Pan-Cancer Analysis of RNA Dysregulation, Somatic Mutations, and Matrix Stiffness using Bioinformatics Approaches

Cancer is a complex disease driven by genetic mutations, epigenetic modifications, and alterations in the tumor microenvironment. Understanding these intricate molecular mechanisms is crucial for advancing cancer diagnosis, prognosis, and treatment. RNA sequencing (RNA-seq) has emerged as a powerful tool to study cancer by providing comprehensive insights into gene expression, alternative splicing, and mutations at the transcriptome level. This dissertation leverages RNA-seq data to explore different dimensions of cancer biology through multi-omics integration and computational approaches. The research is divided into three main projects. First, I developed OncoDB, an interactive database to analyze gene expression, methylation patterns, and viral interactions in cancer, revealing key pathways associated with oncogenic viruses. Second, I established a pipeline to identify somatic mutations using RNA-seq, highlighting mutations missed by DNA sequencing and their clinical implications. Third, I designed a computational model to predict tumor matrix stiffness using RNA-seq data, uncovering how matrix stiffness influences tumor complexity, immune infiltration, and extracellular matrix alterations. These findings provide a deeper understanding of the molecular and biophysical characteristics of tumors, identify novel somatic mutations, and offer insights into potential therapeutic strategies. This work demonstrates the importance of combining multi-omics data with computational approaches to unravel cancer’s complexity and advance precision oncology.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Mechanical Engineering & Materials Science

Year dc:date.available

2024

Author dc:creator

• Tang, Gongyu

Contributors dc:contributor

• Jessica Wagenseil
• Xiaowei Wang; Jessica Wagenseil; Jin Zhang; Matthew Bersi; Ramesh Agarwal

• Bioinformatics;Cancer;Genomics;Machine learning;Mutation;Tumor matrix stiffness
• Engineering
• Mechanical Engineering

Statement dc:rights

• I have not registered my thesis with the U.S. Copyright Office, but intend to later.

Language dc:language

English (en)

Identifier

https://openscholarship.wustl.edu/eng_etds/1142

OAI identifier oai:identifier

oai:openscholarship.wustl.edu:eng_etds-2215