Cancer causes more than 500,000 deaths a year in the United States, with more than 90% of the morbidity and mortality attributed to metastases. Metastasis is the spread of cancerous clones of cells across a body, whose dispersal routes are not medically detected or visible until later stages of cancer development. These migratory routes are critical to our understanding of the processes that influence tumor diversity in patients as well as aggressiveness, resistance, and escape of tumors from therapy. Comparative analysis of the extensive genetic heterogeneity present in tumors can be used to map the dynamic history of cancer cell migration over time and space. We propose to develop new methods for inferring cancer cell migrations accurately. Our new approaches will employ principles of Bayesian molecular phylogenetics and patterns of mutational signatures in cancer cell genomes for the first time to produce accurate maps of cell migration among tumor sites. We will also develop new methods for detecting mutational signatures. These will overcome many limitations of the current methods for datasets containing a small number of mutations, a situation commonly encountered in single- patient clone phylogenies. Our methodological developments will be complemented by the distribution of a library of functions containing our new and advanced approaches for high-throughput and in-depth analysis of metastatic tumor genomic data. Overall, the proposed software and research developments will lead to advances in cancer, bioinformatics, functional genomics, and data science. New software and its source code will be made available free of charge for all uses, including research, education, and training.

Public Health Relevance

Comparative analysis of genome sequence variation present in tumors and cancer cells provides a powerful means to reconstruct migration routes of metastases. We will develop advanced methods and software tools for evolutionary bioinformatics of somatic genomic variation to infer migration routes and models. These methods and resources will greatly facilitate studies into causes and consequences of metastases that are being pursued by basic biologists and clinicians.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Research Project (R01)
Project #
5R01LM013385-02
Application #
10159969
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Ye, Jane
Project Start
2020-05-06
Project End
2024-02-29
Budget Start
2021-03-01
Budget End
2022-02-28
Support Year
2
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Temple University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
057123192
City
Philadelphia
State
PA
Country
United States
Zip Code
19122