The Gram-negative bacterium Burkholderia pseudomallei is the causative agent of melioidosis, a serious infectious disease of humans and animals. Once considered an esoteric tropical disease confined to Southeast Asia and northern Australia, research on B. pseudomallei has recently gained global prominence due to its classification as a potential bioterrorism agent by countries such as the United States and also by increasing numbers of case reports from regions where it is not endemic. An environmental bacterium typically found in soil and water, assessing the true global prevalence of melioidosis is challenged by the fact that clinical symptoms associated with B. pseudomallei infection are extremely varied and may be confused with diverse conditions such as lung cancer, tuberculosis, or Staphyloccocus aureus infection. These diagnostic challenges, coupled with lack of awareness among clinicians, have likely contributed to underdiagnosis and the high mortality rate of melioidosis, as initial treatment is often either inappropriate or delayed. Even after antibiotic treatment, relapses are frequent, and after resolution of acute symptoms, chronic melioidosis can also occur, and the symptoms can persist for months to years. In a recent article, Price et al. [mBio 4(4):e00388-13, 2013, doi:10.1128/mBio.00388-13] demonstrate how comparative genomic sequencing can reveal the repertoire of genetic changes incurred by B. pseudomallei during chronic human infection. Their results have significant clinical ramifications and highlight B. pseudomallei’s ability to survive in a wide range of potential niches within hosts, through the acquisition of genetic adaptations that optimize fitness and resource utilization.
Burkholderia pseudomallei (Bp), the causative agent of the often-deadly infectious disease melioidosis, contains one of the largest prokaryotic genomes sequenced to date, at 7.2 Mb with two large circular chromosomes (1 and 2). To comprehensively delineate the Bp transcriptome, we integrated whole-genome tiling array expression data of Bp exposed to >80 diverse physical, chemical, and biological conditions. Our results provide direct experimental support for the strand-specific expression of 5,467 Sanger protein-coding genes, 1,041 operons, and 766 non-coding RNAs. A large proportion of these transcripts displayed condition-dependent expression, consistent with them playing functional roles. The two Bp chromosomes exhibited dramatically different transcriptional landscapes — Chr 1 genes were highly and constitutively expressed, while Chr 2 genes exhibited mosaic expression where distinct subsets were expressed in a strongly condition-dependent manner. We identified dozens of cis-regulatory motifs associated with specific condition-dependent expression programs, and used the condition compendium to elucidate key biological processes associated with two complex pathogen phenotypes — quorum sensing and in vivo infection. Our results demonstrate the utility of a Bp condition-compendium as a community resource for biological discovery. Moreover, the observation that significant portions of the Bp virulence machinery can be activated by specific in vitro cues provides insights into Bp's capacity as an “accidental pathogen”, where genetic pathways used by the bacterium to survive in environmental niches may have also facilitated its ability to colonize human hosts.
Bacterial transcriptomes are dynamic, context-specific and condition-dependent. Infection by the soil bacterium, Burkholderia pseudomallei, causes melioidosis, an often fatal infectious disease of humans and animals. Possessing a large multi-chromosomal genome, B. pseudomallei is able to persist and survive in a multitude of environments. To obtain a comprehensive overview of B. pseudomallei expressed transcripts, we initiated whole-genome transcriptome profiling covering a broad spectrum of conditions and exposures — a so-called “condition compendium”. Using the compendium, we confirmed many previously-annotated genes and operons, and also identified hundreds of novel transcripts including anti-sense transcripts and non-coding RNAs. By systematically examining genes exhibiting highly similar expression patterns, we ascribed putative functions to previously uncharacterized genes, and identified novel regulatory elements controlling these expression patterns. We also used the compendium to elucidate candidate virulence pathways associated with quorum-sensing and infection in mice. Our study showcases the power of a B. pseudomallei condition compendium as a valuable resource for understanding microbial physiology and the pathogenesis of melioidosis.
