Date of Award

Fall 2022

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Bioinformatics & Computational Biology

Abstract

Breast cancer is the leading cause of cancer death for women in the US. Many cancertypes have significant associations with their resident microbial communities - emerging evidence suggests that breast cancers also interact with the local tissue-associated microbiota. Studies have examined the relationship between breast cancer and its microbiome, however, the studies varied in their approaches used to evaluate these relationships. Microbiome research advances rapidly and analysis pipelines and databases are updated frequently. This dynamic environment makes inter-study comparisons and superficial evaluations challenging as no two studies are using the same standards for evaluation. Researchers have observed the microbiota of tumor tissue, surrounding normal sites, and healthy breast tissue from non-cancer individuals (Hieken et al., 2016; Urbaniak et al., 2016; Xuan et al., 2014), but they have not been able to translate their findings into information that can be used for breast cancer treatment or detection nor address what affect studying different variable regions has in their analysis. Within the majority of these studies, comparisons of the tumor tissue with adjacent normal tissue has revealed differences. This project will integrate all available studies related to breast cancer and the mammary microbiome to 1 reassess the original findings in light of advances in this rapidly progressing field and 2 incorporate all the data available as a large meta- analysis to identify general trends and specific differences across patient cohorts and studies.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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