Mosaicism occurs due to postzygotic genetic alterations during early embryonic development. The phenomenon is common, present in all humans, animals, and plants, and is associated with phenotypic variability and heterogeneity. Mosaic pathogenic gene variants result in a mosaic disease state, in which the individual can present with mild, generalized disease, a localized disease phenotype in specific organs and tissue regions, or full-blown clinical features which are indistinguishable from the heterozygous disease state. Multiple studies have described the prevalence and clinical correlations associated with low-level mosaicism for various genetic disorders, including several tumor suppressor gene (TSG) syndromes, which are well-known to display mosaicism. However, the extent of mosaicism research varies widely between TSG syndromes. Currently there is no comprehensive, up to date review covering multiple TSGs and focusing on mosaicism prevalence, diagnostic strategies and transmission risk. Here, in this literature review, I focus on 8 common tumor suppressor genes NF1, NF2, TSC1, TSC2, RB1, PTEN, VHL, and TP53; reporting the following disease aspects: • Role and function of each tumor suppressor gene, disease prevalence, inheritance pattern, penetrance/expressivity pattern, age of onset clinical features, organs affected, and benign or malignant tumors seen • Different types of mosaicism, including critical review of recent, representative publications for each tumor suppressor gene syndrome • Established criteria for clinical diagnosis of inherited versus mosaic disease, molecular diagnosis, and current methods of genetic analysis Then more extensively, this thesis discusses the most informative, representative original studies for each TSG and provides a summary which covers: • The number of mosaic patients analyzed and the spectrum of clinical features of the cohort they were sampled from • The spectrum of variant allele frequency (VAF), tissue types analyzed, and different analysis methods performed • Whether or not the mosaic patients met clinical criteria for diagnosis of inherited disease • The number of patients who were persistently classified as no mutation identified (NMI) after genetic analysis • Spectrum and type of mosaic mutational event(s) identified • Age of onset and age range of mosaic patients • Patient ascertainment and family history (sporadic or familial cases) and • Type of mosaicism seen Furthermore, it compares and discusses disease severity, possibility of malignancy, and genotype-phenotype correlations for each TSG. Ultimately, by juxtaposing these TSGs, this review aims to centralize existing knowledge about mosaicism and provide insight into how molecular techniques can be broadly applied for better diagnosis of mosaic disease. / 2022-11-10T00:00:00Z

It is important to understand the entire spectrum of somatic variants to gain more insight into mutations that occur in different cancers for development of better diagnostic, prognostic and therapeutic tools. This thesis outlines our work in understanding somatic variant calling, improving the identification of somatic variants from whole genome and whole exome platforms and identification of biomarkers for lung cancer. Integrating somatic variants from whole genome and whole exome platforms poses a challenge as variants identified in the exonic regions of the whole genome platform may not be identified on the whole exome platform and vice-versa. Taking a simple union or intersection of the somatic variants from both platforms would lead to inclusion of many false positives (through union) and exclusion of many true variants (through intersection). We develop the first framework to improve the identification of somatic variants on whole genome and exome platforms using a machine learning approach by combining the results from two popular somatic variant callers. Testing on simulated and real data sets shows that our framework identifies variants more accurately than using only one somatic variant caller or using variants from only one platform. Short tandem repeats (STRs) are repetitive units of 2-6 nucleotides. STRs make up approximately 1% of the human genome and have been traditionally used as genetic markers in population studies. We conduct a series of in silico analyses using the exome data of 32 individuals with lung cancer to identify 103 STRs that could potentially serve as cancer diagnostic markers and 624 STRs that could potentially serve as cancer predisposition markers. Overall these studies improve the accuracy in identification of somatic variants and highlight the association of STRs to lung cancer. / Ph. D.