Emerging resistance to current antibiotics raises the need for new microbial drug targets. We show that targeting branched-chain amino acid (BCAA) biosynthesis using sulfonylurea herbicides, which inhibit the BCAA biosynthetic enzyme acetohydroxyacid synthase (AHAS), can exert bacteriostatic effects on several pathogenic bacteria, including Burkholderia pseudomallei, Pseudomonas aeruginosa, and Acinetobacter baumannii. Our results suggest that targeting biosynthetic enzymes like AHAS, which are lacking in humans, could represent a promising antimicrobial drug strategy.
Neuroblastoma is a pediatric cancer of the peripheral nervous system in which structural chromosome aberrations are emblematic of aggressive tumors. In this study, we performed an in-depth analysis of somatic rearrangements in two neuroblastoma cell lines and two primary tumors using paired-end sequencing of mate-pair libraries and RNA-seq. The cell lines presented with typical genetic alterations of neuroblastoma and the two tumors belong to the group of neuroblastoma exhibiting a profile of chromothripsis. Inter and intra-chromosomal rearrangements were identified in the four samples, allowing in particular characterization of unbalanced translocations at high resolution. Using complementary experiments, we further characterized 51 rearrangements at the base pair resolution that revealed 59 DNA junctions. In a subset of cases, complex rearrangements were observed with templated insertion of fragments of nearby sequences. Although we did not identify known particular motifs in the local environment of the breakpoints, we documented frequent microhomologies at the junctions in both chromothripsis and non-chromothripsis associated breakpoints. RNA-seq experiments confirmed expression of several predicted chimeric genes and genes with disrupted exon structure including ALK, NBAS, FHIT, PTPRD and ODZ4. Our study therefore indicates that both non-homologous end joining-mediated repair and replicative processes may account for genomic rearrangements in neuroblastoma. RNA-seq analysis allows the identification of the subset of abnormal transcripts expressed from genomic rearrangements that may be involved in neuroblastoma oncogenesis.
Genetic alterations in kinases have been linked to multiple human pathologies. To explore the landscape of kinase genetic variation in gastric cancer (GC), we used targeted, paired-end deep sequencing to analyze 532 protein and phosphoinositide kinases in 14 GC cell lines. We identified 10,604 single-nucleotide variants (SNV) in kinase exons including greater than 300 novel nonsynonymous SNVs. Family-wise analysis of the nonsynonymous SNVs revealed a significant enrichment in mitogen-activated protein kinase (MAPK)-related genes (P < 0.01), suggesting a preferential involvement of this kinase family in GC. A potential antioncogenic role for MAP2K4, a gene exhibiting recurrent alterations in 2 lines, was functionally supported by siRNA knockdown and overexpression studies in wild-type and MAP2K4 variant lines. The deep sequencing data also revealed novel, large-scale structural rearrangement events involving kinases including gene fusions involving CDK12 and the ERBB2 receptor tyrosine kinase in MKN7 cells. Integrating SNVs and copy number alterations, we identified Hs746T as a cell line exhibiting both splice-site mutations and genomic amplification of MET, resulting in MET protein overexpression. When applied to primary GCs, we identified somatic mutations in 8 kinases, 4 of which were recurrently altered in both primary tumors and cell lines (MAP3K6, STK31, FER, and CDKL5). These results demonstrate that how targeted deep sequencing approaches can deliver unprecedented multilevel characterization of a medically and pharmacologically relevant gene family. The catalog of kinome genetic variants assembled here may broaden our knowledge on kinases and provide useful information on genetic alterations in GC.
Ultra-deep pyrosequencing (UDPS) is used to identify rare sequence variants. The sequence depth is influenced by several factors including the error frequency of PCR and UDPS. This study investigated the characteristics and source of errors in raw and cleaned UDPS data.
