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Biology subjects

Severson, D. T.

Publications and source records attributed to Severson, D. T..

3 recordsLinked to original sources

Comprehensive multi-site profiling of the malignant pleural mesothelioma micro-environment identifies candidate molecular determinants of histopathologic type

Pleural mesothelioma (PM) comprises sarcomatoid, epithelioid and biphasic histologic subtypes. Bulk PM RNA-sequencing identifies a histology-associated molecular gradient with features of epithelial-mesenchymal (EM) transition but cannot parse malignant, stromal, and immune tumor components. The mechanisms driving PM malignant cell phenotype and associated histology is not well-characterized. Here, we use single-cell RNA-sequencing (scRNA-seq) paired with exome, bulk RNA-sequencing, and histologic analysis of adjacent samples to characterize malignant cell EM state, parse the tumor microenvironment (TME), and identify candidate drivers of PM cell fate. We observe EM variation in malignant cells analogous to bulk samples. We characterize epithelioid and sarcomatoid malignant cell programs and identify a new uncommitted malignant cell EM phenotype enriched in biphasic histology samples. Using inferred CNVs we observe that single individual PM clones consist of cells exhibiting all three EM cell states. We find that distinct non-malignant microenvironments associated with tumors consisting of mostly cells in each state, and identify WNT inhibition, GAS6-AXL, and HBEGF-EGFR signaling as pathways associated with distinct EM cell states. These findings provide deeper insight into the molecular drivers of PM malignant cells and identify non-malignant cell signals as potential EMT and growth drivers in PM.

cancer biology↗

Single cell RNA-seq reveals profound transcriptional similarity between Barretts esophagus and esophageal glands

Barretts esophagus is a precursor of esophageal adenocarcinoma. In this common condition, squamous epithelium in the esophagus is replaced by columnar epithelium in response to acid reflux. Barretts esophagus is highly heterogeneous and its relationships to normal tissues are unclear. We investigated the cellular complexity of Barretts esophagus and the upper gastrointestinal tract using RNA-sequencing of 2895 single cells from multiple biopsies from four patients with Barretts esophagus and two patients without esophageal pathology. We found that uncharacterised cell populations in Barretts esophagus, marked by LEFTY1 and OLFM4, exhibit a profound transcriptional overlap with a subset of esophageal cells, but not with gastric or duodenal cells. Additionally, SPINK4 and ITLN1 mark cells that precede morphologically identifiable goblet cells in colon and Barretts esophagus, potentially aiding the identification of metaplasia. Our findings reveal striking transcriptional relationships between normal tissue populations and cells in a premalignant condition, with implications for clinical practice.

genetics↗

BEARscc: Robustness Of Single-Cell Clusters Determined Using Simulated Technical Replicates

Technical variance is a major confounding factor in single-cell RNA sequencing, not least because it is not possible to replicate measurements on the same cell. We present BEARscc, a tool that uses RNA spike-in controls to simulate experiment-specific technical replicates. We demonstrate that the tool improves the unsupervised classification of cells and facilitates the biological interpretation of single-cell RNA-seq experiments.

bioinformatics↗