BioMet Toolbox 2.0: genome-wide analysis of metabolism and omics data

Analysis of large data sets using computational and mathematical tools have become a central part of biological sciences. Large amounts of data are being generated each year from different biological research fields leading to a constant development of software and algorithms aimed to deal with the increasing creation of information. The BioMet Toolbox 2.0 integrates a number of functionalities in a user-friendly environment enabling the user to work with biological data in a web interface. The unique and distinguishing feature of the BioMet Toolbox 2.0 is to provide a web user interface to tools for metabolic pathways and omics analysis developed under different platform-dependent environments enabling easy access to these computational tools

HnRNPK maintains single strand RNA through controlling double-strand RNA in mammalian cells

Although antisense transcription is a widespread event in the mammalian genome, double-stranded RNA (dsRNA) formation between sense and antisense transcripts is very rare and mechanisms that control dsRNA remain unknown. By characterizing the FGF-2 regulated transcriptome in normal and cancer cells, we identified sense and antisense transcripts IER3 and IER3-AS1 that play a critical role in FGF-2 controlled oncogenic pathways. We show that IER3 and IER3-AS1 regulate each other\u27s transcription through HnRNPK-mediated post-transcriptional regulation. HnRNPK controls the mRNA stability and colocalization of IER3 and IER3-AS1. HnRNPK interaction with IER3 and IER3-AS1 determines their oncogenic functions by maintaining them in a single-stranded form. hnRNPK depletion neutralizes their oncogenic functions through promoting dsRNA formation and cytoplasmic accumulation. Intriguingly, hnRNPK loss-of-function and gain-of-function experiments reveal its role in maintaining global single- and double-stranded RNA. Thus, our data unveil the critical role of HnRNPK in maintaining single-stranded RNAs and their physiological functions by blocking RNA-RNA interactions

Evaluation and assessment of read-mapping by multiple next-generation sequencing aligners based on genome-wide characteristics

Massive data produced due to the advent of next-generation sequencing (NGS) technology is widely used for biological researches and medical diagnosis. The crucial step in NGS analysis is read alignment or mapping which is computationally intensive and complex. The mapping bias tends to affect the downstream analysis, including detection of polymorphisms. In order to provide guidelines to the biologist for suitable selection of aligners; we have evaluated and benchmarked 5 different aligners (BWA, Bowtie2, NovoAlign, Smalt and Stampy) and their mapping bias based on characteristics of 5 microbial genomes. Two million simulated read pairs of various sizes (36 bp, 50 bp, 72 bp, 100 bp, 125 bp, 150 bp, 200 bp, 250 bp and 300 bp) were aligned. Specific alignment features such as sensitivity of mapping, percentage of properly paired reads, alignment time and effect of tandem repeats on incorrectly mapped reads were evaluated. BWA showed faster alignment followed by Bowtie2 and Smalt. NovoAlign and Stampy were comparatively slower. Most of the aligners showed high sensitivity towards long reads (> 100 bp) mapping. On the other hand NovoAlign showed higher sensitivity towards both short reads (36 bp, 50 bp, 72 bp) and long reads (> 100 bp) mappings; It also showed higher sensitivity towards mapping a complex genome like Plasmodium falciparum. The percentage of properly paired reads aligned by NovoAlign, BWA and Stampy were markedly higher. None of the aligners outperforms the others in the benchmark, however the aligners perform differently with genome characteristics. We expect that the results from this study will be useful for the end user to choose aligner, thus enhance the accuracy of read mapping. (C) 2017 Elsevier Inc. All rights reserved

EZH2 upregulates the PI3K/AKT pathway through IGF1R and MYC in clinically aggressive chronic lymphocytic leukaemia

EZH2 is overexpressed in poor-prognostic chronic lymphocytic leukaemia (CLL) cases, acting as an oncogene; however, thus far, the EZH2 target genes in CLL have not been disclosed. In this study, using ChIP-sequencing, we identified EZH2 and H3K27me3 target genes in two prognostic subgroups of CLL with distinct prognosis and outcome, i.e., cases with unmutated (U-CLL, n = 6) or mutated IGHV genes (M-CLL, n = 6). While the majority of oncogenic pathways were equally enriched for EZH2 target genes in both prognostic subgroups, PI3K pathway genes were differentially bound by EZH2 in U-CLL versus M-CLL. The occupancy of EZH2 for selected PI3K pathway target genes was validated in additional CLL samples (n = 16) and CLL cell lines using siRNA-mediated EZH2 downregulation and ChIP assays. Intriguingly, we found that EZH2 directly binds to the IGF1R promoter along with MYC and upregulates IGF1R expression in U-CLL, leading to downstream PI3K activation. By investigating an independent CLL cohort (n = 96), a positive correlation was observed between EZH2 and IGF1R expression with higher levels in U-CLL compared to M-CLL. Accordingly, siRNA-mediated downregulation of either EZH2, MYC or IGF1R and treatment with EZH2 and MYC pharmacological inhibitors in the HG3 CLL cell line induced a significant reduction in PI3K pathway activation. In conclusion, we characterize for the first time EZH2 target genes in CLL revealing a hitherto unknown implication of EZH2 in modulating the PI3K pathway in a non-canonical, PRC2-independent way, with potential therapeutic implications considering that PI3K inhibitors are effective therapeutic agents for CLL