UDPS of a 167-nucleotide fragment of the HIV-1 SG3Δenv plasmid was performed on the Roche/454 platform. The plasmid was diluted to one copy, PCR amplified and subjected to bidirectional UDPS on three occasions. The dataset consisted of 47,693 UDPS reads. Raw UDPS data had an average error frequency of 0.30% per nucleotide site. Most errors were insertions and deletions in homopolymeric regions. We used a cleaning strategy that removed almost all indel errors, but had little effect on substitution errors, which reduced the error frequency to 0.056% per nucleotide. In cleaned data the error frequency was similar in homopolymeric and non-homopolymeric regions, but varied considerably across sites. These site-specific error frequencies were moderately, but still significantly, correlated between runs (r = 0.15–0.65) and between forward and reverse sequencing directions within runs (r = 0.33–0.65). Furthermore, transition errors were 48-times more common than transversion errors (0.052% vs. 0.001%; p<0.0001). Collectively the results indicate that a considerable proportion of the sequencing errors that remained after data cleaning were generated during the PCR that preceded UDPS.
A majority of the sequencing errors that remained after data cleaning were introduced by PCR prior to sequencing, which means that they will be independent of platform used for next-generation sequencing. The transition vs. transversion error bias in cleaned UDPS data will influence the detection limits of rare mutations and sequence variants.
A major goal of cancer genome sequencing is to identify mutations or other somatic alterations that can be targeted by selective and specific drugs. dGene is an annotation tool designed to rapidly identify genes belonging to one of ten druggable classes that are frequently targeted in cancer drug development. These classes were comprehensively populated by combining and manually curating data from multiple specialized and general databases. dGene was used by The Cancer Genome Atlas squamous cell lung cancer project, and here we further demonstrate its utility using recently released breast cancer genome sequencing data. dGene is designed to be usable by any cancer researcher without the need for support from a bioinformatics specialist. A full description of dGene and options for its implementation are provided here.
To profile RNA expression in gastric cancer by anatomic subsites as an initial step in identifying molecular subtypes and providing targets for early detection and therapy.
We performed transcriptome analysis using the Affymetrix GeneChip U133A in gastric cardia adenocarcinomas (n = 62) and gastric noncardia adenocarcinomas (n = 72) and their matched normal tissues from patients in Shanxi Province, and validated selected dysregulated genes with additional RNA studies. Expression of dysregulated genes was also related to survival of cases.
Principal Component Analysis showed that samples clustered by tumor vs. normal, anatomic location, and histopathologic features. Paired t-tests of tumor/normal tissues identified 511 genes whose expression was dysregulated (P<4.7E-07 and at least two-fold difference in magnitude) in cardia or noncardia gastric cancers, including nearly one-half (n = 239, 47%) dysregulated in both cardia and noncardia, one-fourth dysregulated in cardia only (n = 128, 25%), and about one-fourth in noncardia only (n = 144, 28%). Additional RNA studies confirmed profiling results. Expression was associated with case survival for 20 genes in cardia and 36 genes in noncardia gastric cancers.
The dysregulated genes identified here represent a comprehensive starting point for future efforts to understand etiologic heterogeneity, develop diagnostic biomarkers for early detection, and test molecularly-targeted therapies for gastric cancer.
Although several prognostic genomic predictors have been identified from independent studies, it remains unclear whether these predictors are actually concordant with respect to their predictions for individual patients and which predictor performs best. We compared five prognostic genomic predictors, the V7RHS, the ColoGuideEx, the Meta163, the OncoDX, and the MDA114, in terms of predicting disease-free survival in two independent cohorts of patients with colorectal cancer.
Using original classification algorithms, we tested the predictions of five genomic predictors for disease-free survival in two cohorts of patients with colorectal cancer (n = 229 and n = 168) and evaluated concordance of predictors in predicting outcomes for individual patients.
We found that only two predictors, OncoDX and MDA114, demonstrated robust performance in identifying patients with poor prognosis in 2 independent cohorts. These two predictors also had modest but significant concordance of predicted outcome (r>0.3, P<0.001 in both cohorts).
Further validation of developed genomic predictors is necessary. Despite the limited number of genes shared by OncoDX and MDA114, individual-patient outcomes predicted by these two predictors were significantly concordant.
