MammOnc-DB, an integrative breast cancer data analysis platform for target discovery

Breast cancer (BCa), a leading malignancy among women, is characterized by morphological and molecular heterogeneity. While early-stage, hormone receptor, and HER2-positive BCa are treatable, triple-negative BCa and metastatic BCa remains largely untreatable. Advances in sequencing and proteomic technologies have improved our understanding of the molecular alterations that occur during BCa initiation and progression and enabled identification of subclass-specific biomarkers and therapeutic targets. Despite the availability of abundant omics data in public repositories, user-friendly tools for multi-omics data analysis and integration are scarce. To address this, we developed a comprehensive BCa data analysis platform called MammOnc-DB ( http://resource.path.uab.edu/MammOnc-Home.html ), comprising data from more than 20,000 BCa samples. MammOnc-DB facilitates hypothesis generation and testing, biomarker discovery, and therapeutic targets identification. The platform also includes pre- and post-treatment data, which can help users identify treatment resistance markers and support combination therapy strategies, offering researchers and clinicians a comprehensive tool for BCa data analysis and visualization.

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Institutions

Publication Details

Journal
npj Breast Cancer
Published
2025-04-18
DOI
https://doi.org/10.1038/s41523-025-00750-x
Citations
9
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
7.25

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article

MammOnc-DB, an integrative breast cancer data analysis platform for target discovery

Raj Singh, Santhosh Kumar Karthikeyan, Zhaohui Qin, Chad J. Creighton et al.
9 citations
npj Breast Cancer
Bioinformatics and Genomic Networks
7.25
article

MammOnc-DB, an integrative breast cancer data analysis platform for target discovery

Raj Singh, Santhosh Kumar Karthikeyan, Zhaohui Qin, Chad J. Creighton, Darshan S. Chandrashekar, Upender Manne, Celina G. Kleer, Sadeep Shrestha, Harikrishna Nakshatri, Sooryanarayana Varambally, Sidharth Kumar, Snigdha Sahai, Ritu Aneja
article en
9 citations

Abstract

Breast cancer (BCa), a leading malignancy among women, is characterized by morphological and molecular heterogeneity. While early-stage, hormone receptor, and HER2-positive BCa are treatable, triple-negative BCa and metastatic BCa remains largely untreatable. Advances in sequencing and proteomic technologies have improved our understanding of the molecular alterations that occur during BCa initiation and progression and enabled identification of subclass-specific biomarkers and therapeutic targets. Despite the availability of abundant omics data in public repositories, user-friendly tools for multi-omics data analysis and integration are scarce. To address this, we developed a comprehensive BCa data analysis platform called MammOnc-DB ( http://resource.path.uab.edu/MammOnc-Home.html ), comprising data from more than 20,000 BCa samples. MammOnc-DB facilitates hypothesis generation and testing, biomarker discovery, and therapeutic targets identification. The platform also includes pre- and post-treatment data, which can help users identify treatment resistance markers and support combination therapy strategies, offering researchers and clinicians a comprehensive tool for BCa data analysis and visualization.

npj Breast CancerVol. 11(1)
Alabama Department of Public Health (US), University of Alabama at Birmingham Hospital (US), Emory University (US), Baylor College of Medicine (US), University of Michigan (US), University of Alabama at Birmingham (US), University of Illinois Chicago (US), Indiana University School of Medicine, Indiana University – Purdue University Indianapolis (US), Morehouse School of Medicine (US)
Breast Cancer Research Foundation
Good health and well-being
Openalex Percentile: Top 3%
Bioinformatics and Genomic Networks
7.25
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