Subha Madhavan

Super enhancer inhibitors suppress MYC driven transcriptional amplification and tumor progression in osteosarcoma

Osteosarcoma is the most common primary bone sarcoma that mostly occurs in young adults. The causes of osteosarcoma are heterogeneous and still not fully understood. Identification of novel, important oncogenic factors in osteosarcoma and development of better, effective therapeutic approaches are in urgent need for better treatment of osteosarcoma patients. In this study, we uncovered that the oncogene MYC is significantly upregulated in metastastic osteosarcoma samples. In addition, high MYC expression is associated with poor survival of osteosarcoma patients. Analysis of MYC targets in osteosarcoma revealed that most of the osteosarcoma super enhancer genes are bound by MYC. Treatment of osteosarcoma cells with super enhancer inhibitors THZ1 and JQ1 effectively suppresses the proliferation, migration, and invasion of osteosarcoma cells. Mechanistically, THZ1 treatment suppresses a large group of super enhancer containing MYC target genes including CDK6 and TGFB2. These findings revealed that the MYC-driven super enhancer signaling is crucial for the osteosarcoma tumorigenesis and targeting the MYC/super enhancer axis represents as a promising therapeutic strategy for treatment of osteosarcoma patients.Bone cancer: Disease-promoting DNA regions revealed as therapeutic targetsInsight into a molecular pathway involved in an aggressive bone cancer has suggested a new approach to its treatment. Osteosarcoma usually develops in growing bone tissue, but often spreads to other organs, consequently reducing survival. The molecular mechanisms behind osteosarcoma are not fully understood. A team led by Shuibin Lin from Sun Yat-sen University investigated the role of MYC, a gene that is important in other cancers. They found that increased expression of MYC is associated with the spread of osteosarcoma and a poor prognosis because the protein product of MYC activates many super-enhancers, regions of DNA that increase the expression of cancer-related genes. Inhibition of the super-enhancers suppressed growth and spreading of osteosarcoma in cultured cells and a mouse model, suggesting a novel therapeutic approach to osteosarcoma.

Identification of a novel metabolic-related mutation (IDH1) in metastatic pancreatic cancer.

ABSTRACT Isocitrate dehydrogenase 1 (IDH1) is a metabolic enzyme implicated in cancer cell metabolic reprogramming. This is underscored by the detection of functional, somatic IDH1 mutations frequently found in secondary glioblastoma. To our knowledge, there has never been a reported, validated case of an IDH1 mutation in a pancreatic ductal adenocarcinoma (PDA). Herein, we present a case of a patient with metastatic PDA that harbored a potentially actionable, albeit rare, IDH1 mutation. As part of the Know Your Tumor project (Pancreatic Cancer Action Network), a 48-year-old female was diagnosed with metastatic PDA and subsequently started on standard of care chemotherapy, during which her hepatic lesions progressed. Detailed molecular profiling was performed on a biopsy from a liver lesion that demonstrated an IDH1 mutation, R132H. This mutation was confirmed by an independent sequencing reaction from the tumor sample, and by immunohistochemistry using an antibody specific for the IDH1 R132H mutation. The patient subsequently received a mutant IDH1 inhibitor (AG-120, Agios Pharmaceuticals, Cambridge, MA), but with no response. IDH1 mutations are common in certain cancer types, but have not been reported in PDA. We report the first case of an IDH1 mutation in this tumor type, perhaps providing a rare opportunity for a targeted therapy as a treatment option for PDA.

Eye-Tracking Study to Enhance Usability of Molecular Diagnostics Reports in Cancer Precision Medicine

PurposeWe conducted usability studies on commercially available molecular diagnostic (MDX) test reports to identify strengths and weaknesses in content and form that drive clinical decision making. Given routine genomic testing in cancer medicine, oncologists must interpret MDX reports as well as evidence concerning clinical utility of biomarkers accurately for treatment or trial selection. This work aims to evaluate effectiveness of MDX reports in facilitating cancer treatment planning.MethodsFourteen clinicians at an academic tertiary care medical facility, with a wide range of experience in oncology and in the use of molecular testing, participated in this study. Three commercially available, widely used, Clinical Laboratory Improvement Amendments (CLIA)–certified, College of American Pathologists (CAP)–accredited test reports (labeled Laboratories A, B, and C) were used. Eye tracking, surveys, and think-aloud protocols were used to collect usability data for these MDX reports focusing on ease of compr...

A harmonized meta-knowledgebase of clinical interpretations of cancer genomic variants

Precision oncology relies on the accurate discovery and interpretation of genomic variants to enable individualized therapy selection, diagnosis, or prognosis. However, knowledgebases containing clinical interpretations of somatic cancer variants are highly disparate in interpretation content, structure, and supporting primary literature, reducing consistency and impeding consensus when evaluating variants and their relevance in a clinical setting. With the cooperation of experts of the Global Alliance for Genomics and Health (GA4GH) and of six prominent cancer variant knowledgebases, we developed a framework for aggregating and harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations covering 3,437 unique variants in 415 genes, 357 diseases, and 791 drugs. We demonstrated large gains in overlapping terms between resources across variants, diseases, and drugs as a result of this harmonization. We subsequently demonstrated improved matching between patients of the GENIE cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 34% to 57% in aggregate. We developed an open and freely available web interface for exploring the harmonized interpretations from these six knowledgebases at search.cancervariants.org.

The REMBRANDT study, a large collection of genomic data from brain cancer patients

The Rembrandt brain cancer dataset includes 671 patients collected from 14 contributing institutions from 2004–2006. It is accessible for conducting clinical translational research using the open access Georgetown Database of Cancer (G-DOC) platform. In addition, the raw and processed genomics and transcriptomics data have also been made available via the public NCBI GEO repository as a super series GSE108476. Such combined datasets would provide researchers with a unique opportunity to conduct integrative analysis of gene expression and copy number changes in patients alongside clinical outcomes (overall survival) using this large brain cancer study.