Search

Pancreatic acinar cell carcinoma (ACC) is a rare pancreatic neoplasm, often eluding clinicians because of the lack of diagnosis awareness and expert knowledge regarding clinical, radiological and pathological characteristics of ACC. Main differential diagnoses include pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine tumor (PNET) and accurate diagnosis is crucial to ensure optimal treatment and outcomes. This case of a 58-year old male illustrates the correlation between clinical, imaging, molecular histopathological and whole genome and transcriptome profiling that was required to diagnose and guide treatment of this complex pancreatic ACC.

Genetic variation modulates gene expression transcriptionally or post-transcriptionally, and can profoundly alter an individual's phenotype. Measuring allelic differential expression at heterozygous loci within an individual, a phenomenon called allele-specific expression (ASE), can assist in identifying such factors. Massively parallel DNA and RNA sequencing and advances in bioinformatic methodologies provide an outstanding opportunity to measure ASE genome-wide. In this study, matched DNA and RNA sequencing, genotyping arrays and computationally phased haplotypes were integrated to comprehensively and conservatively quantify ASE in a single human brain and liver tissue sample. We describe a methodological evaluation and assessment of common bioinformatic steps for ASE quantification, and recommend a robust approach to accurately measure SNP, gene and isoform ASE through the use of personalized haplotype genome alignment, strict alignment quality control and intragenic SNP aggregation. Our results indicate that accurate ASE quantification requires careful bioinformatic analyses and is adversely affected by sample specific alignment confounders and random sampling even at moderate sequence depths. We identified multiple known and several novel ASE genes in liver, including WDR72, DSP and UBD, as well as genes that contained ASE SNPs with imbalance direction discordant with haplotype phase, explainable by annotated transcript structure, suggesting isoform derived ASE. The methods evaluated in this study will be of use to researchers performing highly conservative quantification of ASE, and the genes and isoforms identified as ASE of interest to researchers studying those loci.

Protein prenylation is a widespread and highly conserved eukaryotic post-translational modification that endows proteins with the ability to reversibly attach to intracellular membranes. The dynamic interaction of prenylated proteins with intracellular membranes is essential for their signalling functions and is frequently deregulated in disease processes such as cancer. As a result, protein prenylation has been pharmacologically targeted by numerous drug discovery programs, albeit with limited success. To a large extent, this can be attributed to an insufficient understanding of the interplay of different protein prenyltransferases and the combinatorial diversity of the prenylatable sequence space. Here, we report a high-throughput, growth-based genetic selection assay in Saccharomyces cerevisiae based on the Ras Recruitment System which, for the first time, has allowed us to create a comprehensive map of prenylatable protein sequences in S. cerevisiae. We demonstrate that potential prenylatable space is sparsely (6.2%) occupied leaving room for creation of synthetic orthogonal prenylatable sequences. To experimentally demonstrate that, we used the developed platform to engineer mutant farnesyltransferases that efficiently prenylate substrate motives that are not recognised by endogenous protein prenyltransferases. These uncoupled mutants can now be used as starting points for the systematic engineering of the eukaryotic protein prenylation machinery.