Dengue viruses 1–4 (DENV1-4) rely heavily on the host cell machinery to complete their life cycle, while at the same time evade the host response that could restrict their replication efficiency. These requirements may account for much of the broad gene-level changes to the host transcriptome upon DENV infection. However, host gene function is also regulated through transcriptional start site (TSS) selection and post-transcriptional modification to the RNA that give rise to multiple gene isoforms. The roles these processes play in the host response to dengue infection have not been explored. In the present study, we utilized RNA sequencing (RNAseq) to identify novel transcript variations in response to infection with both a pathogenic strain of DENV1 and its attenuated derivative. RNAseq provides the information necessary to distinguish the various isoforms produced from a single gene and their splice variants. Our data indicate that there is an extensive amount of previously uncharacterized TSS and post-transcriptional modifications to host RNA over a wide range of pathways and host functions in response to DENV infection. Many of the differentially expressed genes identified in this study have previously been shown to be required for flavivirus propagation and/or interact with DENV gene products. We also show here that the human transcriptome response to an infection by wild-type DENV or its attenuated derivative differs significantly. This differential response to wild-type and attenuated DENV infection suggests that alternative processing events may be part of a previously uncharacterized innate immune response to viral infection that is in large part evaded by wild-type DENV.
Dengue is the most common insect-borne viral disease globally. The continued absence of an effective therapy stems from an incomplete understanding of disease pathogenesis, of which the host response to infection is thought to play a central role. While previous studies have described the changes in total gene expression with dengue virus infection, they have not been able to provide any information on the subtle variations of the host RNA. These variations lead to the production of gene isoforms that can have a profound effect on gene function. In the current study, we have used the newly developed technique of RNA sequencing to more accurately interrogate the variations in the host RNA after infection with a wild-type dengue virus or its attenuated derivative. Findings from this study show that there is an extensive amount of previously uncharacterized variation in host RNA response to dengue infection. The response to infection with the wild-type dengue also differs significantly from infection with the vaccine strain. This suggests that variations in the host RNA comprise a part of the host response to viral infection that is in large part evaded by wild-type dengue viruses.
Gastrointestinal cancers are frequently associated with chronic inflammation and
excessive secretion of IL-6 family cytokines, which promote tumorigenesis through
persistent activation of the GP130/JAK/STAT3 pathway. Although tumor progression can
be prevented by genetic ablation of Stat3 in mice, this
transcription factor remains a challenging therapeutic target with a paucity of
clinically approved inhibitors. Here, we uncovered parallel and excessive activation
of mTOR complex 1 (mTORC1) alongside STAT3 in human intestinal-type gastric cancers
(IGCs). Furthermore, in a preclinical mouse model of IGC, GP130 ligand administration
simultaneously activated mTORC1/S6 kinase and STAT3 signaling. We therefore
investigated whether mTORC1 activation was required for inflammation-associated
gastrointestinal tumorigenesis. Strikingly, the mTORC1-specific inhibitor RAD001
potently suppressed initiation and progression of both murine IGC and
colitis-associated colon cancer. The therapeutic effect of RAD001 was associated with
reduced tumor vascularization and cell proliferation but occurred independently of
STAT3 activity. We analyzed the mechanism of GP130-mediated mTORC1 activation in
cells and mice and revealed a requirement for JAK and PI3K activity but not for GP130
tyrosine phosphorylation or STAT3. Our results suggest that GP130-dependent
activation of the druggable PI3K/mTORC1 pathway is required for
inflammation-associated gastrointestinal tumorigenesis. These findings advocate
clinical application of PI3K/mTORC1 inhibitors for the treatment of corresponding
The US Public Health Emergency Medical Countermeasures Enterprise convened subject matter experts at the 2010 HHS Burkholderia Workshop to develop consensus recommendations for postexposure prophylaxis against and treatment for Burkholderia pseudomallei and B. mallei infections, which cause melioidosis and glanders, respectively. Drugs recommended by consensus of the participants are ceftazidime or meropenem for initial intensive therapy, and trimethoprim/sulfamethoxazole or amoxicillin/clavulanic acid for eradication therapy. For postexposure prophylaxis, recommended drugs are trimethoprim/sulfamethoxazole or co-amoxiclav. To improve the timely diagnosis of melioidosis and glanders, further development and wide distribution of rapid diagnostic assays were also recommended. Standardized animal models and B. pseudomallei strains are needed for further development of therapeutic options. Training for laboratory technicians and physicians would facilitate better diagnosis and treatment options.
