Dna Methylation-Based Epigenetic Biomarkers In Cell-Type Deconvolution And Tumor Tissue Of Origin Identification, Ze Zhang

Dartmouth College Ph.D Dissertations

DNA methylation is an epigenetic modification that regulates gene expression and is essential to establishing and preserving cellular identity. Genome-wide DNA methylation arrays provide a standardized and cost-effective approach to measuring DNA methylation. When combined with a cell-type reference library, DNA methylation measures allow the assessment of underlying cell-type proportions in heterogeneous mixtures. This approach, known as DNA methylation deconvolution or methylation cytometry, offers a standardized and cost-effective method for evaluating cell-type proportions. While this approach has succeeded in discerning cell types in various human tissues like blood, brain, tumors, skin, breast, and buccal swabs, the existing methods have major …

The Role Of Non-Coding Rnas In Myelodysplastic Neoplasms, Vasileios Georgoulis, Epameinondas Koumpis, Eleftheria Hatzimichael

Computational Medicine Center Faculty Papers

Myelodysplastic syndromes or neoplasms (MDS) are a heterogeneous group of myeloid clonal disorders characterized by peripheral blood cytopenias, blood and marrow cell dysplasia, and increased risk of evolution to acute myeloid leukemia (AML). Non-coding RNAs, especially microRNAs and long non-coding RNAs, serve as regulators of normal and malignant hematopoiesis and have been implicated in carcinogenesis. This review presents a comprehensive summary of the biology and role of non-coding RNAs, including the less studied circRNA, siRNA, piRNA, and snoRNA as potential prognostic and/or predictive biomarkers or therapeutic targets in MDS.

Genome-Scale Methylation Analysis In Blood And Tumor Identifies Immune Profile, Age Acceleration, And Dna Methylation Alterations Associated With Bladder Cancer Outcomes, Ji-Qing Chen

Dartmouth College Ph.D Dissertations

Bladder cancer patients receive frequent screening due to the high tumor recurrence rate (more than 60%). Nowadays, the conventional monitoring method relies on cystoscopy which is highly invasive and increases patient morbidity and burden to the health care system with frequent follow-up. As a result, it is urgent to explore novel markers related to the outcomes of bladder cancer. Immune profiles have been associated with cancer outcomes and may have the potential to be biomarkers for outcomes management. However, little work has been conducted to investigate the associations of immune cell profiles with bladder cancer outcomes. Here, I utilized the …

Mining Sars-Cov-2 Phylogenetic Trees To Estimate Circulating Infections And Patterns Of Migration, Erin V. Brintnell

Electronic Thesis and Dissertation Repository

The SARS-CoV-2 pandemic led to the formation of very large databases of genomic viral data. These databases contain information on transmission dynamics, emergence and evolution of SARS-CoV-2. However, extracting this information from sequences is difficult, as most methods of analyzing viral genomes were developed for smaller data sets. Therefore, my objective was to develop new fast estimators of the number of infections (I) and the rate of migration based on simple features of SARS-CoV-2 phylogenies.

I simulated pathogen evolution using a susceptible-exposed-infectious-recovered (SEIR) model of pathogen spread, reconstructing evolution using CoVizu. For simulations of I, I varied the total number …

Cellbrf: A Feature Selection Method For Single-Cell Clustering Using Cell Balance And Random Forest, Yunpei Xu, Hong-Dong Li, Cui-Xiang Lin, Ruiqing Zheng, Yaohang Li, Jinhui Xu, Jianxin Wang

Computer Science Faculty Publications

Motivation

Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to dissect the complexity of biological tissues through cell sub-population identification in combination with clustering approaches. Feature selection is a critical step for improving the accuracy and interpretability of single-cell clustering. Existing feature selection methods underutilize the discriminatory potential of genes across distinct cell types. We hypothesize that incorporating such information could further boost the performance of single cell clustering. Results

We develop CellBRF, a feature selection method that considers genes’ relevance to cell types for single-cell clustering. The key idea is to identify genes that are most important for discriminating …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

Intergenic Transcription In In Vivo Developed Bovine Oocytes And Pre-Implantation Embryos, Saurav Ranjitkar, Mohammad Shiri, Jiangwen Sun, Xiuchun Tian

Computer Science Faculty Publications

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and …

Prediction Of Kinase-Substrate Associations Using The Functional Landscape Of Kinases And Phosphorylation Sites, Serhan Yilmaz, Filipa Blasco Tavares Pereira Lopes, Mark R. Chance, Mehmet Koyutürk

