Cancer is one of the leading causes of morbidity and mortality worldwide. Driven by advancements in quantifying and characterizing the molecular profile of the tumor, cancer therapy is becoming more personalized, selective, and specific. A key factor contributing to the lethality, therapeutic failure, and drug resistance of cancer patients, however, is intra-tumor heterogeneity (ITH), characterized by a mixture of tumor cells with different complements of somatic mutations. ITH is found in almost every type of cancer and can be highly variable, with up to 8,000 different coding mutations found within primary tumors or between primary and metastatic or recurrence sites. High-throughput next-generation sequencing (NGS) technologies are now giving an early, unprecedented view of intra-tumor mutational heterogeneity, but challenges remain. Current barriers to progress exist in the arena of NGS analytical and computational software. There is an immediate need for NGS-compatible computational methods that can detect cellular lineages and distinct molecular mechanisms so clinicians can leverage the power of high-throughput NGS technology and fulfill the promise of precision oncology. The objective of this Phase I SBIR project is to explore the clinical feasibility of a novel computational platform, OncoGenomic Heterogeneity Software, that was designed using licensed technology from Brown University and is the first commercial product of Medley Genomics, a small business that was founded on the overall goal of building novel analytical approaches to define complex genomic heterogeneity and to understand human disease. The OncoGenomic Heterogeneity Software platform utilizes innovative analytical approaches to provide estimates of ITH with greater specificity, accuracy, and reproducibility than existing solutions. To explore the clinical feasibility of this technology, Medley Genomics will: Build on current technical validation studies to establish the optimal conditions for utilizing genomic heterogeneity software in primary breast tumors (Aim 1); Explore and evaluate the use of genomic heterogeneity software in formalin-fixed, paraffin-embedded breast tumor tissue, in comparison with fresh/frozen tissue (Aim 2); and enable the current genomic heterogeneity software to be compatible with cloud-based computing and HIPAA-compliant systems (Aim 3). The successful conclusion of this study will support a future Phase II SBIR effort that, in collaboration with colleagues at a large academic medical center, will constitute a clinical effort to retrospectively and then longitudinally evaluate the use of the OncoGenomic Heterogeneity Software package with NGS (and possibly single-cell sequencing) data to identify and characterize the ITH in primary tumors to inform early, targeted intervention(s) in cancer treatment. Enabling this technology has the potential to both streamline and simplify the interpretation of NGS data for evaluating ITH more comprehensively, thus allowing oncologists to prescribe more accurate, effective targeted therapies faster and with more confidence.
Precision oncology is the ability to treat cancer patients individually, in line with the unique mutational profiles of their tumors. These efforts are thwarted, however, given that existing technologies (i.e., next-generation sequencing, or NGS) are not able to fully account for the heterogeneous nature of tumors?current barriers to progress exist in the arena of NGS analytical and computational software. This project will advance a novel genomic heterogeneity software platform, championed by Medley Genomics, that is based on innovative algorithms and software licensed from Brown University, and validate its clinical feasibility by characterizing intra- tumor mutational heterogeneity in primary breast tumors (fresh and paraffin-embedded/formalin-fixed specimens). The purpose of this work is to provide computational solutions that will allow oncologists to further leverage the power of NGS in the clinic, and make precision oncology a reality.