Burkholderia pseudomallei; melioidosis; Burkholderia mallei; glanders; drug therapy; postexposure prophylaxis; ceftazidime; carbapenems; trimethoprim/sulfamethoxazole; combination; amoxicillin/potassium clavulanate; clavulanic acid bacteria; antibiotic; antibacterial drugs; antimicrobial drugs; bacteria; Suggested citation for this article: Lipsitz R; Garges S; Aurigemma R; Baccam P; Blaney DD; Cheng AC; et al. Workshop on treatment of and postexposure prophylaxis for Burkholderia pseudomallei and B. mallei infection; 2010. Emerg Infect Dis [Internet]. 2012 Dec [date cited]. http://dx.doi.org/10.3201/eid1812.120638
Defining the architecture of a specific cancer genome, including its structural variants, is essential for understanding tumor biology, mechanisms of oncogenesis, and for designing effective personalized therapies. Short read paired-end sequencing is currently the most sensitive method for detecting somatic mutations that arise during tumor development. However, mapping structural variants using this method leads to a large number of false positive calls, mostly due to the repetitive nature of the genome and the difficulty of assigning correct mapping positions to short reads. This study describes a method to efficiently identify large tumor-specific deletions, inversions, duplications and translocations from low coverage data using SVDetect or BreakDancer software and a set of novel filtering procedures designed to reduce false positive calls. Applying our method to a spontaneous T cell lymphoma arising in a core RAG2/p53-deficient mouse, we identified 40 validated tumor-specific structural rearrangements supported by as few as 2 independent read pairs.
Regional genomic copy number alterations (CNA) are observed in the vast majority of cancers. Besides specifically targeting well-known, canonical oncogenes, CNAs may also play more subtle roles in terms of modulating genetic potential and broad gene expression patterns of developing tumors. Any significant differences in the overall CNA patterns between different cancer types may thus point towards specific biological mechanisms acting in those cancers. In addition, differences among CNA profiles may prove valuable for cancer classifications beyond existing annotation systems.
We have analyzed molecular-cytogenetic data from 25579 tumors samples, which were classified into 160 cancer types according to the International Classification of Disease (ICD) coding system. When correcting for differences in the overall CNA frequencies between cancer types, related cancers were often found to cluster together according to similarities in their CNA profiles. Based on a randomization approach, distance measures from the cluster dendrograms were used to identify those specific genomic regions that contributed significantly to this signal. This approach identified 43 non-neutral genomic regions whose propensity for the occurrence of copy number alterations varied with the type of cancer at hand. Only a subset of these identified loci overlapped with previously implied, highly recurrent (hot-spot) cytogenetic imbalance regions.
Thus, for many genomic regions, a simple null-hypothesis of independence between cancer type and relative copy number alteration frequency can be rejected. Since a subset of these regions display relatively low overall CNA frequencies, they may point towards second-tier genomic targets that are adaptively relevant but not necessarily essential for cancer development.
Although genome-wide transcriptional analysis has been used for many years to study bacterial gene expression, many aspects of the bacterial transcriptome remain undefined. One example is antisense transcription, which has been observed in a number of bacteria, though the function of antisense transcripts, and their distribution across the bacterial genome, is still unclear.
