Computational Biology Commons^™

Data Curation And Integration For Cancer Cell Line Pharmacogenomics Analysis, Meric Kinali

Graduate Masters Theses

Cancer cell lines are essential resources for connecting genomic and molecular features with drug response and identifying biomarkers. Therefore, large-scale cancer cell line resources have been growing, but this introduces challenges such as data standardization, consistent annotation, matching identifiers, cross-database integration, and a reproducible computational framework. CellMiner Cross Database (CellMinerCDB) integrates pharmacogenomic datasets from multiple resources and provides a standardized analysis of cell lines across datasets. This thesis examines cancer cell line cross-databases and their importance in pharmacogenomics, with a particular focus on CellMinerCDB. As part of this work, I developed an R package for the gCSI (Genentech Cell Line …

Understanding Epigenomic Landscapes In Cancer Progression And Immunotherapy Response, Jonathan Schulz

Dissertations and Theses (Open Access)

Nonmutational epigenomic reprogramming has emerged as a key hallmark of cancer that plays crucial roles in tumor evolution during its progression and response to therapy. However, the extent and nature of epigenomic reprogramming remains poorly understood. This dissertation examines how epigenetic regulation shapes cancer progression and response to immunotherapy. Working at the intersection of cancer biology and computational genomics, it develops analytical frameworks for characterizing chromatin structure and DNA methylation across diverse tumor contexts and uses these frameworks to address two complementary biological questions: how promoter-associated chromatin organization varies across cancer types, and how epigenetic perturbation modulates tumor immunogenicity in …

Understanding How Genetic Mutations Induce Oligodendrocyte Progenitors To Become Cancer Cells, Dennis Huang

Dissertations, Theses, and Capstone Projects

Gliomas are the most devastating adult brain tumors characterized by poor survival rate and limited options for treatment. Previous studies have shown that they are very heterogeneous and can be further sub-classified based on their transcriptional signature and the presence of specific mutations. One such subtype, is the “proneural glioma”, which is characterized by the enrichment in oligodendrocyte progenitor cell (OPC) transcripts and mutations in genes encoding for the tumor suppressor P53 (Trp53) and for Platelet Derived Grow Factor (PDGF) signaling. Since OPCs are the most abundant proliferative population in the adult brain, in this …

Developing A Small Molecule To Inhibit Hsf1 Expression In Cancer And Evaluating Natural Genetic Variation In Small Molecule Toxicity., Michaela Kendal Foley

Theses and Dissertations

Each year cancer affects nearly 20 million people worldwide and genetic differences across populations can impact cancer onset and progression. Specifically, tumors with high levels of HSF1, the master regulator of the cytoprotective heat shock response (HSR), are correlated with poor patient outcomes in multiple cancers such as prostate, breast, and melanoma. Subsequently, the development of pharmacological inhibitors of HSF1 represents a promising strategy for anticancer therapeutics. Using a luciferase-based transcriptional reporter, two small molecule libraries were screened for inhibitors of HSF1 expression in human embryonic kidney cells, yielding ten compounds that decrease HSF1 expression. To identify if cancer lines …

Leveraging Attention Mechanism To Unlock Gene And Protein Attributes, Ala Jararweh

Computer Science ETDs

Advancing personalized medicine depends on effectively integrating and interpreting the vast, heterogeneous landscape of biological data, from genomic sequences and transcriptomics to the insights embedded in scientific literature. Current machine learning models often focus on single data modalities, limiting their capacity to capture the multifaceted nature of biological systems. We address this gap by developing three attention-based machine-learning models integrating diverse data modalities. Firstly, DeepVul is a multi-task model that leverages cancer transcriptome data to predict genes critical for cancer survival and their corresponding drugs. Subsequently, LitGene refines gene representations by integrating textual information from the scientific literature. Finally, Protein2Text …

The Role Of Secondary And Tertiary Structure In The Cap-Independent Translation Of Fgf-9 And Hif-1-Alpha, Amanda Michelle Whittaker

