{"id":102555,"date":"2023-09-06T01:56:00","date_gmt":"2023-09-06T06:56:00","guid":{"rendered":"https:\/\/www.unmc.edu\/newsroom\/?p=102555"},"modified":"2025-09-30T15:15:34","modified_gmt":"2025-09-30T20:15:34","slug":"med-center-researchers-publish-breast-cancer-article-in-human-genomics","status":"publish","type":"post","link":"https:\/\/www.unmc.edu\/newsroom\/2023\/09\/06\/med-center-researchers-publish-breast-cancer-article-in-human-genomics\/","title":{"rendered":"Med center researchers publish breast cancer article in Human Genomics"},"content":{"rendered":"
\n

An article based on the Breast Cancer Precision Medicine Project on a midwestern patient cohort has been published in the journal Human Genomics.<\/p>\n\n\n\n

The article, titled \u201cThe Mutational Landscape of a US Midwestern Breast Cancer Cohort Reveals Subtype-Specific Cancer Drivers and Prognostic Markers<\/a>,\u201d was authored by a team of researchers from UNMC. The project was primarily led by Kenneth Cowan, MD, PhD, director of the Fred & Pamela Buffett Cancer Center, and Babu Guda, PhD, professor and vice chair of the UNMC Department of Genetics, Cell Biology and Anatomy.<\/p>\n\n\n\n

Funded by the Helmsley Charitable Trust Foundation, the study was based on data from a cohort of 554 breast cancer patients from Nebraska, North Dakota and South Dakota, with patient records from the iCaRe2 Breast Cancer Collaborative Registry used for this study.<\/p>\n\n\n\n

The Fred & Pamela Buffett Cancer Center and its affiliated hospital network maintain the Breast Cancer Collaborative Registry, which catalogs data on breast cancer patients that includes information such as tumor stage and grade, hormone receptor status and histological subtype, in addition to long-term patient follow-up, therapeutic regimens and treatment response.<\/p>\n\n\n\n

For this study, tumor grade, subtype and stage, histological subtype, lymph node involvement and ethnic groups were selected for analysis. Whole exome sequencing was carried out for the matched tumor-normal patient samples, and the data were analyzed using seven different covariates.<\/p>\n\n\n\n

The Bioinformatics and Systems Biology Core, led by Dr. Guda, carried out the data analysis and investigated the mutational profiles of different subtypes of breast cancer.<\/p>\n\n\n\n

The study revealed the differences in the tumor mutational burden, mutually exclusive mutations, subtype specific cancer drivers and prognostic markers across different cohorts.<\/p>\n\n\n\n

\u201cThis work provides a strong rationale for investigations into the molecular mechanisms of genes and pathways associated with the major subtypes of breast cancer, leading to, among other things, applications in personalized therapy for breast cancer,\u201d Dr. Guda said. \u201cDeveloping new biomarkers can take place as a result of a better understanding of mutations in the subtypes of breast cancer.\u201d<\/p>\n<\/div><\/div>","protected":false},"excerpt":{"rendered":"

The study delved into data on cancer mutations from a cohort of 554 regional breast cancer 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