Basal-like and triple negative breast cancer (TNBC) share common molecular features, poor prognosis and a propensity for metastasis to the brain. Amplification of epidermal growth factor receptor (EGFR) occurs in ~50% of basal-like breast cancer, and mutations in the epidermal growth factor receptor (EGFR) have been reported in up to ~ 10% of Asian TNBC patients. In non-small cell lung cancer several different mutations in the EGFR tyrosine kinase domain confer sensitivity to receptor tyrosine kinase inhibitors, but the tumourigenic potential of EGFR mutations in breast cells and their potential for targeted therapy is unknown.Constructs containing wild type, G719S or E746-A750 deletion mutant forms of EGFR were transfected into the MCF10A breast cells and their tumorigenic derivative, MCF10CA1a. The effects of EGFR over-expression and mutation on proliferation, migration, invasion, response to gefitinib, and tumour formation in vivo was investigated. Copy number analysis and whole exome sequencing of the MCF10A and MCF10CA1a cell lines were also performed.Mutant EGFR increased MCF10A and MCF10CA1a proliferation and MCF10A gefitinib sensitivity. The EGFR-E746-A750 deletion increased MCF10CA1a cell migration and invasion, and greatly increased MCF10CA1a xenograft tumour formation and growth. Compared to MCF10A cells, MCF10CA1a cells exhibited large regions of gain on chromosomes 3 and 9, deletion on chromosome 7, and mutations in many genes implicated in cancer.Mutant EGFR enhances the oncogenic properties of MCF10A cell line, and increases sensitivity to gefitinib. Although the addition of EGFR E746-A750 renders the MCF10CA1a cells more tumourigenic in vivo it is not accompanied by increased gefitinib sensitivity, perhaps due to additional mutations, including the PIK3CA H1047R mutation, that the MCF10CA1a cell line has acquired. Screening TNBC/basal-like breast cancer for EGFR mutations may prove useful for directing therapy but, as in non-small cell lung cancer, accompanying mutations in PIK3CA may confer gefitinib resistance.

mRNA synthesis, processing, and destruction involve a complex series of molecular steps that are incompletely understood. Because the RNA intermediates in each of these steps have finite lifetimes, extensive mechanistic and dynamical information is encoded in total cellular RNA. Here we report the development of SnapShot-Seq, a set of computational methods that allow the determination of in vivo rates of pre-mRNA synthesis, splicing, intron degradation, and mRNA decay from a single RNA-Seq snapshot of total cellular RNA. SnapShot-Seq can detect in vivo changes in the rates of specific steps of splicing, and it provides genome-wide estimates of pre-mRNA synthesis rates comparable to those obtained via labeling of newly synthesized RNA. We used SnapShot-Seq to investigate the origins of the intrinsic bimodality of metazoan gene expression levels, and our results suggest that this bimodality is partly due to spillover of transcriptional activation from highly expressed genes to their poorly expressed neighbors. SnapShot-Seq dramatically expands the information obtainable from a standard RNA-Seq experiment.

Leigh syndrome (LS) is a rare progressive multi-system neurodegenerative disorder, the genetics of which is frequently difficult to resolve. Rapid determination of the genetic etiology of LS in a 5-year-old girl facilitated inclusion in Edison Pharmaceutical's phase 2B clinical trial of EPI-743. SNP-arrays and high-coverage whole exome sequencing were performed on the proband, both parents and three unaffected siblings. Subsequent multi-tissue targeted high-depth mitochondrial sequencing was performed using custom long-range PCR amplicons. Tissue-specific mutant load was also assessed by qPCR. Complex I was interrogated by spectrophotometric enzyme assays and Western Blot. No putatively causal mutations were identified in nuclear-encoded genes. Analysis of low-coverage off-target mitochondrial reads revealed a previously unreported mitochondrial mutation in the proband in MT-ND3 (m.10134C>A, p.Q26K), a Complex I mitochondrial gene previously associated with LS. Targeted investigations demonstrated that this mutation was 1% heteroplasmic in the mother's blood and homoplasmic in the proband's blood, fibroblasts, liver and muscle. Enzyme assays revealed decreased Complex I activity. The identification of this novel LS MT-ND3 variant, the genomics of which was accomplished in less than 3.5 weeks, indicates that rapid genomic approaches may prove useful in time-sensitive cases with an unresolved genetic diagnosis.

Whole genome sequencing was used to characterize the resistome of intensive care unit (ICU) outbreak-associated carbapenem-resistant K. pneumoniae isolates. Importantly, and of particular concern, the carbapenem-hydrolyzing β-lactamase gene bla(OXA-48) and the extended-spectrum β-lactamase gene bla(CTX-M-14), were identified on a single broad host-range conjugative plasmid. This represents the first report of bla(OXA-48) in Australia and highlights the importance of resistance gene surveillance, as such plasmids can silently spread amongst enterobacterial populations and have the potential to drastically limit treatment options. Furthermore, the in vivo evolution of these isolates was also examined after 18 months of intra-abdominal carriage in a patient that transited through the ICU during the outbreak period. Reflecting the clonality of K. pneumoniae, only 11 single nucleotide polymorphisms (SNPs) were accumulated during this time-period and many of these were associated with genes involved in tolerance/resistance to antibiotics, metals or organic solvents, and transcriptional regulation. Collectively, these SNPs are likely to be associated with changes in virulence (at least to some extent) that have refined the in vivo colonization capacity of the original outbreak isolate.

