Regulatory and epigenetic landscapes in biological discovery, diagnostics and disease mechanisms

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Epigenetics Research in the Elnitski Lab DNA Methylation Biomarkers and Cancer Detection: The Elnitski lab's groundbreaking work in DNA methylation biomarkers has propelled blood-based multi-cancer detection forward. Our versatile ZNF154 biomarker spans over 14 cancer types (Sanchez-Vega et al. 2013), garnering global attention for its potential to revolutionize cancer screening. Simulating blood-based data, we differentiated tumor DNA from normal samples (Margolin et al. 2014). Our innovative computational approach and blood-based assay detected ovarian cancer DNA, outperforming CA-125 (Miller et al. 2020), and demonstrated efficacy in identifying both early and late-stage pancreatic and colon cancers (Miller et al. 2021). Multi-Cancer Marker Combinations: Recognizing the transformative potential of non-invasive cancer detection through blood-based tests, we expanded our research to include testing combinations of multi-cancer markers. By analyzing tumor methylation array data from The Cancer Genome Atlas (TCGA) across 14 cancer types, we identified additional markers. Rigorous evaluation of these markers by logistic regression models revealed that combining three markers led to a substantial increase in the average area under the ROC curve (AUC) across the 14 tumor types, outperforming single markers (Manuscript submitted). Epigenetic Regulation and Tumor Phenotypic Variation: The Elnitski lab's focus on epigenetic regulation extended to addressing phenotypic differences in solid human epithelial cancers. Through a computational method, we unveiled the presence of the CpG island methylator phenotype (CIMP) across 14 distinct cancer types, based on The Cancer Genome Atlas data, as well as 23 cancer cell lines (Sanchez-Vega et al. 2015). A significant contribution was made by reporting the first instance of CIMP in ovarian tumors, noting similar methylation changes in ovarian and uterine endometrioid tumors (Kolbe et al. 2012). This work highlighted shared biological pathways across diverse cancers, suggesting potential common underlying causes (Miller et al. 2016, Sanchez-Vega et al. 2017). Notably, ongoing efforts involve testing small molecules with the potential to reverse the methylation phenotype (Manuscript in preparation). Ovarian Cancer Epigenetics Research: Within the realm of epigenetic regulation, the Elnitski lab's investigations have further assessed ovarian cancer. We discovered that ovarian cancers with distinct molecular subtypes exhibit differences in DNA methylation landscapes (Li et al. 2021). Specifically, serous tumors, the most aggressive subtype, displayed gene repression, possibly due to selective silencing of important genes. The lab further investigated the ESR1 regulatory axis in serous epithelial ovarian cancer, utilizing size exclusion chromatography to uncover a complex containing ESR1 and other factors. Our findings highlighted a pervasive regulatory network that impacted pathways related to proliferation, epithelial-mesenchymal transition, and apoptosis. Emerging therapeutic strategies aim at enhancing hormonal therapy efficacy (Manuscript in preparation). Splicing Research in the Elnitski Lab Isoform Expression as a Cancer Driver: Mutations in the human kinome drive cancer, however, the full story of processes that drive cancer extends beyond mutations. To understand melanoma, our study examined isoform expression changes in 538 kinases and 3,040 isoforms across 103 primary tumor and 367 metastatic samples from TCGA (Holland et al 2022). We identified significant differential expression (DE) and isoform ratio differences (DIR). DE enriched receptor tyrosine kinases, while DIR revealed splicing changes in non-receptor tyrosine kinases, emphasizing the crucial role of isoform-level expression analysis. We demonstrated differential apoptosis and protein localization due to distinct splicing isoforms of the SLK gene. Clustering of tumor samples by isoform expression unveiled subgroups tied to driver mutations and progression of tumor metastasis. Samples with BRAF hotspot mutations separated from those with RAS hotspot mutations, indicating potential treatment-specific responses. Subgroupings identified distinct phenotypic features, such as immune infiltrate or apoptosis-related genes, or suppressors of tumor metastasis, implying crucial loss-of-function events. Our study introduces a novel approach for therapeutic target identification, highlighting the importance of isoform expression profiles. Somatic Mutations and Splicing Alteration: Building on our prior work, we examined the intersection of somatic mutations and alternative splicing dysregulation in cancer. We developed a machine learning classifier capable of identifying mutations disrupting splicing, paving the way for a deeper understanding of the interplay between genetic mutations and splicing alterations (Gotea et al. 2019). Expanding on this work, we addressed the relationship between somatic point mutations and alternative splicing across a spectrum of 33 cancer types. This widespread aberrant alternative splicing in cancer impacts crucial traits such as proliferation, angiogenesis, and invasion. Our innovative approach introduced the concept of "SoMAS" (Somatic Mutation associated with Alternative Splicing), a computational pipeline that utilizes principal component analysis (PCA) to explore how somatic mutations influence alternative splicing. Through comprehensive analysis involving 33 cancer types and 9,738 tumor samples from The Cancer Genome Atlas, we identified 908 somatically mutated genes linked to altered isoform expression across multiple cancer types. Notably, these genes encompass well-established oncogenes, tumor suppressor genes, RNA binding proteins, and splicing factors, offering both biological and clinical relevance. Our findings have been substantiated by independent cohorts and methodologies, thereby illuminating the intricate network connecting somatic mutations with overall splicing profiles in cancer transcriptomes (Manuscript submitted). Expression Analysis in ADHD: The Elnitski lab extended our expression studies to collaborate on neurodevelopmental disorders, with a focus on attention deficit hyperactivity disorder (ADHD). We helped to unravel the molecular mechanistic understanding of ADHD (Sudre et al 2023). New findings revealed significant differential expression of genes in the anterior cingulate cortex and the caudate, particularly downregulation of neurotransmitter gene pathways, including glutamatergic pathways. This transcriptomic evidence points to cortico-striatal neurotransmitter anomalies in the pathogenesis of ADHD, aligning with current models of the disorder. Unveiling Latent Splicing Mechanisms: The Elnitski lab's research also addressed latent splicing mechanisms, uncovering hidden processes occurring in cellular stress and cancer. Our model proposed a novel paradigm for preventing latent splicing, centered on the initiator-tRNA operating in the nucleus independently of protein translation (Shefer et al. 2022). By identifying nucleolin (NCL) as a key player in this mechanism, we demonstrated its direct engagement with initiator-tRNA within the nucleus. This interaction prevents latent splicing through nucleolin's involvement. The validation of this model came from nucleolin knockdown experiments, revealing activation of latent splicing in vital coding transcripts. This novel understanding of splicing regulation adds a new layer of complexity to the field and carries implications for human diseases. We are now exploring additional factors in the complex to understand their role in human diseases (Manuscript in preparation).