Medical Genetics Commons^™

The Molecular Landscape Of Early-Stage Breast Cancer With Lymph Node Metastasis, Farhad Ghasemi

Electronic Thesis and Dissertation Repository

Axillary lymph nodes (ALNs) are the primary site of metastasis in breast cancer, and their involvement has implications in disease staging, prognostication, and treatment decisions. A non-invasive modality of assessing the risk of ALN metastasis can improve care in patients with early-stage breast cancer by omitting the morbidity and costs associated with axillary surgery.

This thesis explores the molecular landscape of early-stage breast cancers with ALN metastasis and shows the potential of tumour molecular signatures in predicting ALN involvement. After a systematic review of the literature, we use data from The Cancer Genome Atlas (TCGA) to develop molecular signatures correlated …

Genetic Relationships And Therapeutic Options For Relapsed Acute Lymphoblastic Leukemia, Hailie Shertzer

Senior Honors Theses

Acute lymphoblastic leukemia (ALL) is the most common form of cancer among children and can be lethal to the adult population. Though 80% of patients with ALL reach complete remission after treatment, about 20% of those diagnosed fail to remain cancer-free. Genetic rearrangements are the hallmark of relapsed ALL, but the mechanism by which these rearrangements occur is still unclear. Recent research suggests these mutations may be detectable during initial diagnosis. If researchers are able to accurately assess the probability of relapse during diagnosis by analyzing the genome of the leukemic cells, the likelihood of administering effective therapy would increase. …

Differential Iron Regulatory Genetics In 2d & 3d Culture Of Breast Cancer Cells, Tyler Hanna, Suzy Torti Ph. D, Frank Torti M.D., Mph, Nicole Farra Ph. D.

Honors Scholar Theses

The iron regulatory axis has consistently been shown to be perturbed in cancer cell lines relative to non-cancerous cell lines. As cancer cells rapidly divide and grow, they require iron to fuel many intracellular processes, including DNA replication and protein synthesis. Three-dimensional cell culture is an increasingly popular method of culture that purportedly more accurately mimics the in vivo microenvironment of cancers over traditional two-dimensional culture. This project was prompted by previous lab results to investigate differential iron regulatory gene expression in 2D and 3D spheroid culture models. We replicated the findings that the gene hepcidin is induced in 3D …

Managing Variant Discrepancy In Hereditary Cancer: Clinical Practice, Barriers, And Desired Resources, Ellen Zirkelbach

Dissertations & Theses (Open Access)

Variants are changes in the DNA whose phenotypic effects may or may not be definitively understood. Because variant interpretation is a complex process, sources sometimes disagree on the classification of a variant, which is called a variant discrepancy. This study aimed to determine the practice of genetic counselors regarding variant discrepancies and to identify the barriers to counseling a variant discrepancy in hereditary cancer genetic testing. This investigation was unique because it was the first to address variant discrepancies from a clinical point of view. An electronic survey was sent to genetic counselors in the NSGC Cancer Special Interest Group. …

Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …