MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome

Abstract Background Breast cancer is a heterogeneous disease with diverse molecular subtypes, underscoring a better understanding of its molecular features and underlying regulatory mechanisms. Therefore, identifying novel prognostic biomarkers and therapeutic targets is crucial for advancing the cu...

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Main Authors: Bushra Yasin Abohalawa, Hibah Shaath, Ramesh Elango, Radhakrishnan Vishnubalaji, Sameera Rashid, Reem Al-Sarraf, Mohammed Akhtar, Nehad M. Alajez
Format: Article
Language:English
Published: BMC 2024-11-01
Series:Cancer Cell International
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Online Access:https://doi.org/10.1186/s12935-024-03550-8
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author Bushra Yasin Abohalawa
Hibah Shaath
Ramesh Elango
Radhakrishnan Vishnubalaji
Sameera Rashid
Reem Al-Sarraf
Mohammed Akhtar
Nehad M. Alajez
author_facet Bushra Yasin Abohalawa
Hibah Shaath
Ramesh Elango
Radhakrishnan Vishnubalaji
Sameera Rashid
Reem Al-Sarraf
Mohammed Akhtar
Nehad M. Alajez
author_sort Bushra Yasin Abohalawa
collection DOAJ
description Abstract Background Breast cancer is a heterogeneous disease with diverse molecular subtypes, underscoring a better understanding of its molecular features and underlying regulatory mechanisms. Therefore, identifying novel prognostic biomarkers and therapeutic targets is crucial for advancing the current standard of care for breast cancer patients. Methods Ninety-six formalin-fixed paraffin-embedded (FFPE) breast cancer samples underwent miRNAome profiling using QIAseq microRNA library kit and sequencing on Illumina platform. Mature miRNA quantification was conducted using CLC Genomics Workbench v21.0.5, while Relapse-free survival (RFS) analysis was conducted using RStudio 2023.09.1. Gain-of-function studies were conducted using miRNA mimics, while the effects of miRNA exogenous expression on cancer hallmark were assessed using 2-dimentional (2D) proliferation assay, three-dimensional (3D) organotypic culture, and live-dead staining. TargetScan database and Ingenuity Pathway Analysis (IPA) were used for miRNA target identification. Results Hierarchical clustering based on miRNA expression revealed distinct patterns in relation to PAM50 classification and identified miRNAs panels associated with luminal, HER2, and basal subtypes. hsa-miR-5683 emerged as a potential prognostic biomarker, showing a favorable correlation with RFS and suppressing tumorigenicity under 2D and 3D conditions in triple-negative breast cancer (TNBC) models. Findings were further extended to the MCF7 hormone receptor positive (HR+) model. Transcriptomic profiling of hsa-miR-5683 overexpressing TNBC cells revealed its potential role in key oncogenic pathways. Integration of downregulated genes and CRISPR-Cas9 perturbational effects identified ACLY, RACGAP1, AK4, MRPL51, CYB5B, MKRN1, TMEM230, NUP54, ANAPC13, PGAM1, and SOD1 as bona fide gene targets for hsa-miR-5683. Conclusions Our data provides comprehensive miRNA expression atlas in breast cancer subtypes and underscores the prognostic and therapeutic significance of numerous miRNAs, including hsa-miR-5683 in TNBC. The identified gene targets unravel the intricate regulatory network in TNBC progression, suggesting promising avenues for further research and targeted therapeutic interventions.
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spelling doaj-art-3e8d9b41d87f4973a9e2ce64d25b62222024-11-17T12:49:46ZengBMCCancer Cell International1475-28672024-11-0124111310.1186/s12935-024-03550-8MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcomeBushra Yasin Abohalawa0Hibah Shaath1Ramesh Elango2Radhakrishnan Vishnubalaji3Sameera Rashid4Reem Al-Sarraf5Mohammed Akhtar6Nehad M. Alajez7College of Health & Life Sciences, Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF)Translational Oncology Research Center (TORC), Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF)Translational Oncology Research Center (TORC), Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF)Translational Oncology Research Center (TORC), Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF)Department of Laboratory Medicine and Pathology (DLMP), Hamad Medical Corporation (HMC)Department of Laboratory Medicine and Pathology (DLMP), Hamad Medical Corporation (HMC)Department of Laboratory Medicine and Pathology (DLMP), Hamad Medical Corporation (HMC)College of Health & Life Sciences, Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF)Abstract Background Breast cancer is a heterogeneous disease with diverse molecular subtypes, underscoring a better understanding of its molecular features and underlying regulatory mechanisms. Therefore, identifying novel prognostic biomarkers and therapeutic targets is crucial for advancing the current standard of care for breast cancer patients. Methods Ninety-six formalin-fixed paraffin-embedded (FFPE) breast cancer samples underwent miRNAome profiling using QIAseq microRNA library kit and sequencing on Illumina platform. Mature miRNA quantification was conducted using CLC Genomics Workbench v21.0.5, while Relapse-free survival (RFS) analysis was conducted using RStudio 2023.09.1. Gain-of-function studies were conducted using miRNA mimics, while the effects of miRNA exogenous expression on cancer hallmark were assessed using 2-dimentional (2D) proliferation assay, three-dimensional (3D) organotypic culture, and live-dead staining. TargetScan database and Ingenuity Pathway Analysis (IPA) were used for miRNA target identification. Results Hierarchical clustering based on miRNA expression revealed distinct patterns in relation to PAM50 classification and identified miRNAs panels associated with luminal, HER2, and basal subtypes. hsa-miR-5683 emerged as a potential prognostic biomarker, showing a favorable correlation with RFS and suppressing tumorigenicity under 2D and 3D conditions in triple-negative breast cancer (TNBC) models. Findings were further extended to the MCF7 hormone receptor positive (HR+) model. Transcriptomic profiling of hsa-miR-5683 overexpressing TNBC cells revealed its potential role in key oncogenic pathways. Integration of downregulated genes and CRISPR-Cas9 perturbational effects identified ACLY, RACGAP1, AK4, MRPL51, CYB5B, MKRN1, TMEM230, NUP54, ANAPC13, PGAM1, and SOD1 as bona fide gene targets for hsa-miR-5683. Conclusions Our data provides comprehensive miRNA expression atlas in breast cancer subtypes and underscores the prognostic and therapeutic significance of numerous miRNAs, including hsa-miR-5683 in TNBC. The identified gene targets unravel the intricate regulatory network in TNBC progression, suggesting promising avenues for further research and targeted therapeutic interventions.https://doi.org/10.1186/s12935-024-03550-8Breast cancermicroRNASurvivalPrognostic biomarkerTherapeutic target
spellingShingle Bushra Yasin Abohalawa
Hibah Shaath
Ramesh Elango
Radhakrishnan Vishnubalaji
Sameera Rashid
Reem Al-Sarraf
Mohammed Akhtar
Nehad M. Alajez
MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome
Cancer Cell International
Breast cancer
microRNA
Survival
Prognostic biomarker
Therapeutic target
title MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome
title_full MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome
title_fullStr MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome
title_full_unstemmed MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome
title_short MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome
title_sort micrornaome profiling of breast cancer unveils hsa mir 5683 as a tumor suppressor microrna predicting favorable clinical outcome
topic Breast cancer
microRNA
Survival
Prognostic biomarker
Therapeutic target
url https://doi.org/10.1186/s12935-024-03550-8
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