A proteo-genomic map of human health that identifies many potential causal disease genes and highlights genetically driven connections across diverse human conditions is published in Science this week. Noting that the characterization of the genetic regulation of proteins is essential for understanding disease etiology and developing therapies, a team led by investigators from the University of Cambridge identified 10,674 genetic associations for 3,892 plasma proteins to create a cis-anchored gene-protein-disease map of 1,859 connections that highlights strong cross-disease biological convergence. This map, they write, establishes a framework to connect etiologically related diseases, provide biological context for new or emerging disorders, and integrate different biological domains to establish mechanisms for known gene-disease links.
Using an integrated epigenomic and transcriptomic approach, a group led by University of Michigan scientists has identified a new potential therapeutic target for certain brain tumors. High-grade gliomas with arginine or valine substitutions of the histone H3.3 glycine-34 residue (H3.3G34R/V) carry a poor prognosis and current treatments are not curative. Because H3.3G34R/V mutations reprogram epigenetic modifications, the researchers used ChIP sequencing and ChromHMM computational analysis to define therapeutic dependencies in H3.3G34R/V gliomas. As reported in Science Translational Medicine, they find activating epigenetic modifications on histone H3 lysine residues, as well as DNA promoter hypomethylation. They also find redistribution of repressive histone marks at the leukemia inhibitory factor (LIF) locus, leading to increased LIF abundance and secretion. LIF activated STAT3 signaling to promote the survival of H3.3G34R/V glioma cells, while immunohistochemistry and single-cell RNA sequencing from H3.3G34R/V patient tumors revealed high STAT3 protein and RNA expression, respectively, in tumor cells with both inter- and intratumor heterogeneity. When STAT3 was targeted a blood-brain barrier-permeable small molecule in mice with H3.3G34R/V tumors, the drug suppressed tumor growth. The work identifies the LIF/STAT3 pathway as a key epigenetically driven and druggable vulnerability in H3.3G34R/V gliomas, the study's authors write. "This finding could inform development of targeted, combination therapies for these lethal brain tumors."
A new computational tool that uses single-cell epigenomic data to infer copy number variants (CNVs) that define cancer cells is presented in Science Advances this week. Single-cell epigenomic assays hold great potential for understanding the mechanisms of transcriptional control in functionally diverse cancer cell populations, but their use with clinical tumor specimens is limited by their inability to distinguish malignant from nonmalignant cells. To overcome this, scientist from the University of Calgary and collaborators developed Copy-scAT, an R package that uses single-cell assay transposase accessible chromatin sequencing datasets to call CNVs at the single-cell level. With scATAC data from adult and pediatric glioblastoma, as well as multiple myeloma, the researchers demonstrate the effectiveness of Copy-scAT in calling focal amplifications and chromosome arm-level gains and losses. "At the most basic level, Copy-scAT can therefore discriminate between malignant and nonmalignant cells in scATAC datasets based on the presence or absence, respectively, of CNVs," they write. "Furthermore, application of Copy-scAT allows the relationship between genetic and epigenetic differences to be investigated within individual subclones."