Literature DB >> 34373545

Pathogenic nsSNPs that increase the risks of cancers among the Orang Asli and Malays.

Nurul Ain Khoruddin1,2, Mohd NurFakhruzzaman Noorizhab1,3, Lay Kek Teh1,3, Farida Zuraina Mohd Yusof1,2, Mohd Zaki Salleh4,5.   

Abstract

Single-nucleotide polymorphisms (SNPs) are the most common genetic variations for various complex human diseases, including cancers. Genome-wide association studies (GWAS) have identified numerous SNPs that increase cancer risks, such as breast cancer, colorectal cancer, and leukemia. These SNPs were cataloged for scientific use. However, GWAS are often conducted on certain populations in which the Orang Asli and Malays were not included. Therefore, we have developed a bioinformatic pipeline to mine the whole-genome sequence databases of the Orang Asli and Malays to determine the presence of pathogenic SNPs that might increase the risks of cancers among them. Five different in silico tools, SIFT, PROVEAN, Poly-Phen-2, Condel, and PANTHER, were used to predict and assess the functional impacts of the SNPs. Out of the 80 cancer-related nsSNPs from the GWAS dataset, 52 nsSNPs were found among the Orang Asli and Malays. They were further analyzed using the bioinformatic pipeline to identify the pathogenic variants. Three nsSNPs; rs1126809 (TYR), rs10936600 (LRRC34), and rs757978 (FARP2), were found as the most damaging cancer pathogenic variants. These mutations alter the protein interface and change the allosteric sites of the respective proteins. As TYR, LRRC34, and FARP2 genes play important roles in numerous cellular processes such as cell proliferation, differentiation, growth, and cell survival; therefore, any impairment on the protein function could be involved in the development of cancer. rs1126809, rs10936600, and rs757978 are the important pathogenic variants that increase the risks of cancers among the Orang Asli and Malays. The roles and impacts of these variants in cancers will require further investigations using in vitro cancer models.
© 2021. The Author(s).

Entities:  

Year:  2021        PMID: 34373545     DOI: 10.1038/s41598-021-95618-y

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  57 in total

1.  Predicting the functional consequences of non-synonymous single nucleotide polymorphisms: structure-based assessment of amino acid variation.

Authors:  D Chasman; R M Adams
Journal:  J Mol Biol       Date:  2001-03-23       Impact factor: 5.469

2.  Identification and in silico analysis of functional SNPs of the BRCA1 gene.

Authors:  R Rajasekaran; C Sudandiradoss; C George Priya Doss; Rao Sethumadhavan
Journal:  Genomics       Date:  2007-08-27       Impact factor: 5.736

3.  Identification of most damaging nsSNPs in human CCR6 gene: In silico analyses.

Authors:  Mehran Akhtar; Tazkira Jamal; Hina Jamal; Jalal Ud Din; Muhsin Jamal; Muhammad Arif; Maria Arshad; Fazal Jalil
Journal:  Int J Immunogenet       Date:  2019-07-31       Impact factor: 1.466

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Authors:  Marharyta Petukh; Tugba G Kucukkal; Emil Alexov
Journal:  Hum Mutat       Date:  2015-04-06       Impact factor: 4.878

Review 5.  Structural and physico-chemical effects of disease and non-disease nsSNPs on proteins.

Authors:  Tugba G Kucukkal; Marharyta Petukh; Lin Li; Emil Alexov
Journal:  Curr Opin Struct Biol       Date:  2015-02-04       Impact factor: 6.809

6.  Serum inhibitor of phytohemagglutinin-induced lymphocyte proliferation in Bartter syndrome.

Authors:  E H Garin; P J Sausville; G A Richard
Journal:  J Pediatr       Date:  1983-04       Impact factor: 4.406

7.  In silico analysis of nsSNPs in ABCB1 gene affecting breast cancer associated protein P-glycoprotein (P-gp).

Authors:  Rajkumar Chakraborty; Himani Gupta; Razia Rahman; Yasha Hasija
Journal:  Comput Biol Chem       Date:  2018-08-11       Impact factor: 2.877

8.  Improving the prediction of disease-related variants using protein three-dimensional structure.

Authors:  Emidio Capriotti; Russ B Altman
Journal:  BMC Bioinformatics       Date:  2011-07-05       Impact factor: 3.169

9.  Computational analysis of high-risk SNPs in human CHK2 gene responsible for hereditary breast cancer: A functional and structural impact.

Authors:  Nutan V Badgujar; Bhoomi V Tarapara; Franky D Shah
Journal:  PLoS One       Date:  2019-08-09       Impact factor: 3.240

10.  Identifying Mendelian disease genes with the variant effect scoring tool.

Authors:  Hannah Carter; Christopher Douville; Peter D Stenson; David N Cooper; Rachel Karchin
Journal:  BMC Genomics       Date:  2013-05-28       Impact factor: 3.969

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  1 in total

1.  Genome-wide association study of actinic keratosis identifies new susceptibility loci implicated in pigmentation and immune regulation pathways.

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Journal:  Commun Biol       Date:  2022-04-21
  1 in total

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