Literature DB >> 35855195

An In Silico Analysis Identified Members of the Pleckstrin Homology-Like Domain, Family B (PHLDB family) as Potential Prognostic and Predictive Biomarkers of Treatment Response in Breast Cancer Patients.

Renan Gomes do Nascimento1,2,3, Jéssica de Moraes4,5, Danilo de Oliveira Cerqueira1,3, Sandro Jorge Januário1,6.   

Abstract

Objective: Breast cancer is the leading cause of morbidity and mortality in women worldwide. This malignant neoplasm can be classified into four clinically relevant subtypes according to the expression of a number of biomarkers. However, these tumors show considerable intratumoral heterogeneity and multidrug resistance. Members of the pleckstrin homology-like domain, family B (PHLDB) play a critical role in the regulation of p53 and AKT signaling pathways, important for cancer and cellular metabolism. The present study was performed to evaluate the expression pattern of PHLDB family members in breast cancer and its potential prognostic and predictive value for therapeutic response using bioinformatics tools. Materials and
Methods: This in silico analysis was performed using several online repositories, including UALCAN, GEPIA2, bc-GenExMiner, KM Plotter, PrognoScan and ROC Plotter.
Results: PHLDB family genes were found to be differentially expressed in tumor samples when compared to healthy breast tissue samples. Furthermore, epigenetic regulation may be one of the regulatory mechanisms for the expression of these markers. The PHLDB family of genes proved to be potential markers for predicting the development of lymph node metastasis (p<0.0001) and poor clinical outcome. All members of the PHLDB family were significantly correlated with hormone receptors. High levels of PHLDBs expression were associated with worse overall survival and recurrence-free survival in breast cancer patients. Finally, our data demonstrate that members of the PHLDB family can be promising markers in the stratification of patients who may or may not respond to different available therapies.
Conclusion: Our cumulative results demonstrate that PHLDB family members may be promising biomarkers for predicting prognosis and therapeutic response in breast cancer patients. ©Copyright 2022 by the the Turkish Federation of Breast Diseases Societies / European Journal of Breast Health published by Galenos Publishing House.

Entities:  

Keywords:  Breast cancer; PHLDB; biomarkers; in silico analysis

Year:  2022        PMID: 35855195      PMCID: PMC9255658          DOI: 10.4274/ejbh.galenos.2022.2022-3-5

Source DB:  PubMed          Journal:  Eur J Breast Health


  30 in total

Review 1.  Pleckstrin homology (PH) like domains - versatile modules in protein-protein interaction platforms.

Authors:  Klaus Scheffzek; Stefan Welti
Journal:  FEBS Lett       Date:  2012-06-19       Impact factor: 4.124

2.  Down-regulation of PHLDA1 gene expression is associated with breast cancer progression.

Authors:  Maria Aparecida Nagai; José Humberto T G Fregnani; Mário Mourão Netto; Maria Mitzi Brentani; Fernando A Soares
Journal:  Breast Cancer Res Treat       Date:  2007-01-09       Impact factor: 4.872

3.  bc-GenExMiner: an easy-to-use online platform for gene prognostic analyses in breast cancer.

Authors:  Pascal Jézéquel; Mario Campone; Wilfried Gouraud; Catherine Guérin-Charbonnel; Christophe Leux; Gabriel Ricolleau; Loïc Campion
Journal:  Breast Cancer Res Treat       Date:  2011-03-31       Impact factor: 4.872

Review 4.  Breast cancer.

Authors:  Nadia Harbeck; Frédérique Penault-Llorca; Javier Cortes; Michael Gnant; Nehmat Houssami; Philip Poortmans; Kathryn Ruddy; Janice Tsang; Fatima Cardoso
Journal:  Nat Rev Dis Primers       Date:  2019-09-23       Impact factor: 52.329

5.  Modulation of ErbB2 blockade in ErbB2-positive cancers: the role of ErbB2 Mutations and PHLDA1.

Authors:  Guangyuan Li; Xiaoqi Wang; Hanina Hibshoosh; Cheng Jin; Balazs Halmos
Journal:  PLoS One       Date:  2014-09-19       Impact factor: 3.240

6.  UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses.

Authors:  Darshan S Chandrashekar; Bhuwan Bashel; Sai Akshaya Hodigere Balasubramanya; Chad J Creighton; Israel Ponce-Rodriguez; Balabhadrapatruni V S K Chakravarthi; Sooryanarayana Varambally
Journal:  Neoplasia       Date:  2017-07-18       Impact factor: 5.715

7.  GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis.

Authors:  Zefang Tang; Boxi Kang; Chenwei Li; Tianxiang Chen; Zemin Zhang
Journal:  Nucleic Acids Res       Date:  2019-07-02       Impact factor: 16.971

Review 8.  PI3K/AKT/mTOR Signaling Pathway in Breast Cancer: From Molecular Landscape to Clinical Aspects.

Authors:  Daniela Miricescu; Alexandra Totan; Iulia-Ioana Stanescu-Spinu; Silviu Constantin Badoiu; Constantin Stefani; Maria Greabu
Journal:  Int J Mol Sci       Date:  2020-12-26       Impact factor: 5.923

9.  Computational Analysis of the Binding Specificities of PH Domains.

Authors:  Zhi Jiang; Zhongjie Liang; Bairong Shen; Guang Hu
Journal:  Biomed Res Int       Date:  2015-12-31       Impact factor: 3.411

10.  PHLDA1, another PHLDA family protein that inhibits Akt.

Authors:  Yu Chen; Masahiro Takikawa; Shuichi Tsutsumi; Yoko Yamaguchi; Atsushi Okabe; Mayuna Shimada; Tatsuya Kawase; Akane Sada; Issei Ezawa; Yuhei Takano; Kisaburo Nagata; Yutaka Suzuki; Kentaro Semba; Hiroyuki Aburatani; Rieko Ohki
Journal:  Cancer Sci       Date:  2018-10-13       Impact factor: 6.716

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