Literature DB >> 34432285

MicroRNAs and Heat Shock Proteins in Breast Cancer Biology.

Mehmet Taha Yildiz1, Lütfi Tutar2, Nazlı Irmak Giritlioğlu3, Banu Bayram4, Yusuf Tutar5,6.   

Abstract

Breast cancer has five major immune types; luminal A, luminal B, HER2, Basal-like, and normal-like. Cells produce a family of protein called heat shock proteins (Hsps) in response to exposure to thermal and other proteotoxic stresses play essential roles in cancer metabolism and this large family shows a diverse set of Hsp involvement in different breast cancer immune types. Recently, Hsp members categorized according to their immune type roles. Hsp family consists of several subtypes formed by molecular weight; Hsp70, Hsp90, Hsp100, Hsp40, Hsp60, and small molecule Hsps. Cancer cells employ Hsps as survival factors since most of these proteins prevent apoptosis. Several studies monitored Hsp roles in breast cancer cells and reported Hsp27 involvement in drug resistance, Hsp70 in tumor cell transformation-progression, and interaction with p53. Furthermore, the association of Hsp90 with steroid receptors and signaling proteins in patients with breast cancer directed research to focus on Hsp-based treatments. miRNAs are known to play key roles in all types of cancer that are upregulated or downregulated in cancer which respectively referred to as oncogenes (oncomirs) or tumor suppressors. Expression profiles of miRNAs may be used to classify, diagnose, and predict different cancer types. It is clear that miRNAs play regulatory roles in gene expression and this work reveals miRNA correlation to Hsp depending on specific breast cancer immune types. Deregulation of specific Hsp genes in breast cancer subtypes allows for identification of new targets for drug design and cancer treatment. Here, we performed miRNA network analysis by recruiting Hsp genes detected in breast cancer subtypes and reviewed some of the miRNAs related to aforementioned Hsp genes.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Breast cancer; Hsp; miRNA; miRNA network

Mesh:

Substances:

Year:  2022        PMID: 34432285     DOI: 10.1007/978-1-0716-1170-8_15

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  107 in total

Review 1.  Clinical implications of the intrinsic molecular subtypes of breast cancer.

Authors:  Aleix Prat; Estela Pineda; Barbara Adamo; Patricia Galván; Aranzazu Fernández; Lydia Gaba; Marc Díez; Margarita Viladot; Ana Arance; Montserrat Muñoz
Journal:  Breast       Date:  2015-08-05       Impact factor: 4.380

Review 2.  Heat shock proteins; an overview.

Authors:  Lütfi Tutar; Yusuf Tutar
Journal:  Curr Pharm Biotechnol       Date:  2010-02       Impact factor: 2.837

Review 3.  Molecular classification of breast cancer: limitations and potential.

Authors:  Lajos Pusztai; Chafika Mazouni; Keith Anderson; Yun Wu; W Fraser Symmans
Journal:  Oncologist       Date:  2006-09

4.  Evaluation of miR-16 as an internal control in the patients with breast cancer.

Authors:  Soheil Madadi; Meysam Soleimani
Journal:  Hum Pathol       Date:  2018-11-17       Impact factor: 3.466

Review 5.  HER2 in breast cancer: a review and update.

Authors:  Uma Krishnamurti; Jan F Silverman
Journal:  Adv Anat Pathol       Date:  2014-03       Impact factor: 3.875

6.  Immunohistochemical Surrogates for Molecular Classification of Breast Carcinoma: A 2015 Update.

Authors:  Ping Tang; Gary M Tse
Journal:  Arch Pathol Lab Med       Date:  2016-08       Impact factor: 5.534

Review 7.  Biological subtypes of breast cancer: Prognostic and therapeutic implications.

Authors:  Ozlem Yersal; Sabri Barutca
Journal:  World J Clin Oncol       Date:  2014-08-10

Review 8.  Breast cancer intrinsic subtype classification, clinical use and future trends.

Authors:  Xiaofeng Dai; Ting Li; Zhonghu Bai; Yankun Yang; Xiuxia Liu; Jinling Zhan; Bozhi Shi
Journal:  Am J Cancer Res       Date:  2015-09-15       Impact factor: 6.166

9.  Different signatures of miR-16, miR-30b and miR-93 in exosomes from breast cancer and DCIS patients.

Authors:  Qingtao Ni; Ines Stevic; Chi Pan; Volkmar Müller; Leticia Oliveira-Ferrer; Klaus Pantel; Heidi Schwarzenbach
Journal:  Sci Rep       Date:  2018-08-28       Impact factor: 4.379

10.  Breast tumor subgroups reveal diverse clinical prognostic power.

Authors:  Zhaoqi Liu; Xiang-Sun Zhang; Shihua Zhang
Journal:  Sci Rep       Date:  2014-02-06       Impact factor: 4.379

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  1 in total

1.  Prediction of Pathogenic Factors in Dysbiotic Gut Microbiomes of Colorectal Cancer Patients Using Reverse Microbiomics.

Authors:  Haihe Wang; Kaibo Zhang; Lin Wu; Qian Qin; Yongqun He
Journal:  Front Oncol       Date:  2022-04-27       Impact factor: 5.738

  1 in total

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