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

被引:9
|
作者
Chai, Chuan-Yu [1 ]
Maran, Sathiya [2 ]
Thew, Hin-Yee [2 ]
Tan, Yong-Chiang [3 ]
Abd Rahman, Nik Mohd Afizan Nik [4 ]
Cheng, Wan-Hee [5 ]
Lai, Kok-Song [6 ]
Loh, Jiun-Yan [7 ]
Yap, Wai-Sum [8 ]
机构
[1] Univ Tunku Abdul Rahman, Fac Sci, Dept Biol Sci, Jalan Univ, Bandar Barat 31900, Kampar, Malaysia
[2] Monash Univ Malaysia, Sch Pharm, Jalan Lagoon Selatan, Bandar Sunway 47500, Malaysia
[3] Int Med Univ, Sch Postgrad Studies, Jalan Jalil Perkasa 19, Kuala Lumpur 57000, Malaysia
[4] Univ Putra Malaysia, Fac Biotechnol & Biomol Sci, Dept Cell & Mol Biol, Serdang 43400, Selangor, Malaysia
[5] INTI Int Univ, Fac Hlth & Life Sci, Nilai 71800, Negeri Sembilan, Malaysia
[6] Higher Coll Technol, Abu Dhabi Womens Coll, Hlth Sci Div, Abu Dhabi 41012, U Arab Emirates
[7] UCSI Univ, Ctr Res Adv Aquaculture CORAA, 1 Jalan Menara Gading UCSI Height, Kuala Lumpur 56000, Malaysia
[8] He & Ni Acad, Off Tower B, Kuala Lumpur 59200, Malaysia
来源
BIOLOGY-BASEL | 2022年 / 11卷 / 11期
关键词
HRAS; nsSNPs; RAS; MAPK signaling pathway; diagnosis; prognosis; SEQUENCE; RAS; INHIBITION; SUPPRESSES; PROTEINS; DISEASES; DATABASE; SITES;
D O I
10.3390/biology11111604
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. 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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页数:16
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