NGS of brush cytology samples improves the detection of high-grade dysplasia and cholangiocarcinoma in patients with primary sclerosing cholangitis: A retrospective and prospective study.

BACKGROUND: Biliary dysplasia, a precursor of cholangiocarcinoma (CCA), is a common complication of primary sclerosing cholangitis. Patients with high-grade dysplasia (HGD) or early CCA who have received oncological treatment are candidates for liver transplantation. The preoperative diagnosis of CCA or HGD is challenging, and the sensitivity of biliary brush cytology (BC) is limited. METHODS: By using next-generation sequencing (NGS), we retrospectively analyzed archived tissue samples (n=62) obtained from explanted liver tissue and CCA samples to identify oncogenic mutations that occur during primary sclerosing cholangitis carcinogenesis. BC samples were prospectively collected from patients with primary sclerosing cholangitis (n=97) referred for endoscopic retrograde cholangiography to measure the diagnostic utility of NGS combined with BC compared with traditional cytology alone. RESULTS: Mutations in KRAS, GNAS, FLT3, RNF43, TP53, ATRX, and SMAD4 were detected in archived CCA or HGD samples. KRAS, GNAS, TP53, CDKN2A, FBXW7, BRAF, and ATM mutations were detected in prospectively collected brush samples from patients with histologically verified CCA or HGD. One patient with low-grade dysplasia in the explanted liver had KRAS and GNAS mutations in brush sample. No mutations were observed in brush samples or archived tissues in liver transplantation cases without biliary neoplasia. While KRAS mutations are common in biliary neoplasms, they were also observed in patients without biliary neoplasia during surveillance. CONCLUSIONS: In summary, NGS of BC samples increased the sensitivity of detecting biliary neoplasia compared with traditional cytology. Performing NGS on BC samples may help diagnose HGD or early CCA, benefiting the timing of liver transplantation.

Data-driven characterization of molecular phenotypes across heterogeneous sample collections.

Existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on molecular profiles. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensionality reduction algorithm t-distributed stochastic neighbor embedding (t-SNE) with multi-study and multi-platform data on hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation, comparison of molecular disease subtypes identified from separate t-SNE representations, and characterization of the obtained clusters based on pathway databases and additional data. In this manner, we performed an integrative analysis across multi-omics acute myeloid leukemia studies. Our approach indicated new molecular subtypes with differential survival and drug responsiveness among samples lacking fusion genes, including a novel myelodysplastic syndrome-like cluster and a cluster characterized with CEBPA mutations and differential activity of the S-adenosylmethionine-dependent DNA methylation pathway. In summary, integration across multiple studies can help to identify novel molecular disease subtypes and generate insight into disease biology.

Hemap: An Interactive Online Resource for Characterizing Molecular Phenotypes across Hematologic Malignancies.

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease context for new therapeutic approaches. We analyzed 9,544 transcriptomes from more than 30 hematologic malignancies, normal blood cell types, and cell lines, and showed that disease types could be stratified in a data-driven manner. We then identified cluster-specific pathway activity, new biomarkers, and in silico drug target prioritization through interrogation of drug target databases. Using known vulnerabilities and available drug screens, we highlighted the importance of integrating molecular phenotype with drug target expression for in silico prediction of drug responsiveness. Our analysis implicated BCL2 expression level as an important indicator of venetoclax responsiveness and provided a rationale for its targeting in specific leukemia subtypes and multiple myeloma, linked several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7, and EZH1) with chronic lymphocytic leukemia, and supported CDK6 as a disease-specific target in acute myeloid leukemia. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our publicly available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies. SIGNIFICANCE: This study describes a data resource for researching derailed cellular pathways and candidate drug targets across hematologic malignancies.

Overexpression of PTP4A3 in ETV6-RUNX1 acute lymphoblastic leukemia.

Cell signalling, which is often derailed in cancer, is a network of multiple interconnected pathways with numerous feedback mechanisms. Dynamics of cell signalling is intimately regulated by addition and removal of phosphate groups by kinases and phosphatases. We examined expression of members of the PTP4A family of phosphatases across acute leukemias. While expression of PTP4A1 and PTP4A2 remained relatively unchanged across diseases, PTP4A3 showed marked overexpression in ETV6-RUNX1 and BCR-ABL1 subtypes of precursor B cell acute lymphoblastic leukemia. We show that PTP4A3 is regulated by the ETV6-RUNX1 fusion, but noticed no marked impact on cell viability either after PTP4A3 silencing or treatment with a PTP4A3 inhibitor. Regulation of PTP4A3 expression is altered in specific subgroups of acute leukemias and this is likely brought about by expression of the aberrant fusion genes.

Genome-wide repression of eRNA and target gene loci by the ETV6-RUNX1 fusion in acute leukemia.

Approximately 20%-25% of childhood acute lymphoblastic leukemias carry the ETV6-RUNX1 (E/R) fusion gene, a fusion of two central hematopoietic transcription factors, ETV6 (TEL) and RUNX1 (AML1). Despite its prevalence, the exact genomic targets of E/R have remained elusive. We evaluated gene loci and enhancers targeted by E/R genome-wide in precursor B acute leukemia cells using global run-on sequencing (GRO-seq). We show that expression of the E/R fusion leads to widespread repression of RUNX1 motif-containing enhancers at its target gene loci. Moreover, multiple super-enhancers from the CD19+/CD20+-lineage were repressed, implicating a role in impediment of lineage commitment. In effect, the expression of several genes involved in B cell signaling and adhesion was down-regulated, and the repression depended on the wild-type DNA-binding Runt domain of RUNX1. We also identified a number of E/R-regulated annotated and de novo noncoding genes. The results provide a comprehensive genome-wide mapping between E/R-regulated key regulatory elements and genes in precursor B cell leukemia that disrupt normal B lymphopoiesis.

Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots.

Progression of malignancy to overt disease requires multiple genetic hits. Activation-induced deaminase (AID) can drive lymphomagenesis by generating off-target DNA breaks at loci that harbor highly active enhancers and display convergent transcription. The first active transcriptional profiles from acute lymphoblastic leukemia (ALL) patients acquired here reveal striking similarity at structural variation (SV) sites. Specific transcriptional features, namely convergent transcription and Pol2 stalling, were detected at breakpoints. The overlap was most prominent at SV with recognition motifs for the recombination activating genes (RAG). We present signal feature analysis to detect vulnerable regions and quantified from human cells how convergent transcription contributes to R-loop generation and RNA polymerase stalling. Wide stalling regions were characterized by high DNAse hypersensitivity and unusually broad H3K4me3 signal. Based on 1382 pre-B-ALL patients, the ETV6-RUNX1 fusion positive patients had over ten-fold elevation in RAG1 while high expression of AID marked pre-B-ALL lacking common cytogenetic changes.