It is now clear that response to targeted therapies in cancer is dictated by the molecular characteristics of an individual patient's tumor. The industry is increasingly looking to genomics-based analyses to link drug response phenotypes to underlying genetic mutations and multiplex molecular signatures. Such analyses are hindered by three fundamental challenges. First, cancer comprises a diverse collection of potentially hundreds of distinct molecular diseases and most preclinical experiments are not of the appropriate scale to represent this diversity. Second, most analyses are limited in their scope of genomic associations, focusing on only one out of several possible characterizations (e.g. mutations, gene expression, DNA copy number). Finally, most analyses are missing the last crucial step, which is to map multiplex genetic biomarkers of drug response to clinical tumor populations. Compendia Bioscience seeks to address these fundamental challenges and provide an oncogenomics drug profiling solution that: assesses a broad panel of cancer cell lines for response to a given compound; defines sensitive and refractory cell line populations; performs detailed genomics correlation analysis spanning gene expression DNA copy number and mutations; develops and refines multiplex genetic biomarker(s) of response; and analyzes response biomarker(s) across nearly 30,000 highly curated clinical cancer specimens to identify patient populations and subpopulations likely to respond. The solution builds upon the functionality and resources previously established in Oncomine, a comprehensive gene expression database that collects, standardizes, and analyzes publicly available gene expression data. This will be accomplished by extending the flexibility of Oncomine to capture new metadata on existing studies: by overcoming technical obstacles associated with incorporating new data types; and by utilizing the full range of available data in logical ways to support drug development workflows. The Specific Aims of this Phase I proposal are to: 1. Catalog and annotate publicly available gene mutation data for 300+ cancer cell line panel. 2. Process and integrate DNA copy number data for 300+ cancer cell line panel. 3. Develop method to call amplifications and deletions from DNA copy number data and integrate with mutation data. Altogether the aims of this proposal significantly contribute to proving the feasibility of the overall approach: by assembling critical data elements for a large cell line panel and then directly comparing concordance between cell line data and tumor data.
Public Health Relevance: Despite enormous investments in genomics technology aimed at improving the drug development pipeline, cancer remains a leading cause of mortality in the United States. This proposal seeks to advance preclinical drug development efforts by maximizing the value of experimentally robust, well-characterized cell lines, and using the results of those studies to inform patient selection in clinical trials of novel therapeutic compounds. This will improve public health by making it easier for drug development companies to identify patient populations likely to benefit from novel compounds, and to successfully advance those compounds through clinical trials and to the marketplace.
Public Health Relevance Statement: Project Narrative Despite enormous investments in genomics technology aimed at improving the drug development pipeline, cancer remains a leading cause of mortality in the United States. This proposal seeks to advance preclinical drug development efforts by maximizing the value of experimentally robust, well-characterized cell lines, and using the results of those studies to inform patient selection in clinical trials of novel therapeutic compounds. This will improve public health by making it easier for drug development companies to identify patient populations likely to benefit from novel compounds, and to successfully advance those compounds through clinical trials and to the marketplace.
NIH Spending Category: Biotechnology; Cancer; Genetics; Human Genome
Project Terms: Address; Anti-Cancer Agents; Anti-Tumor Agents; Anti-Tumor Drugs; Antineoplastic Agents; Antineoplastic Drugs; Antineoplastics; Antiproliferative Agents; Antiproliferative Drugs; Bio-Informatics; Bioinformatics; Biologic Sciences; Biological Sciences; Biotechnology; Cancer Cause; Cancer Drug; Cancer Etiology; Cancer Gene Mutation; Cancer Treatment; Cancer cell line; Cancers; Cataloging; Catalogs; Cell Line; Cell Lines, Strains; CellLine; Characteristics; Chemotherapeutic Agents, Neoplastic Disease; Clinical; Clinical Trials; Clinical Trials, Unspecified; Collection; Communities; Complex; Cosmic; DNA; DNA Alteration; DNA Chips; DNA Microarray; DNA Microarray Chip; DNA Microchips; DNA copy number; DNA mutation; Data; Data Banks; Data Bases; Data Element; Data Set; Databank, Electronic; Databanks; Database, Electronic; Databases; Dataset; Deoxyribonucleic Acid; Development; Disease; Disorder; Drug Development, Preclinical; Drug Testing/Development, Preclinical; Drugs; Environment; Explosion; Expression Profiling; Expression Signature; Fill-It; Gene Alteration; Gene Expression; Gene Expression Profile; Gene Mutation; Genes; Genetic; Genetic Alteration; Genetic Change; Genetic Condition; Genetic Diseases; Genetic defect; Genetic mutation; Genomics; Goals; Hereditary Disease; Individual; Industry; Institutes; Investments; Knowledge; Libraries; Licensing; Life Sciences; Ligands; Link; Malignant Neoplasm Therapy; Malignant Neoplasm Treatment; Malignant Neoplasms; Malignant Tumor; Maps; Medication; Medicine; Metadata; Methods; Microarray Analysis; Microarray-Based Analysis; Molecular; Molecular Disease; Molecular Fingerprinting; Molecular Profiling; Mortality; Mortality Vital Statistics; Mutation; Nomenclature; Pathway interactions; Patient Selection; Patients; Pattern; Pharmaceutic Preparations; Pharmaceutical Agent; Pharmaceutical Preparations; Pharmaceuticals; Pharmacologic Substance; Pharmacological Substance; Phase; Phenotype; Population; Position; Positioning Attribute; Preclinical Drug Development; Process; Public Health; Receptor Protein; Refractory; Research; Research Resources; Research Specimen; Resources; Risk; Sampling; Science of Medicine; Sequence Alteration; Services; Solutions; Source; Specimen; Staging; Technology; Testing; Translating; Translatings; Tumor-Specific Treatment Agents; United States; Work; anticancer agent; anticancer drug; anticancer therapy; base; biomarker; cancer genomics; cancer progression; cancer therapy; cancer type; clinical data repository; clinical data warehouse; clinical investigation; cultured cell line; data integration; data repository; design; designing; disease/disorder; drug development; drug sensitivity; drug/agent; experiment; experimental research; experimental study; flexibility; gene expression signature; genetic disorder; genome mutation; genome-wide; hereditary disorder; improved; innovate; innovation; innovative; language translation; malignancy; microarray technology; molecuar profile; molecular signature; neoplasm progression; neoplasm/cancer; neoplastic progression; new approaches; new therapeutics; next generation therapeutics; novel; novel approaches; novel strategies; novel strategy; novel therapeutics; pathway; patient population; pre-clinical; preclinical; public health medicine (field); public health relevance; receptor; relational database; research study; response; technological innovation; transcriptome; tumor; tumor progression
