Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment
Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common primary malignancies of the urinary tract, highly heterogeneous, and increasing in incidence worldwide. Anoikis is a specific type of programmed cell death in which solid tumor cells or normal epithelial cells that do not hav...
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Nature Portfolio
2023-11-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-46398-0 |
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author | Yinglei Jiang Ying Wang Zhengyan Wang Yinzhen Zhang Yulong Hou Xukai Wang |
author_facet | Yinglei Jiang Ying Wang Zhengyan Wang Yinzhen Zhang Yulong Hou Xukai Wang |
author_sort | Yinglei Jiang |
collection | DOAJ |
description | Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common primary malignancies of the urinary tract, highly heterogeneous, and increasing in incidence worldwide. Anoikis is a specific type of programmed cell death in which solid tumor cells or normal epithelial cells that do not have metastatic properties lose adhesion to the extracellular matrix or undergo inappropriate cell adhesion-induced apoptosis. Anoikis is thought to play a critical role in tumorigenesis, maintenance, and treatment, according to an increasing amount of research. However, there is still some uncertainty regarding the general impact of anoikis-related genes (ARGs) on the prognostic importance, tumor microenvironment characteristics, and treatment reaction of ccRCC patients. For this study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus datasets to access the RNA sequencing results and clinical information from ccRCC patients. 29 ARGs related to survival were found using differential analysis and univariate Cox regression analysis. The samples were then divided into two clusters that had different immune traits via unsupervised cluster analysis using 29 prognosis-associated differently expressed ARGs. Then, to build an ARGs signature, 7 genes (PLAU, EDA2R, AFP, PLG, TUBB3, APOBEC3G, and MALAT1) were found using Least Absolute Shrinkage and Selection Operator regression analysis. The new ARGs signature demonstrated outstanding prognostic capability for ccRCC patients' overall survival. In conclusion, for ccRCC patients, we created an ARGs signature that strongly connects to immunological traits and therapy response. Clinicians may find this ARGs signature helpful in developing more individualized and detailed treatment strategies for ccRCC patients. |
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language | English |
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spelling | doaj.art-01ce9ea8377041d5b2f7d83cecd5c7752023-11-05T12:18:35ZengNature PortfolioScientific Reports2045-23222023-11-0113111210.1038/s41598-023-46398-0Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironmentYinglei Jiang0Ying Wang1Zhengyan Wang2Yinzhen Zhang3Yulong Hou4Xukai Wang5Dialysis Room, The Affiliated Hospital of Changchun University of Chinese MedicineDialysis Room, The Affiliated Hospital of Changchun University of Chinese MedicineChangchun University of Chinese MedicineChangchun University of Chinese MedicineChangchun University of Chinese MedicineDialysis Room, The Affiliated Hospital of Changchun University of Chinese MedicineAbstract Clear cell renal cell carcinoma (ccRCC) is one of the most common primary malignancies of the urinary tract, highly heterogeneous, and increasing in incidence worldwide. Anoikis is a specific type of programmed cell death in which solid tumor cells or normal epithelial cells that do not have metastatic properties lose adhesion to the extracellular matrix or undergo inappropriate cell adhesion-induced apoptosis. Anoikis is thought to play a critical role in tumorigenesis, maintenance, and treatment, according to an increasing amount of research. However, there is still some uncertainty regarding the general impact of anoikis-related genes (ARGs) on the prognostic importance, tumor microenvironment characteristics, and treatment reaction of ccRCC patients. For this study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus datasets to access the RNA sequencing results and clinical information from ccRCC patients. 29 ARGs related to survival were found using differential analysis and univariate Cox regression analysis. The samples were then divided into two clusters that had different immune traits via unsupervised cluster analysis using 29 prognosis-associated differently expressed ARGs. Then, to build an ARGs signature, 7 genes (PLAU, EDA2R, AFP, PLG, TUBB3, APOBEC3G, and MALAT1) were found using Least Absolute Shrinkage and Selection Operator regression analysis. The new ARGs signature demonstrated outstanding prognostic capability for ccRCC patients' overall survival. In conclusion, for ccRCC patients, we created an ARGs signature that strongly connects to immunological traits and therapy response. Clinicians may find this ARGs signature helpful in developing more individualized and detailed treatment strategies for ccRCC patients.https://doi.org/10.1038/s41598-023-46398-0 |
spellingShingle | Yinglei Jiang Ying Wang Zhengyan Wang Yinzhen Zhang Yulong Hou Xukai Wang Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment Scientific Reports |
title | Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment |
title_full | Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment |
title_fullStr | Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment |
title_full_unstemmed | Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment |
title_short | Anoikis-related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment |
title_sort | anoikis related genes signature development for clear cell renal cell carcinoma prognosis and tumor microenvironment |
url | https://doi.org/10.1038/s41598-023-46398-0 |
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