to paclitaxel, gemcitabine, and cisplatin, and the low-risk group (LRG) was more susceptible to veriparib and afatinib. CONCLUSION: In summary, the risk score of anoikis-associated genes can be applied as a predictor to predict the prognosis of BLCA in clinical practice. |
format | Online Article Text |
id | pubmed-10232821 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102328212023-06-02 Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation Dong, Ying Xu, Chaojie Su, Ganglin Li, Yanfeng Yan, Bing Liu, Yuhan Yin, Tao Mou, Shuanzhu Mei, Hongbing Front Immunol Immunology BACKGROUND: Anoikis is a programmed cell death process that was proven to be associated with cancer. Uroepithelial carcinoma of the bladder (BLCA) is a malignant disease of the urinary tract and has a strong metastatic potential. To determine whether anoikis-associated genes can predict the prognosis of BLCA accurately, we evaluated the prognostic value of anoikis-associated genes in BLCA and constructed the best model to predict prognosis. METHOD: The BLCA transcriptome data were downloaded from TCGA and GEO databases, and genes with differential expression were selected and then clustered using non-negative matrix factorization (NMF). The genes with the most correlation with anoikis were screened and identified using univariate Cox regression, lasso regression, and multivariate Cox regression. The GEO dataset was used for external validation. Nomograms were created based on risk characteristics in combination with clinical variants and the performance of the model was validated with receiver operating characteristic (ROC) curves. The immunotherapeutic significance of this risk score was assessed using the immune phenomenon score (IPS). IC50 values of predictive chemotherapeutic agents were calculated. Finally, we used RT-qPCR to determine the mRNA expression of four genes, CALR, FASN, CASP6, and RAD9A. RESULT: We screened 406 tumor samples and 19 normal tissue samples from the TCGA database. Based on anoikis-associated genes, we classified patients into two subtypes (C1 and C2) using NMF method. Subsequently, nine core genes were screened by multiple methods after analysis, which were used to construct risk profiles. The design of nomograms based on risk profiles and clinical variables, ROC, and calibration curves confirmed that the model could well have the ability to predict the survival of BLCA patients at 1, 3, and 5 years. By predicting the IC50 values of chemotherapeutic drugs, it was learned that the high-risk group (HRG) was more susceptible to paclitaxel, gemcitabine, and cisplatin, and the low-risk group (LRG) was more susceptible to veriparib and afatinib. CONCLUSION: In summary, the risk score of anoikis-associated genes can be applied as a predictor to predict the prognosis of BLCA in clinical practice. Frontiers Media S.A. 2023-05-18 /pmc/articles/PMC10232821/ /pubmed/37275895 http://dx.doi.org/10.3389/fimmu.2023.1122570 Text en Copyright © 2023 Dong, Xu, Su, Li, Yan, Liu, Yin, Mou and Mei 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 | Immunology Dong, Ying Xu, Chaojie Su, Ganglin Li, Yanfeng Yan, Bing Liu, Yuhan Yin, Tao Mou, Shuanzhu Mei, Hongbing Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation |
title | Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation |
title_full | Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation |
title_fullStr | Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation |
title_full_unstemmed | Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation |
title_short | Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation |
title_sort | clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232821/ https://www.ncbi.nlm.nih.gov/pubmed/37275895 http://dx.doi.org/10.3389/fimmu.2023.1122570 |
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