IMR Press / JOMH / Volume 17 / Issue 4 / DOI: 10.31083/jomh.2021.070
Open Access Systematic Review
Insights into association between urolithiasis and prostate cancer
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1 Department of Urology, Shandong Provincial Third Hospital, Shandong University, 250031 Jinan, China
2 Department of Biotechnology, School of Bioengineering and Biosciences Lovely Professional University, 144111 Punjab, India
3 Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research (BISR), 302021 Rajasthan, India
4 BIOinformatics CLUb for Experimenting Scientists (Bioclues.org), India
5 Department of Internal medicine, The People Hospital of Huaiyin, 250021 Jinan, China
6 Department of Padiatric, Shandong Provincial Third Hospital, Shandong University, 250031 Jinan, China
*Correspondence: wangyufen521@sina.cn (Yufen Wang); sugunakar.24344@lpu.co.in (Sugunakar Vuree)
These authors contributed equally.
J. Mens. Health 2021, 17(4), 52–61; https://doi.org/10.31083/jomh.2021.070
Submitted: 24 January 2021 | Accepted: 4 March 2021 | Published: 30 September 2021
(This article belongs to the Special Issue Therapy and prognosis of metastatic prostate cancer)
Copyright: © 2021 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/).
Abstract

Background and objective: Urolithiasis or renal stones form a major urinary tract infection with formation of calcifications in the bladder and uterus. With the lifestyle diseases burgeoning, the renal stones have become a common cause with an approximate 1 in 1000 people affected all over the world with a risk ratio of 3 : 1 in men and women. On the other hand, prostate or genitourinary cancers are well documented to be associated with urolithiasis.

Methods: A gene list was prepared from the published NCBI dataset, comprising all the genes related to urolithiasis primarily with mutations (both pathogenic and likely pathogenic Single nucleotide polymorphisms, SNP’s) for every particular gene screened later from the published datasets. To see the interactions among all the potential genetic factors, PPI based tools were used and an interaction map was prepared. For the characterization of mutations, we have used gnomAD for verifying all the SNPs whether they are synonymous or nonsynonymous mutations.

Results: We outlined the list of genes and discussed the systems bioinformatics integrated approach associated with it.

Conclusion: We found a large number of genes common to them and their association is subtly known for immunomodulatory response.

Keywords
Urolithiasis
Genitourinary cancer
Prostate cancer
Renal/kidney stones
Hyperuricemia
Calcium homeostasis
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