Single-stranded RNA-seq results revealed a widespread and non-random pattern of antisense transcription covering more than two thirds of the B. anthracis genome. Our analysis revealed a variety of antisense structural patterns, suggesting multiple mechanisms of antisense transcription. The data revealed several instances of sense and antisense expression changes in different growth conditions, suggesting that antisense transcription may play a role in the ways in which B. anthracis responds to its environment. Significantly, genome-wide antisense expression occurred at consistently higher levels on the lagging strand, while the leading strand showed very little antisense activity. Intrasample gene expression comparisons revealed a gene dosage effect in all growth conditions, where genes farthest from the origin showed the lowest overall range of expression for both sense and antisense directed transcription. Additionally, transcription from both strands was verified using a novel strand-specific assay. The variety of structural patterns we observed in antisense transcription suggests multiple mechanisms for this phenomenon, suggesting that some antisense transcription may play a role in regulating the expression of key genes, while some may be due to chromosome replication dynamics and transcriptional noise.
Although the variety of structural patterns we observed in antisense transcription suggest multiple mechanisms for antisense expression, our data also clearly indicate that antisense transcription may play a genome-wide role in regulating the expression of key genes in Bacillus species. This study illustrates the surprising complexity of prokaryotic RNA abundance for both strands of a bacterial chromosome.
While there is strong evidence for phosphatidylinositol 3-kinase (PI3K) involvement in cancer development, there is limited information about the role of PI3K regulatory subunits. PIK3R3, the gene that encodes the PI3K regulatory subunit p55γ, is over-expressed in glioblastoma and ovarian cancers, but its expression in gastric cancer (GC) is not known. We thus used genetic and bioinformatic approaches to examine PIK3R3 expression and function in GC, the second leading cause of cancer mortality world-wide and highly prevalent among Asians.
Primary GC and matched non-neoplastic mucosa tissue specimens from a unique Asian patient gastric cancer library were comprehensively profiled with platforms that measured genome-wide mRNA expression, DNA copy number variation, and DNA methylation status. Function of PIK3R3 was predicted by IPA pathway analysis of co-regulated genes with PIK3R3, and further investigated by siRNA knockdown studies. Cell proliferation was estimated by crystal violet dye elution and BrdU incorporation assay. Cell cycle distribution was analysed by FACS.
PIK3R3 was significantly up-regulated in GC specimens (n = 126, p < 0.05), and 9.5 to 15% tumors showed more than 2 fold increase compare to the paired mucosa tissues. IPA pathway analysis showed that PIK3R3 promoted cellular growth and proliferation. Knockdown of PIK3R3 decreased the growth of GC cells, induced G0/G1 cell cycle arrest, decreased retinoblastoma protein (Rb) phosphorylation, cyclin D1, and PCNA expression.
Using a combination of genetic, bioinformatic, and molecular biological approaches, we showed that PIK3R3 was up-regulated in GC and promoted cell cycle progression and proliferation; and thus may be a potential new therapeutic target for GC.
BACKGROUND & AIMS
Gastric cancer (GC) is a heterogeneous disease comprising multiple subtypes that each have distinct biological properties and effects in patients. We sought to identify new, intrinsic subtypes of GC by gene expression analysis of a large panel of GC cell lines. We tested if these subtypes might be associated with differences patient survival times and responses to various standard-of-care cytotoxic drugs.
We analyzed gene expression profiles for 37 GC cell lines to identify intrinsic GC subtypes. These subtypes were validated in primary tumors from 521 patients in 4 independent cohorts, where the subtypes were determined by either expression profiling or subtype-specific immunohistochemical markers (LGALS4, CDH17). In vitro sensitivity to 3 chemotherapy drugs (5-FU, cisplatin, oxaliplatin) was also assessed.
Unsupervised cell line analysis identified 2 major intrinsic genomic subtypes (G-INT and G-DIF), that had distinct patterns of gene expression. The intrinsic subtypes, but not subtypes based on Lauren’s histopathologic classification, were prognostic of survival, based on univariate and multivariate analysis in multiple patient cohorts. The G-INT cell lines were significantly more sensitive to 5-FU and oxaliplatin, but more resistant to cisplatin, than the G-DIF cell lines. In patients, intrinsic subtypes were associated with survival time following adjuvant, 5-FU based therapy.
