Biology subjects

Elnitski, L. L.

Publications and source records attributed to Elnitski, L. L..

3 recordsLinked to original sources

bioRxiv2025

Discovery and performance of DNA methylation panels for cancer detection and classification in blood

Examining DNA in a liquid biopsy for non-invasive cancer detection relies on identifying dilute signal in a high background. This study aims to identify DNA methylation biomarkers for multi-cancer detection. Utilizing large tissue datasets, we apply novel search algorithms to discover confined biomarker panels capable of distinguishing tumor from normal and determining the tissue of origin. We explore the applicability to blood-based testing using targeted methylation sequencing followed by machine learning classification. We present an 8-marker panel, which successfully predicts tumors across 14 types with a 91% average sensitivity, maintaining a low false positive rate (< 0.04%). Additionally, a panel of 39 CpG sites exhibits accuracies ranging from 69% to 98% for identifying tissue of origin. When tested on 114 patient plasma samples (colon, liver, pancreatic, prostate, and stomach cancer), the 8-marker panel obtains an AUC of 0.78 with a 78% sensitivity among 32 early-stage patients (stage I-II), and 60% overall. Using the 39-marker panel in a multi-class classification model selecting only the best match, 54% of tumor samples were on average correctly assigned to the tissue of origin, and up to 80% when allowing more inclusive criteria. Using a limited set of biomarkers, our work contributes to advancing non-invasive cancer diagnostics.

cancer biology↗

bioRxiv2025

Super-silencers are crucial for development and carcinogenesis in B cells.

The strength of the repressive histone H3 lysine 27 trimethylation modification signal varies drastically at individual silencers. Focusing on cases of an unusually strong repressive signal in regions that we refer to as super-silencers, we demonstrate that the regions that become B-cell super-silencers are originally associated with gene upregulation during development, and their target genes are highly expressed in stem cells, especially during early developmental stages. About 13% of B-cell super-silencers transmute to super-enhancers in B-cell lymphoma and 22% of these conversions recur across more than half of patients. Notably, genes associated with these conversions, like BCL6 and BACH2, are downregulated more swiftly than others when subjected to JQ1, a super-enhancer-disrupting bromodomain and extra-terminal domain inhibitor utilized in cancer chemotherapy. Furthermore, super-silencers are characterized by an over-representation of B-cell-cancer-associated mutations, both somatic and germline, and B-cell-cancer translocation breakpoints. This surpasses the prevalence found in other regulatory elements, such as CTCF binding sites, underlining the crucial role of super-silencers in forming and stabilizing regulatory topologies in standard B cells. For example, over 80% of cases involving the B-cell-lymphoma translocation t(3;14)(q27;q32) fuse super-silencers in the BCL6 locus with enhancer-rich domains. Finally, we demonstrate that the repressive mechanisms of super-silencers are partially governed by the CpG content in their sequences. While CpG-rich super-silencers often prevent promoters from interacting with enhancers, CpG-depleted super-silencers typically suppress the chromatin looping of nearby enhancers. In summary, our findings accentuate the critical role super-silencers play in the normal function of B-cells, suggesting that sequence mutations and activity modifications in these elements could be primary factors in B-cell carcinogenesis.

genomics↗

bioRxiv2023

SoMAS: Finding somatic mutations associated with alternative splicing in human cancers

Aberrant alternative splicing is prevalent in cancer and affects most cancer hallmarks involving proliferation, angiogenesis, and invasion. Somatic point mutations can exert their cancer-driving functions via splicing disruption. We propose "SoMAS" (Somatic Mutation associated with Alternative Splicing), an efficient computational pipeline based on principal component analysis techniques, to explore the role of somatic mutations in shaping the landscape of alternative splicing via both cis- and trans-acting mechanisms. Applying SoMAS to 33 cancer types consisting of 9,738 tumor samples in The Cancer Genome Atlas, we identified 908 somatically mutated genes significantly associated with altered isoform expression in three or more cancer types. These genes include many well-known oncogenes/suppressor genes, RNA binding protein and splicing factor genes with both biological and clinical significance. Many of our identified SoMAS genes were corroborated to affect gene splicing by independent cohorts and/or methodologies. With SoMAS, we for the first time demonstrate the potential network of somatic mutations associated with the overall splicing profiles of cancer transcriptomes, bridging the genetic and epigenetic regulation of human tumorigenesis in an innovative way.

cancer biology↗