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bioRxiv · 10.1101/2021.01.19.427371

In silico analysis and cluster validation of potential breast cancer nsSNPs of serological tumor marker CA27.29

Lakhani, J.·Harwani, D.
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Abstract

Background & ObjectivesCA27.29 is a breast cancer-associated glycoprotein. Many genetic variations caused by non-synonymous nucleotide polymorphisms (nsSNPs) are known to affect the functionality of the CA27.29 protein. MethodsIn the present manuscript, an in silico analysis of the genetic variations in CA27.29 was done to observe functional nsSNPs that possibly alter its stability. Among 2205 SNPs identified from the publically available SNP database (dbSNP), 213 (9.66%) synonymous SNPs, 24 (1.09%) non-synonymous SNPs, and 1351 (61.27%) noncoding intronic SNPs were observed. The function predictability tools SIFT, Provean and Polyphen2 were used to uncover variations in the analyzed nsSNPs and their functionality. ResultsA total of 16, 20 and 10 non-synonymous SNPs (nsSNPs) were predicted to be damaging or deleterious by SIFT, Polyphen, and Provean tools respectively. Intriguingly, 9 nsSNPs were predicted to be damaging by all the three tools used while 4 nsSNPs were predicted to be damaging by SIFT and Polyphen tools. The substitutions C/G->T and G->A/T were observed to be dominant in the analyzed nsSNPs that probably have damaging role to CA27.29 glycoprotein. Moreover, the validation of results using ClinVar tool revealed that all the analyzed possibly, probably and highly damaging nsSNPs are yet to be reported and studied. Besides this, we found Global minor allele frequency (Global MAF) for only 11 nsSNPs, the values of which were observed to be <0.1% that further confirmed the novelty of the analyzed variants. Interpretation & ConclusionsAmong the analyzed nsSNPs, 3 nsSNPs rs145691584, rs148332231 and rs191544901 were found to be located in 3UTR region of CA27.29 gene that were assumed to have the possible functional roles in altering the protein stability. The present study is useful to gain useful insights into the genetic variations in nsSNPs that may playing a critical role in determining the susceptibility to breast cancer.

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Lakhani, J., Harwani, D.. 2021-01-20. In silico analysis and cluster validation of potential breast cancer nsSNPs of serological tumor marker CA27.29. https://doi.org/10.1101/2021.01.19.427371

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