Intrinsic subtypes of GC, based on distinct patterns of expression, are associated with patient survival and response to chemotherapy. Classification of GC based on intrinsic subtypes might be used to determine prognosis and customize therapy.
Microarray analysis; pharmacogenomics; mRNA; stomach; carcinogenesis
The ARID1A gene encodes adenine-thymine (AT)-rich interactive domain-containing protein 1A, which participates in chromatin remodeling. ARID1A has been showed to function as a tumor suppressor in various cancer types. In the current study, we investigated the expression and prognosis value of ARID1A in primary gastric cancer. Meanwhile, the biological role of ARID1A was further investigated using cell model in vitro.
To investigate the role of ARID1A gene in primary gastric cancer pathogenesis, real-time quantitative PCR and western blotting were used to examine the ARID1A expression in paired cancerous and noncancerous tissues. Results revealed decreased ARID1A mRNA (P = 0.0029) and protein (P = 0.0015) expression in most tumor-bearing tissues compared with the matched adjacent non-tumor tissues, and in gastric cancer cell lines. To further investigate the clinicopathological and prognostic roles of ARID1A expression, we performed immunohistochemical analyses of the 224 paraffin-embedded gastric cancer tissue blocks. Data revealed that the loss of ARID1A expression was significantly correlated with T stage (P = 0.001) and grade (P = 0.006). Consistent with these results, we found that loss of ARID1A expression was significantly correlated with poor survival in gastric cancer patients (P = 0.003). Cox regression analyses showed that ARID1A expression was an independent predictor of overall survival (P = 0.029). Furthermore, the functions of ARID1A in the proliferation and colony formation of gastric cell lines were analyzed by transfecting cells with full-length ARID1A expression vector or siRNA targeting ARID1A. Restoring ARID1A expression in gastric cancer cells significantly inhibited cell proliferation and colony formation. Silencing ARID1A expression in gastric epithelial cell line significantly enhanced cell growth rate.
Our data suggest that ARID1A may play an important role in gastric cancer and may serve as a valuable prognostic marker and potential target for gene therapy in the treatment of gastric cancer.
Breast cancer outcome can be predicted using models derived from gene expression data or clinical data. Only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. We rigorously compare three different integration strategies (early, intermediate, and late integration) as well as classifiers employing no integration (only one data type) using five classifiers of varying complexity. We perform our analysis on a set of 295 breast cancer samples, for which gene expression data and an extensive set of clinical parameters are available as well as four breast cancer datasets containing 521 samples that we used as independent validation.mOn the 295 samples, a nearest mean classifier employing a logical OR operation (late integration) on clinical and expression classifiers significantly outperforms all other classifiers. Moreover, regardless of the integration strategy, the nearest mean classifier achieves the best performance. All five classifiers achieve their best performance when integrating clinical and expression data. Repeating the experiments using the 521 samples from the four independent validation datasets also indicated a significant performance improvement when integrating clinical and gene expression data. Whether integration also improves performances on other datasets (e.g. other tumor types) has not been investigated, but seems worthwhile pursuing. Our work suggests that future models for predicting breast cancer outcome should exploit both data types by employing a late OR or intermediate integration strategy based on nearest mean classifiers.
The structure of BPSL1549, a protein of unknown function from Burkholderia pseudomallei reveals a similarity to E. coli cytotoxic necrotizing factor 1. We found that BPSL1549 acted as a potent cytotoxin against eukaryotic cells and was lethal when administered to mice. Expression levels of bpsl1549 correlate with conditions expected to promote or suppress pathogenicity. BPSL1549 promotes deamidation of Gln339 of the translation initiation factor eIF4A, abolishing its helicase activity and inhibiting translation. We propose to name BPSL1549 Burkholderia Lethal Factor 1 (BLF1).