Dissertations, Theses, and Capstone Projects

Under normoxic conditions, eukaryotes initiate translation of RNA through eIF4E recognition of the 5’ cap. However, under cellular stress, eukaryotic translation must be initiated through a 4E-independent, or “cap-independent” mechanism, involving eukaryotic initiation factor 4G (eIF4G) binding directly to the 5’ untranslated regions (5’ UTR) of the RNA. eIF4G binding then recruits the ribosome to the transcript. While this mechanism is useful for translation of apoptotic transcripts and transcripts involved in cell survival, cap-independent translation is also utilized by oncogenic RNA for tumorigenesis. Previous work by our lab and others has categorized this recruitment and initiation mechanism as either internal-ribosome-entry-site …

Timigp: A Computational Framework To Determine The Tumor Immune Microenvironment Associated With Prognosis And Immunotherapy Response, Chenyang Li

Dissertations and Theses (Open Access)

Accumulating evidence has suggested that the tumor immune microenvironment (TIME) drastically impacts cancer patients’ clinical outcomes, including prognosis and immunotherapy response. However, understanding TIME remains challenging due to its complexity and heterogeneity. In this dissertation, we introduce TimiGP (Tumor Immune Microenvironment Illustration based on Gene Pairs), a computational framework designed to address this challenge. Leveraging single-cell RNA-seq (scRNA-seq) and bulk gene expression data alongside clinical information, TimiGP constructs a cell-cell interaction network that elucidates the relationship between immune cell function and relevant clinical outcomes, such as prognosis and treatment response. With immunological insights, these cell-cell interactions also facilitate the development …

A Pan-Cancer Single-Cell Analysis Of Intratumoral Copy Number Diversity And Evolution, Hanghui Ye

Dissertations and Theses (Open Access)

Aneuploidy is a hallmark of human cancers, with many copy number aberrations (CNAs) being associated with disease progression. Previous studies have revealed extensive inter-patient heterogeneity (IPH) in copy number profiles. However, the extent of intratumoral heterogeneity (ITH) and its evolutionary dynamics remain poorly understood.

To address these gaps, we developed Acoustic Cell Tagmentation (ACT), an advanced single-cell single-molecule DNA sequencing (scDNA-seq) technology, to resolve the copy number substructure of human tumors and investigate the evolution of aneuploidy. Applying ACT to eight triple-negative breast cancer (TNBC) patients to profile 9,765 aneuploid tumor cells, we discovered that following initial punctuated copy number …

Early Onset Alzheimer’S Disease Markers In Mouse Hippocampus Unveiled By Single-Cell Transcriptomic Analysis Following Cranial Radiotherapy, Tuba Aksoy

Dissertations and Theses (Open Access)

Cranial radiation therapy plays an integral role in the treatment of brain tumors but can lead to progressive cognitive deficits in survivors by mechanisms that are poorly understood. To develop preventive or mitigative strategies, it is crucial to better understand the underlying pathogenesis of radiation-induced cognitive impairments. The study investigated single-cell transcriptomics and DNA methylation changes as potential drivers of persistent cellular dysfunction after radiation exposure, specifically concentrating on the CA1-3 regions of the hippocampus and the prefrontal cortex due to their role in cognitive functions. Thirteen-week-old mice underwent whole-brain radiation at clinically relevant doses. Following whole-brain radiation, an assessment …

Optimizing Immunotherapies For Improved Cancer Treatment, Anne Talkington, Anthony Kearsley

Biology and Medicine Through Mathematics Conference

No abstract provided.

Epigenetic Modification As A Therapeutic Target In Brafv600e-Mutated Metastatic Colorectal Cancer, Hey Min Lee

Dissertations and Theses (Open Access)

Patients with BRAF^V600E-mutated metastatic colorectal cancer (mCRC) experience a worse prognosis and demonstrate only a 5% response rate to BRAF inhibitor treatment. In this study, adaptive resistance, and a potential combination of standard therapies in BRAF^V600E CRC were unveiled. Intriguingly, a robust association of BRAF^V600E mutation and DNA hypermethylation suggests this is a unique subgroup harboring aberrant epigenetic phenotype. Firstly, DNA methyltransferase (DNMT) inhibitor treatment induced profound DNA hypomethylation in vivo, but minimal change in gene expression due to adaptive elevation of the repressive histone methylation, H3K27me3, leading to compensatory suppression of key tumor suppressor genes, …

The In4mer Crispr/Cas12a Multiplex Knockout Platform And Its Applications, Nazanin Esmaeili Anvar

Dissertations and Theses (Open Access)

Discovering synthetic lethal interactions between genes holds the key to uncovering cancer vulnerabilities, enabling the development of more effective drugs for patients. However, identifying these vulnerabilities in the complex genome of human, which comprises thousands of genes, poses a significant challenge. One alternative approach to investigate these interactions involves exploring enriched sources of synthetic lethal interactions, such as paralog pairs. In recent years, a couple of studies have conducted dual-gene knockout experiments on paralog pairs using different approaches to identify synthetic lethal interactions. In this study, we conducted a meta-analysis of CRISPR genetic interaction screens. We identified a candidate set …

Single Cell Pharmacodynamic Modeling Of Cancer Cell Lines, Arnab Mutsuddy

All Dissertations

Cancer is one of the leading causes of disease related death worldwide. Since the discovery of the genomic origins of cancer, targeted therapy has been developed towards specific mutations implicated for oncogenic transformation. However, current standard-of-care for mapping cancer patients to efficacious drug combination is often inadequate. The pathophysiology of tumor progression relies on the dysregulation of biomolecular pathways of which the topology and the dynamics challenge prognosis. Moreover, the overall genomic instability involved in disease states and the resulting inter-patient as well as intra-tumoral heterogeneity challenge rationalization of therapy and clinical decision-making. It highlights the need for the use …

Identifying New Cancer Genes Based On The Integration Of Annotated Gene Sets Via Hypergraph Neural Networks, Chao Deng, Hong-Dong Li, Li-Shen Zhang, Yiwei Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation

Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited.

Results

Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of …

Sccad: Cluster Decomposition-Based Anomaly Detection For Rare Cell Identification In Single-Cell Expression Data, Yunpei Xu, Shaokai Wang, Qilong Feng, Jiazhi Xia, Yaohang Li, Hong-Dong Li, Jianxin Wang

Computer Science Faculty Publications

Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate …

Exploring 3d Genome Interaction And Epigenetic Regulation Via Swi/Snf Complex And Deep Learning Models, Ruoyun Wang

Dartmouth College Ph.D Dissertations

The three-dimensional organization of the genome is fundamental in regulating gene expression and maintaining cellular function. This organization's complexities, influenced by epigenetic marks and chromatin remodeling complexes, are crucial for understanding genomic regulation. Among these, the SWI/SNF complexes are key, facilitating chromatin accessibility and regulating gene activity across cell types. The first part of my dissertation focuses on SWI/SNF complexes, exploring their role in chromatin remodeling and their impact on 3D genome architecture. Utilizing next-generation sequencing (NGS) techniques, this section investigates the interplay between these complexes and chromatin structure. During my research on the SWI/SNF complex, I was intrigued by …

Unique Transcriptional Profiles Underlie Osteosarcomagenesis Driven By Different P53 Mutants, Dhruv Chachad

Dissertations and Theses (Open Access)

Missense mutations in the DNA binding domain of the Trp53 gene are characterized as structural (p53R172H) or contact (p53R245W) mutations based on their effect on the conformation of the protein. These mutations show gain-of-function activities such as increased metastatic incidence as compared to p53 loss, often mediated by their interaction with a repertoire of transcription factors. These interactions are largely context specific. In order to understand the mechanisms by which these mutations drive osteosarcoma progression, we created a mouse model, wherein either the p53 structural mutant p53R172H, or the contact mutant, p53R245W, are expressed specifically in …

Cell-Typing And Interaction Analysis Of The Immune Compartment Of The Tumor Microenvironment Using High-Resolution Omics Modalities, Courtney Taylor Schiebout

Dartmouth College Ph.D Dissertations

Single-cell RNA-sequencing (scRNA-seq) has provided a new frontier for the investigation of complex tissues. One ideal candidate for the utilization of this method is the tumor microenvironment (TME). The TME is often host to a complex set of cell populations and behaviors that can be highly influential for cancer inhibition or progression. This is especially true of the immune compartment of the TME: the presence of certain types of immune cells in the TME and their expression profiles can significantly affect cancer prognosis in some cases. By providing individual cell-level gene expression data, scRNA-seq can be highly informative for characterizing …

