Project titleAlternative Splicing and the Phenotypes of Different Breast Cancer Subtypes

As of 2021, breast cancer is the most commonly diagnosed type of cancer in the world, holding the second highest death rate of all cancers amongst women. Resulting from genetic mutations that instigate abnormal and uncontrolled growth of cells within the breast, different types of breast cancer arise depending on the cells undergoing mutation. One common modern treatment for breast cancer is hormonal therapy, reducing the risk of cancer cell growth by inhibiting these cells’ receptors of hormones such as estrogen and progesterone. Although this treatment has proven to be effective in the case of hormonal responsive breast cancer cells, triple- negative breast cancer cells have proven to be more aggressive as they completely lack expression of the estrogen receptor, progesterone receptor, and HER2, thereby rendering hormonal therapy useless as the cells are unable to respond or be affected by these hormones.

Past research work has identified a link between the development of breast cancer cells and the molecular mechanism of alternative splicing, where modifications of pre-mRNA constructs facilitate the production of diverse mRNA from a single gene by rearranging coding sequences during splicing. In particular, specific alternative splicing events have been linked with the development of breast cancer cells. In our research work, we hypothesize that this link grows deeper, with specific alternative splicing events revealing information regarding which specific breast cancer subtype will arise within the patient. We will be focusing on identifying alternative splicing events that help discern between the development of triple-negative and hormonal responsive breast cancer cells, thereby also discovering a link between alternative splicing and the phenotypes of these breast cancer subtypes. Our initial study will begin with the following genes: CTAGE5, MYO18A, LMO7, CASP3, PTPRE, MME, and TPM4.

Primary contact nameDorde Popovic
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Students/participant(s) programs
  • Biological Sciences
  • Computer Science
Faculty advisor(s)
Advisor name Email Affiliation
Ihab Younis CMU-Q
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  • Biological Sciences