Somatic mutation calling from next-generation sequencing data remains a challenge due to the difficulties of distinguishing true somatic events from artifacts arising from PCR, sequencing errors or mis-mapping. Tumor cellularity or purity, sub-clonality and copy number changes also confound the identification of true somatic events against a background of germline variants. We have developed a heuristic strategy and software (http://www.qcmg.org/bioinformatics/qsnp/) for somatic mutation calling in samples with low tumor content and we show the superior sensitivity and precision of our approach using a previously sequenced cell line, a series of tumor/normal admixtures, and 3,253 putative somatic SNVs verified on an orthogonal platform.

Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 ([Formula: see text]-value=0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 ([Formula: see text]-value [Formula: see text] 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 ([Formula: see text]-value=0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.

In contrast to the developing testis, molecular pathways driving fetal ovarian development have been difficult to characterise. To date no single master regulator of ovarian development has been identified that would be considered the female equivalent of Sry. Using a genomic approach we identified a number of novel protein-coding as well as non-coding genes that were detectable at higher levels in the ovary compared to testis during early mouse gonad development. We were able to cluster these ovarian genes into different temporal expression categories. Of note, Lrrc34 and AK015184 were detected in XX but not XY germ cells before the onset of sex-specific germ cell differentiation marked by entry into meiosis in an ovary and mitotic arrest in a testis. We also defined distinct spatial expression domains of somatic cell genes in the developing ovary. Our data expands the set of markers of early mouse ovary differentiation and identifies a classification of early ovarian genes, thus providing additional avenues with which to dissect this process.

The development of the mammalian kidney is well conserved from mouse to man. Despite considerable temporal and spatial data on gene expression in mammalian kidney development, primarily in rodent species, there is a paucity of genes whose expression is absolutely specific to a given anatomical compartment and/or developmental stage, defined here as 'anchor' genes. We previously generated an atlas of gene expression in the developing mouse kidney using microarray analysis of anatomical compartments collected via laser capture microdissection. Here, this data is further analysed to identify anchor genes via stringent bioinformatic filtering followed by high resolution section in situ hybridisation performed on 200 transcripts selected as specific to one of 11 anatomical compartments within the midgestation mouse kidney. A total of 37 anchor genes were identified across 6 compartments with the early proximal tubule being the compartment richest in anchor genes. Analysis of minimal and evolutionarily conserved promoter regions of this set of 25 anchor genes identified enrichment of transcription factor binding sites for Hnf4a and Hnf1b, RbpJ (Notch signalling), PPARγ:RxRA and COUP-TF family transcription factors. This was reinforced by GO analyses which also identified these anchor genes as targets in processes including epithelial proliferation and proximal tubular function. As well as defining anchor genes, this large scale validation of gene expression identified a further 92 compartment-enriched genes able to subcompartmentalise key processes during murine renal organogenesis spatially or ontologically. This included a cohort of 13 ureteric epithelial genes revealing previously unappreciated compartmentalisation of the collecting duct system and a series of early tubule genes suggesting that segmentation into proximal tubule, loop of Henle and distal tubule does not occur until the onset of glomerular vascularisation. Overall, this study serves to illuminate previously ill-defined stages of patterning and will enable further refinement of the lineage relationships within mammalian kidney development.

