ORCID ID

0000-0002-0417-0256

Graduation Date

Spring 5-8-2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Programs

Biochemistry & Molecular Biology

First Advisor

Dr. Surinder Batra

Abstract

Gastro-intestinal (GI) malignancies, including gastric, colorectal, and pancreatic cancers, have maintained their high overall mortality due to a lack of prognostic and diagnostic biomarkers and potential therapeutic modalities. While efforts have been made to improve both early detection and therapeutic interventions in these cancers, failure of conventional approaches have proven to be a big challenge, and alternate approaches are needed. Computational biology approaches owing to lesser time and more per target success rate offer a unique solution here. The current study explored the use of computational biology techniques to study the various aspects relating to GI malignancies. First, we sought to understand the role of mucins in colorectal cancer, which helped establish the role of MUC16 and its associated signaling in a subset of patients in colorectal cancer (CRC) as a potential therapeutic target. Interestingly, the role of MUC16 in CRC had remained unexplored up until this point. Further, we carried out a comprehensive study of all mucins in gastric cancer (GC). This study helped us identify and establish a 5-mucin prognostic panel for GC, proving to be highly beneficial in this high-mortality malignancy. Further, our study, for the first time, explored the presence of intrinsically disordered regions (IDRs) in mucins. Interestingly, IDRs have known to have significant functional relevance and hence the high percentage IDRs found within various mucins have the potential to be extremely relevant therapeutic targets. Furthermore, our in-silico identification and pre-clinical assessment of the novel therapeutic ISOX showed extremely high efficacy of ISOX in pancreatic cancer, which can help improve the overall survival of this highly lethal cancer. Overall, this dissertation successfully applies computational tools in highly lethal GI cancers establishing various novel biomarker panels and therapeutic interventions.

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