HerceptinR: A database of herceptin resistant breast cancer patients/cells

Welcome to the official documentation for HerceptinR, a comprehensive database designed to help researchers and clinicians understand the molecular mechanisms behind Trastuzumab (Herceptin) resistance in breast cancer patients. Herceptin is a frontline monoclonal antibody therapy for HER2-positive breast cancer, yet approximately 70% of patients experience de novo or acquired resistance. Web Server: http://crdd.osdd.net/raghava/herceptinr/ (https://webs.iiitd.edu.in/raghava/herceptinr) Citation Ahmad, S., Gupta, S., Kumar, R., Varshney, G. C., & Raghava, G. P. S. (2014). Herceptin Resistance Database for Understanding Mechanism of Resistance in Breast Cancer Patients. Scientific Reports, 4, 4483. https://doi.org/10.1038/srep04483 GitHUB:-https://github.com/Manish-IIITD-repository/HerceptinR About the Platform HerceptinR provides a unified platform that correlates experimental assay data with deep genomic insights. By integrating inhomogeneous data from scattered sources, the database allows for a gross view of how mutations, gene expression, and copy number variations (CNV) contribute to drug resistance. Data Overview Assay Data: Information on 2,500 assays performed against various breast cancer cell lines. Cell Lines: Genomic and pharmacological profiles for 51 breast cancer cell lines (BCCs). Supplementary Drugs: Sensitivity data for 111 drugs/chemicals tested in combination with Herceptin. Genomic Factors: Integration of data from CCLE (Cancer Cell Line Encyclopedia) including 16,582 genes. Key Features Assay Exploration Simple & Advanced Search: Query assays by cell line name, supplementary drug, resistance status, or specific genomic alterations. Browse PMIDs: Access data acquired from 75 research articles with direct links to PubMed and full-text PDFs. Alteration Analysis: Browse 337 types of reported cell line alterations (e.g., siRNA silencing or ectopic expression) to see their impact on Herceptin efficacy. Genomic Analysis Tools Mutation Search: Explore the mutational status of key genes, searchable by protein family, domain, or subcellular localization. Summary of Cell Line: View a complete genomic "snapshot," including lists of over-expressed and under-expressed genes. Multiple Cell Line Comparison: Instantly compare up to five cell lines based on their mutational, expression, and CNV status. Relative GE/CNVs: Pairwise comparison tool to identify the ratio or difference in expression/CNV of specific genes between two cell lines. Visualization & Alignment Drug Sensitivity Plots: View drugs plotted in decreasing order of IC50 to identify the most effective supplementary drug candidates. Alignment of Mutants: Multiple sequence alignment of important mutant genes (e.g., PIK3CA, PTEN, TP53) using the Jalview applet. Technical Overview Backend: Apache HTTP Server 2.2 with MySQL 5.1.47. Frontend: PHP 5.2.9, HTML, and JavaScript. Data Sources: Integrated data from PubMed, CCLE, CancerDR, and UniProt. Gene Sets: Specifically tracks 22 genes involved in resistance via expression and 8 genes involved via mutation. Applications Biomarker Discovery: Identifying genomic signatures that predict whether a patient will respond to Herceptin. Personalized Medicine: Selecting the most appropriate supplementary drug combination based on the specific genomic constraints of a patient's cancer. Target Identification: Locating new molecular targets by studying alterations that reverse resistance in vitro. Contact & Authors Prof. Gajendra P.S. Raghava Department of Computational Biology, Indraprastha Institute of Information Technology (IIIT-Delhi), India. Email: [e-mail] License This resource is licensed under a Creative Commons Attribution NonCommercial-ShareAlike 3.0 Unported License.