13 research outputs found
An international working group consensus report for the prioritization of molecular biomarkers for Ewing sarcoma
The advent of dose intensified interval compressed therapy has improved event-free survival for patients with localized Ewing sarcoma (EwS) to 78% at 5 years. However, nearly a quarter of patients with localized tumors and 60-80% of patients with metastatic tumors suffer relapse and die of disease. In addition, those who survive are often left with debilitating late effects. Clinical features aside from stage have proven inadequate to meaningfully classify patients for risk-stratified therapy. Therefore, there is a critical need to develop approaches to risk stratify patients with EwS based on molecular features. Over the past decade, new technology has enabled the study of multiple molecular biomarkers in EwS. Preliminary evidence requiring validation supports copy number changes, and loss of function mutations in tumor suppressor genes as biomarkers of outcome in EwS. Initial studies of circulating tumor DNA demonstrated that diagnostic ctDNA burden and ctDNA clearance during induction are also associated with outcome. In addition, fusion partner should be a pre-requisite for enrollment on EwS clinical trials, and the fusion type and structure require further study to determine prognostic impact. These emerging biomarkers represent a new horizon in our understanding of disease risk and will enable future efforts to develop risk-adapted treatment
AI is a viable alternative to high throughput screening: a 318-target study
: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
An international working group consensus report for the prioritization of molecular biomarkers for Ewing sarcoma.
The advent of dose intensified interval compressed therapy has improved event-free survival for patients with localized Ewing sarcoma (EwS) to 78% at 5 years. However, nearly a quarter of patients with localized tumors and 60-80% of patients with metastatic tumors suffer relapse and die of disease. In addition, those who survive are often left with debilitating late effects. Clinical features aside from stage have proven inadequate to meaningfully classify patients for risk-stratified therapy. Therefore, there is a critical need to develop approaches to risk stratify patients with EwS based on molecular features. Over the past decade, new technology has enabled the study of multiple molecular biomarkers in EwS. Preliminary evidence requiring validation supports copy number changes, and loss of function mutations in tumor suppressor genes as biomarkers of outcome in EwS. Initial studies of circulating tumor DNA demonstrated that diagnostic ctDNA burden and ctDNA clearance during induction are also associated with outcome. In addition, fusion partner should be a pre-requisite for enrollment on EwS clinical trials, and the fusion type and structure require further study to determine prognostic impact. These emerging biomarkers represent a new horizon in our understanding of disease risk and will enable future efforts to develop risk-adapted treatment
Advances in the evaluation of anorectal function
AB is supported by USPHS NIH Grant DKDK7892