The bacterium Burkholderia pseudomallei causes melioidosis, a rare but serious illness that can be fatal if untreated or misdiagnosed. Species-specific PCR assays provide a technically simple method for differentiating B. pseudomallei from near-neighbor species. However, substantial genetic diversity and high levels of recombination within this species reduce the likelihood that molecular signatures will differentiate all B. pseudomallei from other Burkholderiaceae. Currently available molecular assays for B. pseudomallei detection lack rigorous validation across large in silico datasets and isolate collections to test for specificity, and none have been subjected to stringent quality control criteria (accuracy, precision, selectivity, limit of quantitation (LoQ), limit of detection (LoD), linearity, ruggedness and robustness) to determine their suitability for environmental, clinical or forensic investigations. In this study, we developed two novel B. pseudomallei specific assays, 122018 and 266152, using a dual-probe approach to differentiate B. pseudomallei from B. thailandensis, B. oklahomensis and B. thailandensis-like species; other species failed to amplify. Species specificity was validated across a large DNA panel (>2,300 samples) comprising Burkholderia spp. and non-Burkholderia bacterial and fungal species of clinical and environmental relevance. Comparison of assay specificity to two previously published B. pseudomallei-specific assays, BurkDiff and TTS1, demonstrated comparable performance of all assays, providing between 99.7 and 100% specificity against our isolate panel. Last, we subjected 122018 and 266152 to rigorous quality control analyses, thus providing quantitative limits of assay performance. Using B. pseudomallei as a model, our study provides a framework for comprehensive quantitative validation of molecular assays and provides additional, highly validated B. pseudomallei assays for the scientific research community.
Small sample sizes used in previous studies result in a lack of overlap between the reported gene signatures for prediction of chemotherapy response. Although morphologic features, especially tumor nuclear morphology, are important for cancer grading, little research has been reported on quantitatively correlating cellular morphology with chemotherapy response, especially in a large data set. In this study, we have used a large population of patients to identify molecular and morphologic signatures associated with chemotherapy response in serous ovarian carcinoma.
A gene expression model that predicts response to chemotherapy is developed and validated using a large-scale data set consisting of 493 samples from The Cancer Genome Atlas (TCGA) and 244 samples from an Australian report. An identified 227-gene signature achieves an overall predictive accuracy of greater than 85% with a sensitivity of approximately 95% and specificity of approximately 70%. The gene signature significantly distinguishes between patients with unfavorable versus favorable prognosis, when applied to either an independent data set (P = 0.04) or an external validation set (P<0.0001). In parallel, we present the production of a tumor nuclear image profile generated from 253 sample slides by characterizing patients with nuclear features (such as size, elongation, and roundness) in incremental bins, and we identify a morphologic signature that demonstrates a strong association with chemotherapy response in serous ovarian carcinoma.
A gene signature discovered on a large data set provides robustness in accurately predicting chemotherapy response in serous ovarian carcinoma. The combination of the molecular and morphologic signatures yields a new understanding of potential mechanisms involved in drug resistance.
Porcupine (PORCN) is a membrane-bound O-acyl transferase that is required for the palmitoylation of Wnt proteins, and that is essential in diverse Wnt pathways for Wnt-Wntless (WLS) binding, Wnt secretion, and Wnt signaling activity. We tested if PORCN was required for the proliferation of transformed cells. Knockdown of PORCN by multiple independent siRNAs results in a cell growth defect in a subset of epithelial cancer cell lines. The growth defect is transformation-dependent in human mammary epithelial (HMEC) cells. Additionally, inducible PORCN knockdown by two independent shRNAs markedly reduces the growth of established MDA-MB-231 cancers in orthotopic xenografts in immunodeficient mice. Unexpectedly, the proliferation defect resulting from loss of PORCN occurs in a Wnt-independent manner, as it is rescued by re-expression of catalytically inactive PORCN, and is not seen after RNAi-mediated knockdown of the Wnt carrier protein WLS, nor after treatment with the PORCN inhibitor IWP. Consistent with a role in a Wnt-independent pathway, knockdown of PORCN regulates a distinct set of genes that are not altered by other inhibitors of Wnt signaling. PORCN protein thus appears to moonlight in a novel signaling pathway that is rate-limiting for cancer cell growth and tumorigenesis independent of its enzymatic function in Wnt biosynthesis and secretion.