Faculty Scholarship

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships …

Data-Driven Biomarker Panel Discovery In Ovarian Cancer Using Heterogenous Data Fusion On Exosomal And Non-Exosomal Microrna Expression Data, Paritra Mandal

All Dissertations

Ovarian cancer (OC) is an aggressive gynecological cancer and is currently the 5th leading cause of deaths due to cancer in women. High mortality rates are attributable to the vague pathogenesis and asymptomatic nature of the early stages. The development of a liquid biopsy for routine OC screening could help identify the disease at an earlier stage, making treatments more likely to be effective thereby increasing survival rates. Exosomes, small (~100nm) extracellular vesicles present in body fluids, have been shown to contain cancer-progression, onset, and related factors, making them good candidates for use in liquid biopsies. However, to date, only …

Radiation Exposure Determination In A Secure, Cloud-Based Online Environment, Ben C. Shirley, Eliseos J. Mucaki, Peter Rogan

Biochemistry Publications

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses. This study aimed to broaden accessibility and speed of this system, while protecting data and software integrity. ADCI Online is a secure web-streaming platform accessible worldwide from local servers. Cloud-based systems containing data and software are separated until they are linked for radiation exposure estimation. Dose estimates are identical to ADCI …

Patient-Specific Genome-Scale Metabolic Models For Individualized Predictions Of Liver Disease, Alexandra Manchel, Jan B. Hoek, Ramon Bataller, Radhakrishnan Mahadevan, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

The prevalence of liver disease is steadily increasing, coupled with the limited availability of therapeutic treatments. Recent literature points to metabolic reprogramming as a key feature of liver failure. Hence, we sought to uncover the metabolic pathways and mechanisms associated with liver disease and acute liver failure. We generated patient-specific genome scale metabolic models by integrating RNA-seq data from patient liver samples with a generalized human metabolic model. Flux balance analysis simulations showed a distinct separation of non-alcohol associated and alcohol-associated disease states. Our analysis suggests that the alcohol associated liver has an increased flux through nucleotide and glycerophospholipid metabolic …

Development Of Graphical Models And Statistical Physics Motivated Approaches To Genomic Investigations, Yashwanth Lagisetty

Dissertations & Theses (Open Access)

Identifying genes involved in disease pathology has been a goal of genomic research since the early days of the field. However, as technology improves and the body of research grows, we are faced with more questions than answers. Among these is the pressing matter of our incomplete understanding of the genetic underpinnings of complex diseases. Many hypotheses offer explanations as to why direct and independent analyses of variants, as done in genome-wide association studies (GWAS), may not fully elucidate disease genetics. These range from pointing out flaws in statistical testing to invoking the complex dynamics of epigenetic processes. In the …

Computational Approaches To Understand Chemoresistance & Tumor Evolution Using Longitudinal Clinical Data And Lineage Tracing, Sahil Seth

Dissertations & Theses (Open Access)

Tumors are highly heterogeneous and dynamic, continually adapting and evolving in response to their microenvironment as well as external perturbations. Multi-region (spatial) and single cell sequencing has enabled us to anatomize the heterogeneity further and provide evidence of its association with chemo and drug resistance. To investigate this further we took two different approaches to understand the chemo-resistance, and functional heterogeneity in Triple negative breast cancer (TNBC) and Pancreatic ductal carcinoma in situ (PDAC) from an evolutionary perspective.

The first approach was to leverage tumor profiling from an ongoing randomized clinical trial in triple-negative breast cancer (ARTEMIS) to assess mechanisms …

Using Machine Learning To Recognize Chronic Rhinosinusitis, Irene Liu '23

Student Publications & Research

Chronic Rhinosinusitis (CRS) is a nasal disease characterized by the inflammation of the mucosa and paranasal sinuses with a duration of at least 12 consecutive weeks. So, to diagnose CRS, one needs to keep a record of their symptoms for ~12 weeks before they are recommended to get a tomography which will allow physicians to classify them as a patient with CRS or without. This is a timely and costly process; thus, machine learning should be used to speed the process up. Since patients with CRS have more obstructed noses, the sound produced should be different than an individual without …

Identification Of Dna Methylation Episignatures For Classification And Phenotype/Genotype Correlation In Mendelian Neurodevelopmental Disorders, John Reilly

