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- Creators: Computer Science and Engineering Program
Big Data Network Analysis of Genetic Variation and Gene Expression in Individuals with Breast Cancer
Adaptive therapy utilizes competitive interactions between resistant and sensitive cells by keeping some sensitive cells to control tumor burden with the aim of increasing overall survival and time to progression. The use of adaptive therapy to treat breast cancer, ovarian cancer, and pancreatic cancer in preclinical models has shown significant results in controlling tumor growth. The purpose of this thesis is to draft a protocol to study adaptive therapy in a preclinical model of breast cancer on MCF7, estrogen receptor-positive, cells that have evolved resistance to fulvestrant and palbociclib (MCF7 R). In this study, we used two protocols: drug dose adjustment and intermittent therapy. The MCF7 R cell lines were injected into the mammary fat pads of 11-month-old NOD/SCID gamma (NSG) mice (18 mice) which were then treated with gemcitabine.<br/>The results of this experiment did not provide complete information because of the short-term treatments. In addition, we saw an increase in the tumor size of a few of the treated mice, which could be due to the metabolism of the drug at that age, or because of the difference in injection times. Therefore, these adaptive therapy protocols on hormone-refractory breast cancer cell lines will be repeated on young, 6-week old mice by injecting the cell lines at the same time for all mice, which helps the results to be more consistent and accurate.
Molecular pathology makes use of estimates of tumor content (tumor percentage) for pre-analytic and analytic purposes, such as molecular oncology testing, massive parallel sequencing, or next-generation sequencing (NGS), assessment of sample acceptability, accurate quantitation of variants, assessment of copy number changes (among other applications), determination of specimen viability for testing (since many assays require a minimum tumor content to report variants at the limit of detection) may all be improved with more accurate and reproducible estimates of tumor content. Currently, tumor percentages of samples submitted for molecular testing are estimated by visual examination of Hematoxylin and Eosin (H&E) stained tissue slides under the microscope by pathologists. These estimations can be automated, expedited, and rendered more accurate by applying machine learning methods on digital whole slide images (WSI).
panCanSYGNAL is a web-application designed to allow cancer researchers to search the relationships between somatic mutations, regulators, and biclusters corresponding to many cancers using a Google-like searchable database.