Bioinformatics Commons^™

A Review Of How Bioinformatics And Genome Sequencing Are Affecting Precision Medicine, Taylor S. Hickey

Honors Theses

Advancement in genomic sequencing and bioinformatics methods have been affecting biomedical research through precision medicine, especially in the area of cancer. Vaccine therapies can be developed using neoantigens that target specific mutations in tumors. The goals of this research are to identify mutations that lead to cancer and then define subpopulations in which patients can easily be identified. The future goal is to have targeted vaccines that are specific to each subpopulation ready to be used in treatment of their cancer. Limitations to reaching these goals have been due to tumor heterogeneity, cancer location, and difficulty in creating neoantigens for …

The Genetics Of Skin Cancer: What Genes Drive The Development Of Basal Cell Carcinoma, Squamous Cell Carcinoma, And Melanoma?, Cassandra Poole, Abagail Pack, Elizabeth Whitehead, Virginia Marshall

Spring Showcase for Research and Creative Inquiry

Skin cancer is one of the most common forms of cancer worldwide. The American Academy of Dermatology estimates that 9500 people in the United States are diagnosed with skin cancer every day, and that 1 in 5 Americans will be diagnosed with skin cancer by age 70. With such a high prevalence of disease, understanding how skin cancer develops and how it can be treated is extremely important. This project aims to analyze the genes involved in the development of the three most common forms of skin cancer: basal cell carcinoma, squamous cell carcinoma, and melanoma.

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 …

Real-World Evaluation Of Universal Germline Screening For Cancer Treatment-Relevant Pharmacogenes, Megan L. Hutchcraft, Nan Lin, Shulin Zhang, Catherine Sears, Kyle Zacholski, Elizabeth A. Belcher, Eric B. Durbin, John L. Villano, Michael J. Cavnar, Susanne M. Arnold, Frederick R. Ueland, Jill M. Kolesar

Pathology and Laboratory Medicine Faculty Publications

The purpose of this study was to determine the frequency of clinically actionable treatment-relevant germline pharmacogenomic variants in patients with cancer and assess the real-world clinical utility of universal screening using whole-exome sequencing in this population. Cancer patients underwent research-grade germline whole-exome sequencing as a component of sequencing for somatic variants. Analysis in a clinical bioinformatics pipeline identified clinically actionable pharmacogenomic variants. Clinical Pharmacogenetics Implementation Consortium guidelines defined clinical actionability. We assessed clinical utility by reviewing electronic health records to determine the frequency of patients receiving pharmacogenomically actionable anti-cancer agents and associated outcomes. This observational study evaluated 291 patients with …

Integrated Multiparametric Radiomics And Informatics System For Characterizing Breast Tumor Characteristics With The Oncotypedx Gene Assay, Michael A. Jacobs, Christopher B. Umbricht, Vishwa S. Parekh, Riham H. El Khouli, Leslie Cope, Katarzyna J. Macura, Susan Harvey, Antonio C. Wolff

Radiology Faculty Publications

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained …

A Novel Approach For Classifying Gene Expression Data Using Topic Modeling, Soon Jye Kho, Himi Yalamanchili, Michael L. Raymer, Amit Sheth

Kno.e.sis Publications

Understanding the role of differential gene expression in cancer etiology and cellular process is a complex problem that continues to pose a challenge due to sheer number of genes and inter-related biological processes involved. In this paper, we employ an unsupervised topic model, Latent Dirichlet Allocation (LDA) to mitigate overfitting of high-dimensionality gene expression data and to facilitate understanding of the associated pathways. LDA has been recently applied for clustering and exploring genomic data but not for classification and prediction. Here, we proposed to use LDA inclustering as well as in classification of cancer and healthy tissues using lung cancer …

Pharmacogenetic Discovery In Calgb (Alliance) 90401 And Mechanistic Validation Of A Vac14 Polymorphism That Increases Risk Of Docetaxel-Induced Neuropathy, Heather E. Wheeler

Bioinformatics Faculty Publications

Purpose: Discovery of SNPs that predict a patient's risk of docetaxel-induced neuropathy would enable treatment individualization to maximize efficacy and avoid unnecessary toxicity. The objectives of this analysis were to discover SNPs associated with docetaxel-induced neuropathy and mechanistically validate these associations in preclinical models of drug-induced neuropathy.

Experimental Design: A genome-wide association study was conducted in metastatic castrate-resistant prostate cancer patients treated with docetaxel, prednisone and randomized to bevacizumab or placebo on CALGB 90401. SNPs were genotyped on the Illumina HumanHap610-Quad platform followed by rigorous quality control. The inference was conducted on the cumulative dose at occurrence of grade 3+ …

Towards The Prediction Of Mutations In Genomic Sequences, Juan Carlos Martinez

FIU Electronic Theses and Dissertations

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today’s cancer research.

Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the …