Electronic Thesis and Dissertation Repository

ABSTRACT: Diagnosis for neurodevelopmental disorders poses numerous challenges, related to the lack of specific findings and limited understanding of clinical impact of the majority of genetic variation. Epigenomics mechanisms involve chemical modifications in DNA that involve a range of cellular mechanisms. DNA methylation is an epigenetic mechanism involving addition and removal of methyl groups to cytosine residues. These methylation signals form episignatures; patterns of methylation that can be used as biomarkers capable of differentiating neurodevelopmental disorders. EpiSigns have enabled molecular diagnosis of a number of genetic conditions, classification of variants of unknown significance, and provided insights into the pathophysiology of …

Identifying Molecular Markers For Early Detection Of Toxic Cyanobacteria And Dinoflagellate, Shafqat F. Ehsan

Honors Program Theses and Research Projects

Harmful algal Blooms (HABs) develop when algal colonies grow out of control, causing toxicity or injury to humans, fish, shellfish, marine mammals, and birds. Most HABs of public health concern in saltwater generally are caused by eukaryotic dinoflagellates and diatoms. Prokaryotic cyanobacteria are usually responsible for freshwater blooms although they can contribute to saltwater and brackish blooms too. A common monitoring target of both groups is the saxitoxin-encoding genes. Saxitoxin(STX) is responsible for Paralytic shellfish poisoning, a foodborne illness developed from consumption of STX contaminated shellfish. Each cyanobacterial SXT gene cluster contains a set of core genes, common to all …

Meta-Analysis Of Two Rnaseq Datasets To Determine Diagnostic Biomarkers And Drug Target Candidates For Periodontitis, Carlos Moreno

Annual Research Symposium

No abstract provided.

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

The Low Abundance Of Cpg In The Sars-Cov-2 Genome Is Not An Evolutionarily Signature Of Zap, Ali Afrasiabi, Hamid Alinejad-Rokny, Azad Khosh, Mostafa Rahnama, Nigel Lovell, Zhenming Xu, Diako Ebrahimi

Plant Pathology Faculty Publications

The zinc finger antiviral protein (ZAP) is known to restrict viral replication by binding to the CpG rich regions of viral RNA, and subsequently inducing viral RNA degradation. This enzyme has recently been shown to be capable of restricting SARS-CoV-2. These data have led to the hypothesis that the low abundance of CpG in the SARS-CoV-2 genome is due to an evolutionary pressure exerted by the host ZAP. To investigate this hypothesis, we performed a detailed analysis of many coronavirus sequences and ZAP RNA binding preference data. Our analyses showed neither evidence for an evolutionary pressure acting specifically on CpG …

Completing Single-Cell Dna Methylome Profiles Via Transfer Learning Together With Kl-Divergence, Sanjeeva Dodlapati, Zongliang Jiang, Jiangwen Sun

Computer Science Faculty Publications

The high level of sparsity in methylome profiles obtained using whole-genome bisulfite sequencing in the case of low biological material amount limits its value in the study of systems in which large samples are difficult to assemble, such as mammalian preimplantation embryonic development. The recently developed computational methods for addressing the sparsity by imputing missing have their limits when the required minimum data coverage or profiles of the same tissue in other modalities are not available. In this study, we explored the use of transfer learning together with Kullback-Leibler (KL) divergence to train predictive models for completing methylome profiles with …

Improved Radiation Expression Profiling In Blood By Sequential Application Of Sensitive And Specific Gene Signatures, Eliseos J. Mucaki, Ben C. Shirley, Peter K. Rogan

Biochemistry Publications

Purpose. Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

Methods. This study investigated recall by previous and novel radiation signatures independently derived …

Characterization Of The Growth Factor Receptor Network Oncogenes In Lung Cancer, Ashley Duche

Pharmaceutical Sciences (MS) Theses

Lung cancer remains the leading cause of cancer related deaths worldwide, reportedly contributing to 1.8 million of the 10.0 million mortalities documented in the year 2020. Although advancements have been made in therapeutics and diagnostic methods, formulation of effective treatments and development of drug resistance continues to be a challenge. These challenges arise from our lack of understanding of intricate signaling pathways, such as the Growth Factor Receptor Network (GFRN), which contributes to complex lung tumor heterogeneity allowing for drug resistance development. In this study, gene expression signatures of six GFRN oncogenes overexpressed in human mammary epithelial cells (HMECs) were …

Unveiling Global Roles Of G-Quadruplexes And G4-22 In Human Genetics, Ruth Barros De Paula

Dissertations & Theses (Open Access)

G-quadruplexes are non-B DNA structures formed by four or more runs of repeated guanines that confer unique features to living organism’s genomes. These sequences are enriched in regulatory regions, such as promoters and 5’ UTRs, and have distinct regulatory roles in both health and disease states. Even though previous studies showed the impact of G4 in gene expression, none of them summarized the location-specific effect of G4. Also, there is no broad understanding about the most common G4 repeat in the human genome, named here as G4-22, and how it links to the evolution of mammals and their biology. In …

