Comparative analyses define differences between BHD-associated renal tumour and sporadic chromophobe renal cell carcinoma.

BACKGROUND: Birt-Hogg-Dubé (BHD) syndrome, caused by germline alteration of folliculin (FLCN) gene, develops hybrid oncocytic/chromophobe tumour (HOCT) and chromophobe renal cell carcinoma (ChRCC), whereas sporadic ChRCC does not harbor FLCN alteration. To date, molecular characteristics of these similar histological types of tumours have been incompletely elucidated. METHODS: To elucidate renal tumourigenesis of BHD-associated renal tumours and sporadic renal tumours, we conducted whole genome sequencing (WGS) and RNA-sequencing (RNA-seq) of sixteen BHD-associated renal tumours from nine unrelated BHD patients, twenty-one sporadic ChRCCs and seven sporadic oncocytomas. We then compared somatic mutation profiles with FLCN variants and RNA expression profiles between BHD-associated renal tumours and sporadic renal tumours. FINDINGS: RNA-seq analysis revealed that BHD-associated renal tumours and sporadic renal tumours have totally different expression profiles. Sporadic ChRCCs were clustered into two distinct clusters characterized by L1CAM and FOXI1 expressions, molecular markers for renal tubule subclasses. Increased mitochondrial DNA (mtDNA) copy number with fewer variants was observed in BHD-associated renal tumours compared to sporadic ChRCCs. Cell-of-origin analysis using WGS data demonstrated that BHD-associated renal tumours and sporadic ChRCCs may arise from different cells of origin and second hit FLCN alterations may occur in early third decade of life in BHD patients. INTERPRETATION: These data further our understanding of renal tumourigenesis of these two different types of renal tumours with similar histology. FUNDING: This study was supported by JSPS KAKENHI Grants, RIKEN internal grant, and the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), Center for Cancer Research.

COOBoostR: An Extreme Gradient Boosting-Based Tool for Robust Tissue or Cell-of-Origin Prediction of Tumors.

We present here COOBoostR, a computational method designed for the putative prediction of the tissue- or cell-of-origin of various cancer types. COOBoostR leverages regional somatic mutation density information and chromatin mark features to be applied to an extreme gradient boosting-based machine-learning algorithm. COOBoostR ranks chromatin marks from various tissue and cell types, which best explain the somatic mutation density landscape of any sample of interest. A specific tissue or cell type matching the chromatin mark feature with highest explanatory power is designated as a potential tissue- or cell-of-origin. Through integrating either ChIP-seq based chromatin data, along with regional somatic mutation density data derived from normal cells/tissue, precancerous lesions, and cancer types, we show that COOBoostR outperforms existing random forest-based methods in prediction speed, with comparable or better tissue or cell-of-origin prediction performance (prediction accuracy-normal cells/tissue: 76.99%, precancerous lesions: 95.65%, cancer cells: 89.39%). In addition, our results suggest a dynamic somatic mutation accumulation at the normal tissue or cell stage which could be intertwined with the changes in open chromatin marks and enhancer sites. These results further represent chromatin marks shaping the somatic mutation landscape at the early stage of mutation accumulation, possibly even before the initiation of precancerous lesions or neoplasia.

Hybrid Stomach-Intestinal Chromatin States Underlie Human Barrett's Metaplasia.

BACKGROUND & AIMS: Tissue metaplasia is uncommon in adults because established cis-element programs resist rewiring. In Barrett's esophagus, the distal esophageal mucosa acquires a predominantly intestinal character, with notable gastric features, and is predisposed to developing invasive cancers. We sought to understand the chromatin underpinnings of Barrett's metaplasia and why it commonly displays simultaneous gastric and intestinal properties. METHODS: We profiled cis-regulatory elements with active histone modifications in primary human biopsy materials using chromatin immunoprecipitation followed by DNA sequencing. Mutations in Barrett's esophagus were examined in relation to tissue-specific enhancer landscapes using a random forest machine-learning algorithm. We also profiled open chromatin at single-cell resolution in primary Barrett's biopsy specimens using the assay for transposase-accessible chromatin. We used 1- and 2-color immunohistochemistry to examine protein expression of tissue-restricted genes. RESULTS: Barrett's esophagus bears epigenome fingerprints of human stomach and intestinal columnar, but not esophageal squamous, epithelia. Mutational patterns were best explained as arising on the epigenome background of active gastric cis-elements, supporting the view that adjoining stomach epithelium is a likely tissue source. Individual cells in Barrett's metaplasia coexpress gastric and intestinal genes, reflecting concomitant chromatin access at enhancers ordinarily restricted to one or the other epithelium. Protein expression of stomach-specific mucins; CLDN18; and a novel gastric marker, ANXA10, showed extensive tissue and subclonal heterogeneity of dual stomach-intestinal cell states. CONCLUSIONS: These findings reveal mixed and dynamic tissue-restricted chromatin states and phenotypic heterogeneity in Barrett's esophagus. Pervasive intragland variation argues against stem-cell governance of this phenotype.

