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Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer

SIMPLE SUMMARY: The HRAS gene has been reported to cause cancer, and identifying alleles that could potentially predispose one to cancer could lead to early diagnosis and better prognosis. Here for the first time, we conducted a machine-learning approach to identify high-risk predictive alleles of t...

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Autores principales: Chai, Chuan-Yu, Maran, Sathiya, Thew, Hin-Yee, Tan, Yong-Chiang, Rahman, Nik Mohd Afizan Nik Abd, Cheng, Wan-Hee, Lai, Kok-Song, Loh, Jiun-Yan, Yap, Wai-Sum
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688001/
https://www.ncbi.nlm.nih.gov/pubmed/36358305
http://dx.doi.org/10.3390/biology11111604
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author Chai, Chuan-Yu
Maran, Sathiya
Thew, Hin-Yee
Tan, Yong-Chiang
Rahman, Nik Mohd Afizan Nik Abd
Cheng, Wan-Hee
Lai, Kok-Song
Loh, Jiun-Yan
Yap, Wai-Sum
author_facet Chai, Chuan-Yu
Maran, Sathiya
Thew, Hin-Yee
Tan, Yong-Chiang
Rahman, Nik Mohd Afizan Nik Abd
Cheng, Wan-Hee
Lai, Kok-Song
Loh, Jiun-Yan
Yap, Wai-Sum
author_sort Chai, Chuan-Yu
collection PubMed
description SIMPLE SUMMARY: The HRAS gene has been reported to cause cancer, and identifying alleles that could potentially predispose one to cancer could lead to early diagnosis and better prognosis. Here for the first time, we conducted a machine-learning approach to identify high-risk predictive alleles of the HRAS gene. Our study reported alleles that may serve as potential targets for different proteomic studies, diagnoses, and therapeutic interventions focusing on cancer. ABSTRACT: The Harvey rat sarcoma (HRAS) proto-oncogene belongs to the RAS family and is one of the pathogenic genes that cause cancer. Deleterious nsSNPs might have adverse consequences at the protein level. This study aimed to investigate deleterious nsSNPs in the HRAS gene in predicting structural alterations associated with mutants that disrupt normal protein–protein interactions. Functional and structural analysis was employed in analyzing the HRAS nsSNPs. Putative post-translational modification sites and the changes in protein–protein interactions, which included a variety of signal cascades, were also investigated. Five different bioinformatics tools predicted 33 nsSNPs as “pathogenic” or “harmful”. Stability analysis predicted rs1554885139, rs770492627, rs1589792804, rs730880460, rs104894227, rs104894227, and rs121917759 as unstable. Protein–protein interaction analysis revealed that HRAS has a hub connecting three clusters consisting of 11 proteins, and changes in HRAS might cause signal cascades to dissociate. Furthermore, Kaplan–Meier bioinformatics analyses indicated that the HRAS gene deregulation affected the overall survival rate of patients with breast cancer, leading to prognostic significance. Thus, based on these analyses, our study suggests that the reported nsSNPs of HRAS may serve as potential targets for different proteomic studies, diagnoses, and therapeutic interventions focusing on cancer.
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spelling pubmed-96880012022-11-25 Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer Chai, Chuan-Yu Maran, Sathiya Thew, Hin-Yee Tan, Yong-Chiang Rahman, Nik Mohd Afizan Nik Abd Cheng, Wan-Hee Lai, Kok-Song Loh, Jiun-Yan Yap, Wai-Sum Biology (Basel) Article SIMPLE SUMMARY: The HRAS gene has been reported to cause cancer, and identifying alleles that could potentially predispose one to cancer could lead to early diagnosis and better prognosis. Here for the first time, we conducted a machine-learning approach to identify high-risk predictive alleles of the HRAS gene. Our study reported alleles that may serve as potential targets for different proteomic studies, diagnoses, and therapeutic interventions focusing on cancer. ABSTRACT: The Harvey rat sarcoma (HRAS) proto-oncogene belongs to the RAS family and is one of the pathogenic genes that cause cancer. Deleterious nsSNPs might have adverse consequences at the protein level. This study aimed to investigate deleterious nsSNPs in the HRAS gene in predicting structural alterations associated with mutants that disrupt normal protein–protein interactions. Functional and structural analysis was employed in analyzing the HRAS nsSNPs. Putative post-translational modification sites and the changes in protein–protein interactions, which included a variety of signal cascades, were also investigated. Five different bioinformatics tools predicted 33 nsSNPs as “pathogenic” or “harmful”. Stability analysis predicted rs1554885139, rs770492627, rs1589792804, rs730880460, rs104894227, rs104894227, and rs121917759 as unstable. Protein–protein interaction analysis revealed that HRAS has a hub connecting three clusters consisting of 11 proteins, and changes in HRAS might cause signal cascades to dissociate. Furthermore, Kaplan–Meier bioinformatics analyses indicated that the HRAS gene deregulation affected the overall survival rate of patients with breast cancer, leading to prognostic significance. Thus, based on these analyses, our study suggests that the reported nsSNPs of HRAS may serve as potential targets for different proteomic studies, diagnoses, and therapeutic interventions focusing on cancer. MDPI 2022-11-02 /pmc/articles/PMC9688001/ /pubmed/36358305 http://dx.doi.org/10.3390/biology11111604 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chai, Chuan-Yu
Maran, Sathiya
Thew, Hin-Yee
Tan, Yong-Chiang
Rahman, Nik Mohd Afizan Nik Abd
Cheng, Wan-Hee
Lai, Kok-Song
Loh, Jiun-Yan
Yap, Wai-Sum
Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer
title Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer
title_full Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer
title_fullStr Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer
title_full_unstemmed Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer
title_short Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer
title_sort predicting deleterious non-synonymous single nucleotide polymorphisms (nssnps) of hras gene and in silico evaluation of their structural and functional consequences towards diagnosis and prognosis of cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688001/
https://www.ncbi.nlm.nih.gov/pubmed/36358305
http://dx.doi.org/10.3390/biology11111604
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