TNRC18 engages H3K9me3 to mediate silencing of endogenous retrotransposons.

Trimethylation of histone H3 lysine 9 (H3K9me3) is crucial for the regulation of gene repression and heterochromatin formation, cell-fate determination and organismal development1. H3K9me3 also provides an essential mechanism for silencing transposable elements1-4. However, previous studies have shown that canonical H3K9me3 readers (for example, HP1 (refs. 5-9) and MPP8 (refs. 10-12)) have limited roles in silencing endogenous retroviruses (ERVs), one of the main transposable element classes in the mammalian genome13. Here we report that trinucleotide-repeat-containing 18 (TNRC18), a poorly understood chromatin regulator, recognizes H3K9me3 to mediate the silencing of ERV class I (ERV1) elements such as LTR12 (ref. 14). Biochemical, biophysical and structural studies identified the carboxy-terminal bromo-adjacent homology (BAH) domain of TNRC18 (TNRC18(BAH)) as an H3K9me3-specific reader. Moreover, the amino-terminal segment of TNRC18 is a platform for the direct recruitment of co-repressors such as HDAC-Sin3-NCoR complexes, thus enforcing optimal repression of the H3K9me3-demarcated ERVs. Point mutagenesis that disrupts the TNRC18(BAH)-mediated H3K9me3 engagement caused neonatal death in mice and, in multiple mammalian cell models, led to derepressed expression of ERVs, which affected the landscape of cis-regulatory elements and, therefore, gene-expression programmes. Collectively, we describe a new H3K9me3-sensing and regulatory pathway that operates to epigenetically silence evolutionarily young ERVs and exert substantial effects on host genome integrity, transcriptomic regulation, immunity and development.

Sub-Cluster Identification through Semi-Supervised Optimization of Rare-Cell Silhouettes (SCISSORS) in single-cell RNA-sequencing.

MOTIVATION: Single-cell RNA-sequencing (scRNA-seq) has enabled the molecular profiling of thousands to millions of cells simultaneously in biologically heterogenous samples. Currently, the common practice in scRNA-seq is to determine cell type labels through unsupervised clustering and the examination of cluster-specific genes. However, even small differences in analysis and parameter choosing can greatly alter clustering results and thus impose great influence on which cell types are identified. Existing methods largely focus on determining the optimal number of robust clusters, which can be problematic for identifying cells of extremely low abundance due to their subtle contributions toward overall patterns of gene expression. RESULTS: Here, we present a carefully designed framework, SCISSORS, which accurately profiles subclusters within broad cluster(s) for the identification of rare cell types in scRNA-seq data. SCISSORS employs silhouette scoring for the estimation of heterogeneity of clusters and reveals rare cells in heterogenous clusters by a multi-step semi-supervised reclustering process. Additionally, SCISSORS provides a method for the identification of marker genes of high specificity to the cell type. SCISSORS is wrapped around the popular Seurat R package and can be easily integrated into existing Seurat pipelines. AVAILABILITY AND IMPLEMENTATION: SCISSORS, including source code and vignettes, are freely available at https://github.com/jr-leary7/SCISSORS.

GM-CSF drives myelopoiesis, recruitment and polarisation of tumour-associated macrophages in cholangiocarcinoma and systemic blockade facilitates antitumour immunity.