Rnase Κ Promotes Robust Pirna Production By Generating 2',3'-Cyclic Phosphate-Containing Precursors, Megumi Shigematsu, Takuya Kawamura, Keisuke Morichika, Natsuko Izumi, Takashi Kiuchi, Shozo Honda, Venetia Pliatsika, Ryuma Matsubara, Isidore Rigoutsos, Susumu Katsuma, Yukihide Tomari, Yohei Kirino

Computational Medicine Center Faculty Papers

In animal germlines, PIWI proteins and the associated PIWI-interacting RNAs (piRNAs) protect genome integrity by silencing transposons. Here we report the extensive sequence and quantitative correlations between 2′,3′-cyclic phosphate-containing RNAs (cP-RNAs), identified using cP-RNA-seq, and piRNAs in the Bombyx germ cell line and mouse testes. The cP-RNAs containing 5′-phosphate (P-cP-RNAs) identified by P-cP-RNA-seq harbor highly consistent 5′-end positions as the piRNAs and are loaded onto PIWI protein, suggesting their direct utilization as piRNA precursors. We identified Bombyx RNase Kappa (BmRNase κ) as a mitochondria-associated endoribonuclease which produces cP-RNAs during piRNA biogenesis. BmRNase κ-depletion elevated transposon levels and disrupted a piRNA-mediated …

Comparative Genomics Methods And Applications, Emily N. Alden

Biomedical Sciences ETDs

Virtually all fields of biology have benefited from the advancements in comparative genomics technologies, specifically in the study of evolution. In this dissertation I develop and use comparative genomic technologies to investigate the novel SARS-CoV-2 virus, assembly the first genome of the black lace domestic angelfish and identify germline genetic variants associated with altered breast cancer-specific survival. Our genome tiling array for the novel coronavirus presents a rapid and cost-effective method to sequence the entire viral genome and can be used to track the rapid evolution of viral variants in the population. The domestic angelfish is a member of the …

Impact Of Intratumor Heterogeneity And The Tumor Microenvironment In Shaping Tumor Evolution And Response To Therapy, Akash Mitra

Dissertations & Theses (Open Access)

Intratumor heterogeneity (ITH) is a crucial challenge in cancer treatment. The genotypic and phenotypic heterogeneity underlying diverse cancer types leads to subclonal variation, which may result in mixed or failed response to therapy. The heterogeneity at the tumor level, along with the tumor microenvironment (TME), often shapes tumor evolution and ultimately clinical outcome. Given that modern treatment paradigms increasingly expose patients with metastatic disease to multiple treatment modalities through the course of their disease, there exists a need to characterize robust and predictive biomarkers of response to therapy. In order to accurately characterize tumor evolution, we need to account for …

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 …

Mucin And Splice Variant Profiles Of Pancreatic Adenocarcinoma Predict Patient Survival And Subtyping, Christopher M. Thompson

Theses & Dissertations

PDAC is a pancreatic epithelial malignancy and demonstrates aggressive progression and bleak patient prognosis. Despite decades of research, the evolution of novel diagnostics and intervention modalities for PDAC is stagnant. This dissertation explores the characteristic aberrant and elevated expression of mucins in PDAC. Beginning with the hypothesis that mucins are associated with disease aggressiveness, analysis of PDAC patient survival in TCGA revealed no associations between single mucin expression and patient survival. This led to the underlying issue of PDAC tumor cellularity since this disease demonstrates variability in the proportion of cancer cells within the tumor. Tumor purity assessed with the …

Rare Variant Association Studies In Crohn’S Disease And Colorectal Cancer: Methods And Applications, Jiun-Sheng Chen

Dissertations & Theses (Open Access)

Genetic factors account for a substantial portion of Crohn’s disease and colorectal cancer (CRC) risk. Patients with Crohn’s disease, a condition that causes chronic inflammation of the gastrointestinal tract, are at increased risk of colorectal cancer morbidity and mortality. Genome-wide association studies using single marker approaches have identified loci responsible for these diseases, but disease susceptibility from rare variants is incompletely understood. This dissertation includes three chapters, two association studies for Crohn’s disease and CRC, and a statistical method to improve the power of statistical tests.

For Crohn’s disease, we performed targeted sequencing of 101 genes in 205 children with …

Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede

Dissertations & Theses (Open Access)

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …