This $2,372,456 Project Grant awarded by the National Cancer Institute (CFDA 93.393 - Cancer Cause and Prevention Research) will support a collaborative research program led by Memorial Sloan Kettering Cancer Center focused on leveraging observational (real-world) data to advance precision oncology. The key products and services to be delivered include: Overcoming methodological barriers in the analysis of observational clinico-genomic data (Project 1) Addressing the role of genetic ancestry...
The National Cancer Institute (NCI) awarded a Project Grant (CFDA 93.396 - Cancer Biology Research) totaling $585,931 to the University of Pittsburgh to conduct research on evaluating and selecting representative cancer models for precision medicine. The key objectives are to: (1) identify and clinically annotate prevalent subclones and tumor microenvironment cell types in breast cancer; (2) perform subclone-based congruence and selection for cancer models; and (3) decipher temporal changes in...
This federal Project Grant award from the National Cancer Institute (CFDA 93.393 - Cancer Cause and Prevention Research) provides $653,500.00 to Emory University to develop improved methods for measuring the completeness of cancer registries in the United States. The key products and services to be delivered under this 5-year grant include: Developing advanced statistical methods to estimate cancer registry completeness that account for factors such as cancer type, demographics, geography, and...
The U.S. National Cancer Institute (NCI) awarded a $450,000 Project Grant under the CFDA 93.396 Cancer Biology Research program to The Research Foundation for the State University of New York, doing business as Stony Brook University. The project, titled "Topological Methods for Breast Tissue Quantification," aims to develop advanced algorithms and analytical techniques using topological data analysis (TDA) to extract and interpret fine-grained structural information from breast...
The federal Project Grant award R33CA291166 was provided by the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394). The $419,133 grant supports the development of the "AscitesPredict" technology, which is a novel "ex vivo tumor biosensor" system that uses single-cell analysis and machine learning to evaluate cell identities and therapeutic sensitivities in cancer patient ascites samples. The goals of the 3-year project...
This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to Emory University will develop novel analytic methods and computational approaches to improve disease ruling - the process of ruling out or ruling in aggressive cancer, particularly for prostate cancer. The $692,248 award, with a project period from September 1, 2024 to August 31, 2029, will pursue five specific aims to create an analytic framework and robust...
This federal Project Grant award from the National Cancer Institute (NCI), under the Cancer Detection and Diagnosis Research program (CFDA 93.394), is providing $505,613 to the Fred Hutchinson Cancer Center in Seattle, WA to develop statistical and computational approaches that leverage genomic data to enable precision cancer prevention strategies. Specifically, the project aims to: (1) create deep learning-based methods to identify tumor subtypes linked to adverse outcomes and assess how...
This federal Cooperative Agreement award for $811,500.00 from the National Cancer Institute (CFDA 93.396 Cancer Biology Research) supports research to bridge the gap between bioinformatics and mathematical modeling for patient-specific tumor modeling. The project aims to merge bioinformatics software for analyzing single-cell and spatial multi-omics data with an agent-based modeling framework to simulate cell interactions in virtual tumor environments. Key objectives include refining a cell...
This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to Yale University totals $167,500 and will be executed from September 2023 through August 2025. The primary objectives are to: Develop deep neural network-based emulation analysis methods and software to objectively quantify the relative effectiveness of drugs, devices, and treatment procedures on cancer prognosis, especially when randomized clinical trials are not feasible. The...
This $627,833 federal Project Grant award from the National Cancer Institute's Cancer Biology Research program (CFDA 93.396) aims to develop an informatics platform that integrates molecular and pathological data from various lung cancer preclinical models and patient tumors. The goal is to assess the fidelity of these preclinical models through comparative analyses. The University of Texas Southwestern Medical Center, the prime awardee, will work with Duke University as a sub-awardee to...