Many host-adapted bacterial pathogens contain DNA methyltransferases (mod genes) that are subject to phase-variable expression (high-frequency reversible ON/OFF switching of gene expression). In Haemophilus influenzae and pathogenic Neisseria, the random switching of the modA gene, associated with a phase-variable type III restriction modification (R-M) system, controls expression of a phase-variable regulon of genes (a "phasevarion"), via differential methylation of the genome in the modA ON and OFF states. Phase-variable type III R-M systems are also found in Helicobacter pylori, suggesting that phasevarions may also exist in this key human pathogen. Phylogenetic studies on the phase-variable type III modH gene revealed that there are 17 distinct alleles in H. pylori, which differ only in their DNA recognition domain. One of the most commonly found alleles was modH5 (16% of isolates). Microarray analysis comparing the wild-type P12modH5 ON strain to a P12ΔmodH5 mutant revealed that six genes were either up- or down-regulated, and some were virulence-associated. These included flaA, which encodes a flagella protein important in motility and hopG, an outer membrane protein essential for colonization and associated with gastric cancer. This study provides the first evidence of this epigenetic mechanism of gene expression in H. pylori. Characterisation of H. pylori modH phasevarions to define stable immunological targets will be essential for vaccine development and may also contribute to understanding H. pylori pathogenesis.

In response to the growing need for functional analysis of the human genome, we have developed a platform for high-throughput functional screening of genes overexpressed from lentiviral vectors. Protein-coding human open reading frames (ORFs) from the Mammalian Gene Collection were transferred into lentiviral expression vector using the highly efficient Gateway recombination cloning. Target ORFs were inserted into the vector downstream of a constitutive promoter and upstream of an IRES controlled GFP reporter, so that their transfection, transduction and expression could be monitored by fluorescence. The expression plasmids and viral packaging plasmids were combined and transfected into 293T cells to produce virus, which was then used to transduce the screening cell line. We have optimised the transfection and transduction procedures so that they can be performed using robotic liquid handling systems in arrayed 96-well microplate, one-gene-per-well format, without the need to concentrate the viral supernatant. Since lentiviruses can infect both dividing and non-dividing cells, this system can be used to overexpress human ORFs in a broad spectrum of experimental contexts. We tested the platform in a 1990 gene pilot screen for genes that can increase proliferation of the non-tumorigenic mammary epithelial cell line MCF-10A after removal of growth factors. Transduced cells were labelled with the nucleoside analogue 5-ethynyl-2'-deoxyuridine (EdU) to detect cells progressing through S phase. Hits were identified using high-content imaging and statistical analysis and confirmed with vectors using two different promoters (CMV and EF1α). The screen demonstrates the reliability, versatility and utility of our screening platform, and identifies novel cell cycle/proliferative activities for a number of genes.

A large number of rare sequence variants of unknown clinical significance have been identified in the breast cancer susceptibility genes, BRCA1 and BRCA2. Laboratory-based methods that can distinguish between carriers of pathogenic mutations and non-carriers are likely to have utility for the classification of these sequence variants. To identify predictors of pathogenic mutation status in familial breast cancer patients, we explored the use of gene expression arrays to assess the effect of two DNA-damaging agents (irradiation and mitomycin C) on cellular response in relation to BRCA1 and BRCA2 mutation status. A range of regimes was used to treat 27 lymphoblastoid cell-lines (LCLs) derived from affected women in high-risk breast cancer families (nine BRCA1, nine BRCA2, and nine non-BRCA1/2 or BRCAX individuals) and nine LCLs from healthy individuals. Using an RNA-pooling strategy, we found that treating LCLs with 1.2 microM mitomycin C and measuring the gene expression profiles 1 hour post-treatment had the greatest potential to discriminate BRCA1, BRCA2, and BRCAX mutation status. A classifier was built using the expression profile of nine QRT-PCR validated genes that were associated with BRCA1, BRCA2, and BRCAX status in RNA pools. These nine genes could distinguish BRCA1 from BRCA2 carriers with 83% accuracy in individual samples, but three-way analysis for BRCA1, BRCA2, and BRCAX had a maximum of 59% prediction accuracy. Our results suggest that, compared to BRCA1 and BRCA2 mutation carriers, non-BRCA1/2 (BRCAX) individuals are genetically heterogeneous. This study also demonstrates the effectiveness of RNA pools to compare the expression profiles of cell-lines from BRCA1, BRCA2, and BRCAX cases after treatment with irradiation and mitomycin C as a method to prioritize treatment regimes for detailed downstream expression analysis.

