Recurrent Fusion Genes in Gastric Cancer: CLDN18-ARHGAP26 Induces Loss of Epithelial Integrity.

Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed. Cell Rep 2015 Jul 14; 12(2):272-285

Differential Expression between Human Dermal Papilla Cells from Balding and Non-Balding Scalps Reveals New Candidate Genes for Androgenetic Alopecia

Agency for Science, Technology and Research (A*STAR). EC is supported by the A*STAR Graduate Scholarship program

Patient-specific driver gene prediction and risk assessment through integrated network analysis of cancer omics profiles.

Extensive and multi-dimensional data sets generated from recent cancer omics profiling projects have presented new challenges and opportunities for unraveling the complexity of cancer genome landscapes. In particular, distinguishing the unique complement of genes that drive tumorigenesis in each patient from a sea of passenger mutations is necessary for translating the full benefit of cancer genome sequencing into the clinic. We address this need by presenting a data integration framework (OncoIMPACT) to nominate patient-specific driver genes based on their phenotypic impact. Extensive in silico and in vitro validation helped establish OncoIMPACT\u27s robustness, improved precision over competing approaches and verifiable patient and cell line specific predictions (2/2 and 6/7 true positives and negatives, respectively). In particular, we computationally predicted and experimentally validated the gene TRIM24 as a putative novel amplified driver in a melanoma patient. Applying OncoIMPACT to more than 1000 tumor samples, we generated patient-specific driver gene lists in five different cancer types to identify modes of synergistic action. We also provide the first demonstration that computationally derived driver mutation signatures can be overall superior to single gene and gene expression based signatures in enabling patient stratification and prognostication. Source code and executables for OncoIMPACT are freely available from http://sourceforge.net/projects/oncoimpact. Nucleic Acids Res 2015 Apr 20; 43(7):e44

Experimental and bioinformatics considerations in cancer application of single cell genomics

Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient's tumour at the intercellular level. However, the DNA yield per cell is insufficient for today's sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology

Observations that suggest a contribution of altered dermal papilla mitochondrial function to androgenetic alopecia

Androgenetic alopecia (AGA) is a prevalent hair loss condition in males that develops due to the influence of androgens and genetic predisposition. With the aim of elucidating genes involved in AGA pathogenesis, we modelled AGA with three-dimensional culture of keratinocyte-surrounded dermal papilla (DP) cells. We co-cultured immortalised balding and non-balding human DP cells (DPCs) derived from male AGA patients with epidermal keratinocyte (NHEK) using multi-interfacial polyelectrolyte complexation technique. We observed up-regulated mitochondria-related gene expression in balding compared with non-balding DP aggregates which indicated altered mitochondria metabolism. Further observation of significantly reduced electron transport chain complex activity (complexes I, IV and V), ATP levels and ability to uptake metabolites for ATP generation demonstrated compromised mitochondria function in balding DPC. Balding DP was also found to be under significantly higher oxidative stress than non-balding DP. Our experiments suggest that application of antioxidants lowers oxidative stress levels and improves metabolite uptake in balding DPC. We postulate that the observed up-regulation of mitochondria-related genes in balding DP aggregates resulted from an over-compensatory effort to rescue decreased mitochondrial function in balding DP through the attempted production of new functional mitochondria. In all, our three-dimensional co-culturing revealed mitochondrial dysfunction in balding DPC, suggesting a metabolic component in the aetiology of AGA

Whole-genome reconstruction and mutational signatures in gastric cancer.

BACKGROUND: Gastric cancer is the second highest cause of global cancer mortality. To explore the complete repertoire of somatic alterations in gastric cancer, we combined massively parallel short read and DNA paired-end tag sequencing to present the first whole-genome analysis of two gastric adenocarcinomas, one with chromosomal instability and the other with microsatellite instability. RESULTS: Integrative analysis and de novo assemblies revealed the architecture of a wild-type KRAS amplification, a common driver event in gastric cancer. We discovered three distinct mutational signatures in gastric cancer--against a genome-wide backdrop of oxidative and microsatellite instability-related mutational signatures, we identified the first exome-specific mutational signature. Further characterization of the impact of these signatures by combining sequencing data from 40 complete gastric cancer exomes and targeted screening of an additional 94 independent gastric tumors uncovered ACVR2A, RPL22 and LMAN1 as recurrently mutated genes in microsatellite instability-positive gastric cancer and PAPPA as a recurrently mutated gene in TP53 wild-type gastric cancer. CONCLUSIONS: These results highlight how whole-genome cancer sequencing can uncover information relevant to tissue-specific carcinogenesis that would otherwise be missed from exome-sequencing data

An integrative model of pathway convergence in genetically heterogeneous blast crisis chronic myeloid leukemia

Targeted therapies against the BCR-ABL1 kinase have revolutionized treatment of chronic phase (CP) chronic myeloid leukemia (CML). In contrast, management of blast crisis (BC) CML remains challenging because BC cells acquire complex molecular alterations that confer stemness features to progenitor populations and resistance to BCR-ABL1 tyrosine kinase inhibitors. Comprehensive models of BC transformation have proved elusive because of the rarity and genetic heterogeneity of BC, but are important for developing biomarkers predicting BC progression and effective therapies. To better understand BC, we performed an integrated multiomics analysis of 74 CP and BC samples using wholegenome and exome sequencing, transcriptome and methylome profiling, and chromatin immunoprecipitation followed by high-throughput sequencing. Employing pathway-based analysis, we found the BC genome was significantly enriched for mutations affecting components of the polycomb repressive complex (PRC) pathway. While transcriptomically, BC progenitors were enriched and depleted for PRC1- and PRC2-related gene sets respectively. By integrating our data sets, we determined that BC progenitors undergo PRCdriven epigenetic reprogramming toward a convergent transcriptomic state. Specifically, PRC2 directs BC DNA hypermethylation, which in turn silences key genes involved in myeloid differentiation and tumor suppressor function via so-called epigenetic switching, whereas PRC1 represses an overlapping and distinct set of genes, including novel BC tumor suppressors. On the basis of these observations, we developed an integrated model of BC that facilitated the identification of combinatorial therapies capable of reversing BC reprogramming (decitabine1PRC1 inhibitors), novel PRC-silenced tumor suppressor genes (NR4A2), and gene expression signatures predictive of disease progression and drug resistance in CP