In silico analysis of COSMIC retrieved P body gene mutations in breast cancer

Paleri, Aswathi V.; Cherian, Isaac; Suresh, Padmanaban S.; Venkatesh, Thejaswini

doi:10.1016/j.genrep.2020.100617

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…According to the COSMIC database results, twelve nsSNPs in that L32M, R47C, and D141N are identified in SCLC, G20W, S57C, R70P, I89V, G118V, and A191D are in association with LUSC and three nsSNPs G95V, E157K and G168V associated in the risk of LUAD. However, there remains the possibility that other high-risk nsSNPs identified in this work could be linked to lung cancer and other cancer types (Kosaloglu et al, 2016;Paleri et al, 2020). Speculated nsSNPs that corresponded to the PGRMC1gene mutations were analyzed in the COSMIC database to understand the impact of predicted SNPs in lung cancer (Wang et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

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Computational Identification and Validation of Non-Synonymous SNPs in Progesterone Receptor Membrane Complex 1 Linked to Lung Cancer

Solairaja,

Mohideen,

Venkatabalasubramanian

2023

IJERR

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Numerous gene polymorphisms have been attributed to Lung cancer, but PGRMC1 (Progesterone receptor membrane component 1) is a lesser-known candidate among them. However, emerging research is slowly suggesting the role of polymorphisms in PGRMC1 gene-associated tumorigenesis. Nevertheless, phenotypic changes still need to be studied. The main aim of this study is to identify the most deleterious nsSNPs (non-synonymous single nucleotide polymorphisms) in PGRMC1 that can potentially increase the susceptibility to lung cancer progression. In this work, we scrutinized highly detrimental nsSNPs for PGRMC1 from the available dbSNP database. We further categorized using the FATHMM server to enlist the nsSNPs, which are driver mutants capable of affecting the function of the PGRMC1 protein. We employed clinical evidence from the COSMIC database for further evaluation and confirming the presence of nsSNPs in lung cancer patients. There are 12 nsSNPs reported in lung cancer patients, which are L32M, R47C, D141N, G20W, S57C, R70P, I89V, G118V, A191D, G95V, E157K, and G168V predicted to damage the functions. Conclusively, through a comprehensive comparison of the outcomes obtained through these computational methods, we identified novel I89V, D120E, G95V and G168V nsSNPs that pose substantial risks to the functionality of the PGRMC1 protein. Focusing on the importance of PGRMC1 in lung cancer, analyzing its function was conceded to unveil the interlink between genetic mutation and phenotypic changes. Thus, this study provides insights into the influence of PGRMC1variants in Lung cancer. The evaluated nsSNPs can significantly aid future research on the gene and its association with lung cancer progression in large population distribution frequencies of genotypes among different subgroups.

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Section: Discussionmentioning

confidence: 99%

“…This database represented PGRMC1 mutations in Pan-cancer and distribution in clinical samples. The association of highly deleterious PGRMC1 nsSNPs lung cancer was analysed using a mutation profile (Paleri et al, 2020).…”

Section: Pgrmc1 Mutational Analysis In Lung Cancermentioning

confidence: 99%

Computational Identification and Validation of Non-Synonymous SNPs in Progesterone Receptor Membrane Complex 1 Linked to Lung Cancer

Solairaja,

Mohideen,

Venkatabalasubramanian

2023

IJERR

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“…Oncogenes and tumor suppressor genes/ncRNAs undergo aberrant DNA methylation during cancer progression (Llinàs‐Arias & Esteller, 2017). P body genes are found to be mutated in breast cancer (Paleri et al, 2020). P‐body components undergo protein‐protein and protein‐RNA interactions within its granules and outside of it and form a complex functional network (Zheng et al, 2015).…”

Section: Regulation Of Pb Components By Epigenetic Machinery and Their Role As Biomarkersmentioning

confidence: 99%

Regulation of processing bodies: From viruses to cancer epigenetic machinery

Kanakamani

Suresh

Venkatesh

2020

Cell Biology International

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Processing bodies (PBs) are 100–300 nm cytoplasmic messenger ribonucleoprotein particle (mRNP) granules that regulate eukaryotic gene expression. These cytoplasmic compartments harbor messenger RNAs (mRNAs) and several proteins involved in mRNA decay, microRNA silencing, nonsense‐mediated mRNA decay, and splicing. Though membrane‐less, PB structures are maintained by RNA‐protein and protein‐protein interactions. PB proteins have intrinsically disordered regions and low complexity domains, which account for its liquid to liquid phase separation. In addition to being dynamic and actively involved in the exchange of materials with other mRNPs and organelles, they undergo changes on various cellular cues and environmental stresses, including viral infections. Interestingly, several PB proteins are individually implicated in cancer development, and no study has addressed the effects on PB dynamics after epigenetic modifications of cancer‐associated PB genes. In the current review, we summarize modulations undergone by P bodies or P body components upon viral infections. Furthermore, we discuss the selective and widely investigated PB proteins that undergo methylation changes in cancer and their potential as biomarkers.

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In silico analysis of COSMIC retrieved P body gene mutations in breast cancer

Cited by 2 publications

References 12 publications

Computational Identification and Validation of Non-Synonymous SNPs in Progesterone Receptor Membrane Complex 1 Linked to Lung Cancer

Computational Identification and Validation of Non-Synonymous SNPs in Progesterone Receptor Membrane Complex 1 Linked to Lung Cancer

Regulation of processing bodies: From viruses to cancer epigenetic machinery

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