Bharadwaj, Kishan R

Integrative multi-platform approach to identify biomarkers of diabetes-associated breast cancer progression - Bangalore: Indian Institue of Science, 2023. - xxii,256p.: col.ill. e-Thesis 5.811Mb

PhD;2023; Mathematics

Breast cancer (BrC) is the leading cause of cancer-related death among women worldwide, including in India. Major risk factors for BrC include genetic predisposition, mutations in BRCA genes, post-menopausal hormonal imbalance, hormone replacement therapy, sedentary lifestyle and obesity, insulin resistance, and type 2 diabetes (T2D). India has more than 70 million T2D patients and is on the verge of becoming diabetic capital by 2045. The rate of newly diagnosed T2D and breast cancer incidence has increased linearly in India in the past 20 years. The association between T2D and the incidence of BrC is well established. Further, BrC patients with pre-existing T2D (BrC-D) have a 20-25% increased risk of all- cause mortality. The reasons for increased mortality in BrC-D are that they are given less- aggressive BrC treatment, often present with other co-morbid conditions, complications followed by surgery or radiation therapy, adverse reactions to chemotherapy, impaired wound healing, and susceptibility to infection. Hence, there is a need to identify biomarkers of T2D-associated BrC progression. Current blood-based biomarkers for BrC progression have low prognostic value or are expensive, elaborate, and time-consuming. Biomolecules that are involved in the mechanism of disease progression can serve as biomarkers as well as targets for novel therapy. Inflammation plays a significant role in the development and progression of BrC, and T2D patients often present with chronic inflammation. T2D is a metabolic disorder with altered metabolism, and in BrC, the cancer cells undergo metabolic rewiring to meet the high demand for energy and biosynthetic precursors. In this study, factors involved in inflammation and metabolism were screened in the blood plasma to identify potential candidates for biomarkers of diabetes-associated breast cancer progression


machine learning
Biomarker
algorithms

006.31 / BHA