Advisor(s)
Sooryanarayana Varambally
Committee Member(s)
Darshan Shimoga Chandrashekar
Eason Hildreth
Selvarangan Ponnazhagan
Shahid Mukthar
Upender Manne
School
Joint Health Sciences (Interdisciplinary)
Document Type
Dissertation
Department (new version)
Pathology
Date of Award
1-6-2025
Abstract
ABSTRACT In 2024, breast cancer (BCa) emerged as the most prevalent cancer among women, accounting for 15% of fatalities in the United States. BCa is a multifaceted disease characterized by various molecular alterations associated with tumor initiation, progression, and metastasis. Clinically, different treatments such as endocrine therapy, chemotherapy, and anti-HER2 therapy are employed based on the molecular subtypes of breast cancer. Despite initial treatment responses, some cases experience recurrence due to therapy resistance. The application of next-generation sequencing techniques and data analysis has significantly enhanced our understanding of BCa biology, including its initiation and progression. By exploring BCa multi-omics data, we can uncover therapeutic vulnerabilities and identify novel biomarkers. However, existing cancer web resources have yet to fully leverage the vast amounts of publicly available multi-omics data. Despite the availability of computational tools, there remains an unmet need to effectively utilize large-scale multi-omics BCa data for identifying these biomarkers and achieving personalized treatments. To address this gap, we have developed an integrated BCa proteo-genomic data analysis portal called MammOnc-DB. MammOnc-DB was developed to provide a unique resource for hypothesis generation and testing, as well as for the discovery of biomarkers and therapeutic targets. In this thesis we present MammOnc-DB, an interactive and user-friendly database, for comprehensive analysis and visualization of genomic (microarray, bulk RNA-seq and single cell RNA-seq), epigenetic (DNA Methylation array, and ChIP-seq) and proteomics (MS) data obtained from TCGA, NCBI GEO, CCLE, METABRIC, Weizmann Cell Atlas, CPTAC, PRIDE and ProteomeXchange etc. Conclusively, MammOnc-DB is a comprehensive resource that houses analyzed multi-omics data from normal breast tissue and primary and metastatic breast cancer (BCa) samples, along with clinical information. It encompasses various clinical models, including human tissues, mice, and cell line models. Additionally, the database incorporates therapy and post-treatment studies currently used in treating BCa patients. Our goal with MammOnc-DB (http://resource.path.uab.edu/MammOnc-Home.html) is to foster a global user community that accelerates the discovery of diagnostic markers, therapeutic targets, and effective treatments for breast cancer.
ProQuest ID
Recommended Citation
Karthikeyan, Santhosh Kumar, "Mammonc-Db: A Proteo-Genomic Platform For Comprehensive Breast Cancer Data Analysis, Integration And Visualization" (2025). All ETDs from UAB. 7281.
https://digitalcommons.library.uab.edu/etd-collection/7281