Characterization Of Cell Type-Specific Molecular Heterogeneity In Cancer Using Multi-Omic Approaches, Min Kyung Lee

Dartmouth College Ph.D Dissertations

Tumors are composed of heterogeneous cell types each with its own unique molecular profiles. Recent advances in single cell genomics technologies have begun to increase our understanding of the molecular heterogeneity that exists in tumors with particular focus on gene expression and chromatin accessibility profiles. However, due to limitations in methods for certain sample types and high cost for single cell genomics, bulk tumor molecular profiling has been and remains widely used. In addition, other facets of single cell epigenomic profiling, particularly methylation and hydroxymethylation, remains underexplored. Thus, investigations to understand the cell type specific epigenetic heterogeneity and the cooperation …

Cell Signaling And Stress Response In The Yeast Saccharomyces Cerevisiae: A Study Of Snf1, Scott E. Arbet Ii

Graduate Theses, Dissertations, and Problem Reports (ETD)

Saccharomyces cerevisiae are yeast that are unicellular eukaryotic organisms that are well studied as a model organism for understanding fundamental cellular processes. The ability of yeast to sense nutrient availability is crucial for their survival, growth, and reproduction. Yeast cells use various mechanisms to sense and respond to nutrient availability, including transporter-mediated uptake, receptor-mediated signaling, and sensing of metabolites. The subcellular localization of nutrient-sensing components is crucial for yeast function in nutrient sensing and signaling. Protein complexes, such as the AMP-activated protein kinase (AMPK) pathway, in nutrient sensing and response, as well as the downstream effects of these pathways …

An Investigation Of Epigenetic Mechanisms Driving The Biology Of Head And Neck Squamous Cell Carcinoma, Scot Carson Callahan

Dissertations and Theses (Open Access)

Head and neck squamous cell carcinoma (HNSCC) is the 6th most common cancer worldwide and is associated with significant morbidity and mortality. To date, the majority of work in the field has focused on genomic alterations such as mutations and copy number alterations. However, the clinical success of targeted therapies that exploit known genomic alterations, such as EGFR mutations, has remained mixed. Over the past decade, the importance of epigenetic regulators has come to the forefront, with the realization that many of these genes are mutated in cancer. Despite this realization, the role of epigenetics in regulating tumorigenesis, progression and …

Identifying The Cell Composition And Clonal Diversity Of Supratentorial Ependymoma Using Single Cell Rna-Sequencing, James He

University Scholar Projects

Ependymoma is a primary solid tumor of the central nervous system. Supratentorial ependymoma (ST-EPN), a subtype of ependymomas, is driven by an oncogenic fusion between the ZFTA and RELA genes in 70% of cases. We introduced this fusion into neural progenitor cells of mice embryos via in utero electroporation of a non-viral binary piggyBac transposon system containing ZFTA-RELA. From preliminary data in the LoTurco lab, inducing the expression of ZFTA-RELA into different neural progenitor cells produces tumors of varying lethality and cellular composition. To define the cellular composition and subclonal diversity of ST-EPN tumors, we used single cell RNA-sequencing to …

Single-Fluorophore Sensors For Mechanical Force In Living Cells, Sarah Kricheff

Honors Scholar Theses

Mechanotransduction is the process by which a mechanical stimulus is converted to a cellular signal. This process is heavily influential of cell morphology, differentiation, and behavior. However, altered levels of mechanical stimuli are also found in many pathological contexts. For example, cancerous cells have stiffer surrounding tissue than healthy cells, and research suggests that this alters cell behavior and promotes metastasis. Despite these findings, the cellular processes behind these signaling alterations remain widely unknown. Understanding these cascades is critical, as involved proteins can give us a deeper understanding of the role of mechanotransduction, and certain proteins can potentially be targeted …

Towards A Mathematical Model Of Motility Using Dictyostelium Discoideum: Proteins And Geometric Features That Regulate Bleb-Based Motility, Zully Santiago

