Role of Sirtuins in the Pathobiology of Onco-Hematological Diseases: A PROSPERO-Registered Study and In Silico Analysis

Author:

Goes João Vitor Caetano,Carvalho Luiz Gustavo,de Oliveira Roberta Taiane Germano,Melo Mayara Magna de Lima,Novaes Lázaro Antônio CampanhaORCID,Moreno Daniel Antunes,Gonçalves Paola GyulianeORCID,Montefusco-Pereira Carlos VictorORCID,Pinheiro Ronald Feitosa,Ribeiro Junior Howard LopesORCID

Abstract

The sirtuins (SIRT) gene family (SIRT1 to SIRT7) contains the targets implicated in cellular and organismal aging. The role of SIRTs expression in the pathogenesis and overall survival of patients diagnosed with solid tumors has been widely discussed. However, studies that seek to explain the role of these pathways in the hematopoietic aging process and the consequences of their instability in the pathogenesis of different onco-hematological diseases are still scarce. Therefore, we performed a systematic review (registered in PROSPERO database #CRD42022310079) and in silico analysis (based on GEPIA database) to discuss the role of SIRTs in the advancement of pathogenesis and/or prognosis for different hematological cancer types. In summary, given recent available scientific evidence and in silico gene expression analysis that supports the role of SIRTs in pathobiology of hematological malignances, such as leukemias, lymphomas and myeloma, it is clear the need for further high-quality research and clinical trials that expands the SIRT inhibition knowledge and its effect on controlling clonal progression caused by genomic instability characteristics of these diseases. Finally, SIRTs represent potential molecular targets in the control of the effects caused by aging on the failures of the hematopoietic system that can lead to the involvement of hematological neoplasms.

Funder

Coordenação de Aperfeicoamento de Pessoal de Nível Superior

Hospital de Câncer de Barretos

Publisher

MDPI AG

Subject

Cancer Research,Oncology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Rapid and precise detection of cancers via label-free SERS and deep learning;Analytical and Bioanalytical Chemistry;2023-05-17

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