Evaluation of Microsatellite instability score from GMS560 DNA panel

Microsatellite instability is characterised by gains or losses of nucleotides in short tandem repeat sequences, microsatellites, dispersed throughout the human genome. Microsatellite instability status is a molecular fingerprint for DNA mismatch repair deficiency. Clinical detection of microsatellite instability status is important for identifying inherited disease in patients with colorectal and endometrial cancer but has also a prognostic value for survival and prediction of treatment response. Lately, microsatellite instability has been used as a tumor agnostic biomarker that predicts response to immune checkpoint inhibitors. To identify microsatellite instability status clinically, PCR and immunohistochemistry have been the gold standard. On the contrary, next generation sequencing provide simultaneous accession of large number of microsatellite loci and can be combined with detection of several other biomarkers.  The national collaboration Genome Medicine Sweden have developed a solid tumour gene panel composed of 560 cancer associated genes with integrated microsatellite instability score. Our aim was to validate the microsatellite instability status based on microsatellite instability score from GMS560 DNA panel against the clinically used methods. Extracted DNA (100 ng) from formalin fixed paraffin embedded tissue sections with various tumour cell content >10% were analysed. During target enrichment sequencing analysis, allelic distribution from 5000 microsatellite markers were calculated by MSIsensor Pro to generate an instability score.  The cohort consisted of microsatellite instable verified colorectal cancer samples (n=20), microsatellite stable solid tumour material (n=60). Preliminary results generated a microsatellite instability score for the colorectal cancer samples with a mean of 26.5 % (CI: 23.4-29.6, range: 16.9-32.3). Microsatellite stable tumour samples had a mean microsatellite instability score of 1.5 % (CI: 0.93-2.07, range: 1-4.45).  In conclusion, we found the microsatellite instability score from GMS560 DNA panel to be both diagnostically sensitive and specific for determining MSI status due to obvious separation in instability.

Evaluation of Microsatellite instability score from GMS560 DNA panel

Microsatellite instability is characterised by gains or losses of nucleotides in short tandem repeat sequences, microsatellites, dispersed throughout the human genome. Microsatellite instability status is a molecular fingerprint for DNA mismatch repair deficiency. Clinical detection of microsatellite instability status is important for identifying inherited disease in patients with colorectal and endometrial cancer but has also a prognostic value for survival and prediction of treatment response. Lately, microsatellite instability has been used as a tumor agnostic biomarker that predicts response to immune checkpoint inhibitors. To identify microsatellite instability status clinically, PCR and immunohistochemistry have been the gold standard. On the contrary, next generation sequencing provide simultaneous accession of large number of microsatellite loci and can be combined with detection of several other biomarkers.  The national collaboration Genome Medicine Sweden have developed a solid tumour gene panel composed of 560 cancer associated genes with integrated microsatellite instability score. Our aim was to validate the microsatellite instability status based on microsatellite instability score from GMS560 DNA panel against the clinically used methods. Extracted DNA (100 ng) from formalin fixed paraffin embedded tissue sections with various tumour cell content >10% were analysed. During target enrichment sequencing analysis, allelic distribution from 5000 microsatellite markers were calculated by MSIsensor Pro to generate an instability score.  The cohort consisted of microsatellite instable verified colorectal cancer samples (n=20), microsatellite stable solid tumour material (n=60). Preliminary results generated a microsatellite instability score for the colorectal cancer samples with a mean of 26.5 % (CI: 23.4-29.6, range: 16.9-32.3). Microsatellite stable tumour samples had a mean microsatellite instability score of 1.5 % (CI: 0.93-2.07, range: 1-4.45).  In conclusion, we found the microsatellite instability score from GMS560 DNA panel to be both diagnostically sensitive and specific for determining MSI status due to obvious separation in instability.

Subcellular Distribution of p53 by the p53-Responsive lncRNA NBAT1 Determines Chemotherapeutic Response in Neuroblastoma

Neuroblastoma has a low mutation rate for the p53 gene. Alternative ways of p53 inactivation have been proposed in neuroblastoma, such as abnormal cytoplasmic accumulation of wildtype p53. However, mechanisms leading to p53 inactivation via cytoplasmic accumulation are not well investigated. Here we show that the neuroblastoma risk-associated locus 6p22.3-derived tumor suppressor NBAT1 is a p53-responsive lncRNA that regulates p53 subcellular levels. Low expression of NBAT1 provided resistance to genotoxic drugs by promoting p53 accumulation in cytoplasm and loss from mitochondrial and nuclear compartments. Depletion of NBAT1 altered CRM1 function and contributed to the loss of p53-dependent nuclear gene expression during genotoxic drug treatment. CRM1 inhibition rescued p53-dependent nuclear functions and sensitized NBAT1-depleted cells to genotoxic drugs. Combined inhibition of CRM1 and MDM2 was even more effective in sensitizing aggressive neuroblastoma cells with p53 cytoplasmic accumulation. Thus, our mechanistic studies uncover an NBAT1-dependent CRM1/MDM2-based potential combination therapy for patients with high-risk neuroblastoma. Significance: This study shows how a p53-responsive lncRNA mediates chemotherapeutic response by modulating nuclear p53 pathways and identifies a potential treatment strategy for patients with high-risk neuroblastoma