Abstract

Prostate Cancer (PC) is commonly known as one of the most frequent tumors among males. A significant problem of this tumor is that in early stages most of the cases course as indolent forms, so an active surveillance will anticipate the appearance of aggressive stages. One of the main strategies in medical and biomedical research is to find non-invasive biomarkers for improving monitoring and performing a more precise follow-up of diseases like PC. Here we report the relevant role of IGF2 and miR-93-5p as non-invasive biomarker for PC. This event could improve current medical strategies in PC.

Highlights

  • It is well known that prostate cancer (PC) is a heterogeneous disease, which makes it difficult the identification of any clinical and molecular biomarker in disease management

  • Gene Expression Analysis Out of all the DEGs obtained in differential expression analyses, we focused on IGF2 and some of its closest interactors obtained by using the STRING database

  • Except for IGF2, which is under-expressed in patients with treatment resistance, any other gene showed any statistically significant result

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Summary

Introduction

It is well known that prostate cancer (PC) is a heterogeneous disease, which makes it difficult the identification of any clinical and molecular biomarker in disease management. The use of robust biomarkers; mainly focused on molecular non-invasive ones; is still a challenge in this tumor. Several germline variants have been suggested as relevant in PC such as those in ATM (ataxiatelangiectasia mutated), BRCA1 (breast cancer), BRCA2, MSH2 (MutS Homolog 2), MLH1 (mutL homolog 1), MSH6 (MutS Homolog 6), PMS2 (PMS1 homolog 2), EPCAM (epithelial cellular adhesion molecule) and HOXB13 (Homeobox B13) genes (Saunders et al, 2021). Recent data support the role of several SNPs in IL-6 (Interleukin 6) gene (rs1800795, rs1800796 and rs1800797) as biomarkers of an increased cancer risk in several tumors. Variants rs1800795 and rs1800796 are associated with an overall increased risk of PC (Harun-Or-Roshid et al, 2021)

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