Dissertations, Theses, and Capstone Projects

A variety of biological functions depend on actin organization. The organization of actin is tightly regulated by a plethora of extracellular and intracellular signaling, scaffolding, and actin-binding proteins. Dysfunctions in this regulation lead to immune diseases, increased susceptibility to pathogens, neurodegenerative diseases, developmental disorders, and cancer metastasis. A variety of actin-dependent processes, including cell motility, are regulated by several proteins of interest: Paxillin, a scaffolding protein; WASP, an actin nucleating protein; SCAR/WAVE, another WASP family actin nucleating protein; Talin, a cortex-to-membrane binding protein; Myosin II, an F-actin contracting motor protein; and Protein Kinase C, a protein kinase. D. discoideum cells …

Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan

COBRA Preprint Series

One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards …

Supervised Dimension Reduction For Large-Scale "Omics" Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards, Lauren Spirko-Burns, Karthik Devarajan

COBRA Preprint Series

The past two decades have witnessed significant advances in high-throughput ``omics" technologies such as genomics, proteomics, metabolomics, transcriptomics and radiomics. These technologies have enabled simultaneous measurement of the expression levels of tens of thousands of features from individual patient samples and have generated enormous amounts of data that require analysis and interpretation. One specific area of interest has been in studying the relationship between these features and patient outcomes, such as overall and recurrence-free survival, with the goal of developing a predictive ``omics" profile. Large-scale studies often suffer from the presence of a large fraction of censored observations and potential …

Cyclin C: The Story Of A Non-Cycling Cyclin, Jan Jezek, Daniel G J Smethurst, David C Stieg, Z A C Kiss, Sara E Hanley, Vidyaramanan Ganesan, Kai-Ti Chang, Katrina F Cooper, Randy Strich

Rowan-Virtua School of Osteopathic Medicine Departmental Research

The class I cyclin family is a well-studied group of structurally conserved proteins that interact with their associated cyclin-dependent kinases (Cdks) to regulate different stages of cell cycle progression depending on their oscillating expression levels. However, the role of class II cyclins, which primarily act as transcription factors and whose expression remains constant throughout the cell cycle, is less well understood. As a classic example of a transcriptional cyclin, cyclin C forms a regulatory sub-complex with its partner kinase Cdk8 and two accessory subunits Med12 and Med13 called the Cdk8-dependent kinase module (CKM). The CKM reversibly associates with the multi-subunit …

Computational Analysis Of Genomic Variants Affecting Predicted Microrna:Target Interactions In Prostate Cancer., Angélica Paola Hernández Pérez

KGI Theses and Dissertations

Prostate cancer (PCa) is the most common cancer of men in the United States and is third only to lung and colon as a cause of cancer death. Clinical behavior of the disease is variable and the combination of prostate-specific antigen (PSA) screening and Gleason score staging are currently the best available molecular and pathology tools to predict outcomes. Cancer biology research establishes microRNAs (miRNAs) as key molecular components in both normal and pathological states. Thus, elucidating miRNAs perturbed by genomic alterations will expand our understanding of the molecular taxonomy of PCa with the aim to complement current practices in …

Unseen Science: Modern Discoveries Too Far Away Or Tiny For Human Eyes, Lucy Huang

Capstones

As science has progressed, scientists have realized that evidence goes beyond the realms of physical sight. Whether it is too small or difficult to find, scientists have developed different ways to get around this problem. We see this in cancer genomics and in extrasolar planetary research. Scientists use what they know and what they measure to validate their work.

https://lucy-huang-9tge.squarespace.com/

Exploring Biological Heterogeneity And Its Consequences At Tissue And Cellular Scales Through Mathematical And Computational Modeling, Romica Kerketta

Biomedical Sciences ETDs

This dissertation explores the effects of heterogeneity across different biological scales in cancer as well as normal cells. At the tissue scale, we investigated the variability present in the tumor microenvironment and its effect on patient chemotherapeutic outcomes using a mathematical model of drug transport. We found that parameters such as tumor blood perfusion and radius of blood vessel had an impact on the tumor cytotoxicity. This indicated that the physical microenvironment of the tumor is an important regulator of the tumor response to chemotherapy. At the cellular scale, we investigated the heterogeneity present on the membrane landscape of ErbB2 …