Patient-derived tumor xenograft (PDX) mouse models are a versatile oncology research platform for studying tumor biology and for testing chemotherapeutic approaches tailored to genomic characteristics of individual patients’ tumors. PDX models are generated and distributed by a diverse group of academic labs, multi-institution consortia and contract research organizations.
Save the Date: ITCR 2019 Annual Meeting will be held in Salt Lake City/Park City, Utah, May 28-31 2019.
Several ITCR investigators will be attending the Radiological Society of North America (RSNA) Annual Meeting in Chicago, November 25-30, 2018. Download the schedule for the presentations by ITCR investigators.
RSNA Annual Meeting, November 25-30, 2018
In this ITCR funded study Dr. Min Jin Ha and Dr. Veera Baladandayuthapani from the University of Texas MD Anderson Cancer Center and University of Michigan, assessed pan-cancer pathway activities for >7700 patients across 32 tumor types from The Cancer Proteome Atlas by developing a personalized cancer-specific integrated network estimation (PRECISE) model.
The paper can be accessed here https://www.nature.com/articles/s41598-018-32682-x
The Galaxy-P team (University of Minnesota, PI Tim Griffin) and the Cravat team (Johns Hopkins University, PI Rachel Karchin) have developed an automated workflow within the Galaxy for Proteomics (Galaxy-P) platform, which leverages the Cancer-Related Analysis of Variants Toolkit (CRAVAT) and makes it interoperable with proteogenomic results.
The NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) aims to develop a framework for functional mapping the human body with cellular resolution to enhance our understanding of cellular organization-function. HuBMAP will accelerate the development of the next generation of tools and techniques to generate 3D tissue maps using validated high-content, high-throughput imaging and omics assays, and establish an open data platform for integrating, visualizing data to build multi-dimensional maps.
ITCR funded Cancer Deep Phenotype Extraction (DeepPhe) tool new release is now available! The tool extracts deep phenotypic information from the clinical narrative at the document-, episode-, and patient-level. The final output is FHIR compliant patient-level phenotypic summary which can be consumed by research warehouses or the DeepPhe native visualization tool. PI Dr. Guergana Savova, Boston Children's Hospital and Harvard Medical School
The next application receipt date for ITCR funding opportunities is November 20, 2018. All funding opportunties can be found here.
Computational DREAM Challenge to generate computational methods for extracting information from the cancer proteome and for linking those data to genomic and transcriptomic information.
The next application receipt date for ITCR funding opportunities is November 20, 2017. All funding opportunties can be found here.