OBJECTIVE: Intrahepatic cholangiocarcinoma (iCCA) is rising in incidence, and at present, there are limited effective systemic therapies. iCCA tumours are infiltrated by stromal cells, with high prevalence of suppressive myeloid populations including tumour-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs). Here, we show that tumour-derived granulocyte-macrophage colony-stimulating factor (GM-CSF) and the host bone marrow is central for monopoiesis and potentiation of TAMs, and abrogation of this signalling axis facilitates antitumour immunity in a novel model of iCCA. METHODS: Blood and tumours were analysed from iCCA patients and controls. Treatment and correlative studies were performed in mice with autochthonous and established orthotopic iCCA tumours treated with anti-GM-CSF monoclonal antibody. RESULTS: Systemic elevation in circulating myeloid cells correlates with poor prognosis in patients with iCCA, and patients who undergo resection have a worse overall survival if tumours are more infiltrated with CD68+ TAMs. Mice with spontaneous iCCA demonstrate significant elevation of monocytic myeloid cells in the tumour microenvironment and immune compartments, and tumours overexpress GM-CSF. Blockade of GM-CSF with a monoclonal antibody decreased tumour growth and spread. Mice bearing orthotopic tumours treated with anti-GM-CSF demonstrate repolarisation of immunosuppressive TAMs and MDSCs, facilitating T cell response and tumour regression. GM-CSF blockade dampened inflammatory gene networks in tumours and TAMs. Human tumours with decreased GM-CSF expression exhibit improved overall survival after resection. CONCLUSIONS: iCCA uses the GM-CSF-bone marrow axis to establish an immunosuppressive tumour microenvironment. Blockade of the GM-CSF axis promotes antitumour T cell immunity.

Purity Independent Subtyping of Tumors (PurIST) Pancreatic Cancer Classifier: Analytic Validation of a 16-RNA Expression Signature Distinguishing Basal and Classical Subtypes.

The two major molecular subtypes of pancreatic adenocarcinoma reportedly have differential response to FOLFIRINOX-based therapy. To promote rapid assignment of basal versus classical subtypes, an array-based single-sample classifier assay was developed and applied to 74 formalin-fixed, paraffin-embedded biopsy or resection specimens of known subtype based on transcriptomics. The Purity Independent Subtyping of Tumors (PurIST) algorithm assigns subtype based on relative expression of 16 RNAs counted by RNA sequencing (RNAseq) versus more practical array-based NanoString nCounter Elements XT technology. Subtype calls were largely concordant between RNAseq and array methods (72/74, 97% agreement). Compared with the lengthy RNAseq protocol, the array-based assay takes just 3 working days to analyze, permitting rapid reporting of tumor subtype. In conclusion, the PurIST pancreatic cancer classifier has robust performance to classify pancreatic adenocarcinoma into basal versus classical subtypes. Clinical validation studies are underway to evaluate outcome in patients whose standard-of-care chemotherapy regimen is selected on the basis of rapid subtype assignment (NCT04683315).

Consensus molecular subtype differences linking colon adenocarcinoma and obesity revealed by a cohort transcriptomic analysis.

Colorectal cancer (CRC) is the third-leading cause of cancer-related deaths in the United States and worldwide. Obesity-a worldwide public health concern-is a known risk factor for cancer including CRC. However, the mechanisms underlying the link between CRC and obesity have yet to be fully elucidated in part because of the molecular heterogeneity of CRC. We hypothesized that obesity modulates CRC in a consensus molecular subtype (CMS)-dependent manner. RNA-seq data and associated tumor and patient characteristics including body weight and height data for 232 patients were obtained from The Cancer Genomic Atlas-Colon Adenocarcinoma (TCGA-COAD) database. Tumor samples were classified into the four CMSs with the CMScaller R package; body mass index (BMI) was calculated and categorized as normal, overweight, and obese. We observed a significant difference in CMS categorization between BMI categories. Differentially expressed genes (DEGs) between obese and overweight samples and normal samples differed across the CMSs, and associated prognostic analyses indicated that the DEGs had differing associations on survival. Using Gene Set Enrichment Analysis, we found differences in Hallmark gene set enrichment between obese and overweight samples and normal samples across the CMSs. We constructed Protein-Protein Interaction networks and observed differences in obesity-regulated hub genes for each CMS. Finally, we analyzed and found differences in predicted drug sensitivity between obese and overweight samples and normal samples across the CMSs. Our findings support that obesity impacts the CRC tumor transcriptome in a CMS-specific manner. The possible associations reported here are preliminary and will require validation using in vitro and animal models to examine the CMS-dependence of the genes and pathways. Once validated the obesity-linked genes and pathways may represent new therapeutic targets to treat colon cancer in a CMS-dependent manner.