Transcriptional regulation by microRNAs (miRNAs) involves complementary base-pairing at target sites on mRNAs, yielding complex secondary structures. Here we introduce an efficient computational approach and software (FASTH) for genome-scale prediction of miRNA target sites based on minimizing the free energy of duplex structure. We apply our approach to identify miRNA target sites in the human and mouse transcriptomes. Our results show that short sequence motifs in the 5' end of miRNAs frequently match mRNAs perfectly, not only at validated target sites but additionally at many other, energetically favourable sites. High-quality matching regions are abundant and occur at similar frequencies in all mRNA regions, not only the 3'UTR. About one-third of potential miRNA target sites are reassigned to different mRNA regions, or gained or lost altogether, among different transcript isoforms from the same gene. Many potential miRNA target sites predicted in human are not found in mouse, and vice-versa, but among those that do occur in orthologous human and mouse mRNAs most are situated in corresponding mRNA regions, i.e. these sites are themselves orthologous. Using a luciferase assay in HEK293 cells, we validate four of six predicted miRNA-mRNA interactions, with the mRNA level reduced by an average of 73%. We demonstrate that a thermodynamically based computational approach to prediction of miRNA binding sites on mRNAs can be scaled to analyse complete mammalian transcriptome datasets. These results confirm and extend the scope of miRNA-mediated species- and transcript-specific regulation in different cell types, tissues and developmental conditions.

Many host-adapted bacterial pathogens contain DNA methyltransferases (mod genes) that are subject to phase-variable expression (high-frequency reversible ON/OFF switching of gene expression). In Haemophilus influenzae, the random switching of the modA gene controls expression of a phase-variable regulon of genes (a "phasevarion"), via differential methylation of the genome in the modA ON and OFF states. Phase-variable mod genes are also present in Neisseria meningitidis and Neisseria gonorrhoeae, suggesting that phasevarions may occur in these important human pathogens. Phylogenetic studies on phase-variable mod genes associated with type III restriction modification (R-M) systems revealed that these organisms have two distinct mod genes--modA and modB. There are also distinct alleles of modA (abundant: modA11, 12, 13; minor: modA4, 15, 18) and modB (modB1, 2). These alleles differ only in their DNA recognition domain. ModA11 was only found in N. meningitidis and modA13 only in N. gonorrhoeae. The recognition site for the modA13 methyltransferase in N. gonorrhoeae strain FA1090 was identified as 5'-AGAAA-3'. Mutant strains lacking the modA11, 12 or 13 genes were made in N. meningitidis and N. gonorrhoeae and their phenotype analyzed in comparison to a corresponding mod ON wild-type strain. Microarray analysis revealed that in all three modA alleles multiple genes were either upregulated or downregulated, some of which were virulence-associated. For example, in N. meningitidis MC58 (modA11), differentially expressed genes included those encoding the candidate vaccine antigens lactoferrin binding proteins A and B. Functional studies using N. gonorrhoeae FA1090 and the clinical isolate O1G1370 confirmed that modA13 ON and OFF strains have distinct phenotypes in antimicrobial resistance, in a primary human cervical epithelial cell model of infection, and in biofilm formation. This study, in conjunction with our previous work in H. influenzae, indicates that phasevarions may be a common strategy used by host-adapted bacterial pathogens to randomly switch between "differentiated" cell types.

Short proteins play key roles in cell signalling and other processes, but their abundance in the mammalian proteome is unknown. Current catalogues of mammalian proteins exhibit an artefactual discontinuity at a length of 100 aa, so that protein abundance peaks just above this length and falls off sharply below it. To clarify the abundance of short proteins, we identify proteins in the FANTOM collection of mouse cDNAs by analysing synonymous and non-synonymous substitutions with the computer program CRITICA. This analysis confirms that there is no real discontinuity at length 100. Roughly 10% of mouse proteins are shorter than 100 aa, although the majority of these are variants of proteins longer than 100 aa. We identify many novel short proteins, including a "dark matter" subset containing ones that lack detectable homology to other known proteins. Translation assays confirm that some of these novel proteins can be translated and localised to the secretory pathway.