Biomedical Entity Explorer: A Web Server for Biomedical Entity Exploration.

Biomedical Entity Explorer (BEE) is a web server that can search for biomedical entities from a database of six biomedical entity types (gene, miRNA, drug, disease, single nucleotide polymorphism [SNP], pathway) and their gene associations. The search results can be explored using intersections, unions, and negations. BEE has integrated biomedical entities from 16 databases (Ensemble, PharmGKB, Genetic Home Reference, Tarbase, Mirbase, NCI Thesaurus, DisGeNET, Linked life data, UMLS, GSEA MsigDB, Reactome, KEGG, Gene Ontology, HGVD, SNPedia, and dbSNP) based on their gene associations and built a database with their synonyms, descriptions, and links containing individual details. Users can enter the keyword of one or more entities and select the type of entity for which they want to know the relationship for and by using set operations such as union, negation, and intersection, they can navigate the search results more clearly. We believe that BEE will not only be useful for biologists querying for complex associations between entities, but can also be a good starting point for general users searching for biomedical entities. BEE is accessible at (http://bike-bee.snu.ac.kr).

An Organoid Biobank of Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping.

Gastroenteropancreatic (GEP) neuroendocrine neoplasm (NEN) that consists of neuroendocrine tumor and neuroendocrine carcinoma (NEC) is a lethal but under-investigated disease owing to its rarity. To fill the scarcity of clinically relevant models of GEP-NEN, we here established 25 lines of NEN organoids and performed their comprehensive molecular characterization. GEP-NEN organoids recapitulated pathohistological and functional phenotypes of the original tumors. Whole-genome sequencing revealed frequent genetic alterations in TP53 and RB1 in GEP-NECs, and characteristic chromosome-wide loss of heterozygosity in GEP-NENs. Transcriptome analysis identified molecular subtypes that are distinguished by the expression of distinct transcription factors. GEP-NEN organoids gained independence from the stem cell niche irrespective of genetic mutations. Compound knockout of TP53 and RB1, together with overexpression of key transcription factors, conferred on the normal colonic epithelium phenotypes that are compatible with GEP-NEN biology. Altogether, our study not only provides genetic understanding of GEP-NEN, but also connects its genetics and biological phenotypes.

Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer.

Primary liver tissue cancer types are renowned to display a consistent increase in global disease burden and mortality, thus needing more effective diagnostics and treatments. Yet, integrative research efforts to identify cell-of-origin for these cancers by utilizing human specimen data were poorly established. To this end, we analyzed previously published whole-genome sequencing data for 384 tumor and progenitor tissues along with 423 publicly available normal tissue epigenomic features and single cell RNA-seq data from human livers to assess correlation patterns and extended this information to conduct in-silico prediction of the cell-of-origin for primary liver cancer subtypes. Despite mixed histological features, the cell-of-origin for mixed hepatocellular carcinoma/intrahepatic cholangiocarcinoma subtype was predominantly predicted to be hepatocytic origin. Individual sample-level predictions also revealed hepatocytes as one of the major predicted cell-of-origin for intrahepatic cholangiocarcinoma, thus implying trans-differentiation process during cancer progression. Additional analyses on the whole genome sequencing data of hepatic progenitor cells suggest these cells may not be a direct cell-of-origin for liver cancers. These results provide novel insights on the nature and potential contributors of cell-of-origins for primary liver cancers.

Chromatin marks shape mutation landscape at early stage of cancer progression.

Somatic mutation rates in cancer differ across the genome in a cancer cell-type specific manner. Although key factors that contribute to the differences were identified, the major cancer progression stage when these factors associate with the mutation variance remained poorly investigated. Here, we analyzed whole-genome sequencing data of pre-cancerous and matching cancer tissues from 173 individuals and 423 normal tissue chromatin features to determine the critical stage of these features contributing to shaping the somatic mutation landscape. Our data showed that the establishment of somatic mutation landscape inferred by chromatin features occur early in the process of cancer progression, and gastric acid reflux environmental exposure-mediated epigenetic changes, represented as gastric metaplasia, at early stage can dramatically impact the somatic mutation landscape. We suggest a possible crucial role of chromatin features during the mutation landscape establishment at early stage of progression in a cancer-type specific manner.