The pro-apoptotic BCL-2 family proteins BAX and BAK serve as essential gatekeepers of the intrinsic apoptotic pathway and, when activated, transform into pore forming homo-oligomers that permeabilize the mitochondrial outer membrane. Deletion of Bax and Bak causes marked resistance to death stimuli in a variety of cell types. Bax−/−Bak−/− mice are predominantly nonviable and survivors exhibit multiple developmental abnormalities characterized by cellular excess, including accumulation of neural progenitor cells in the periventricular, hippocampal, cerebellar, and olfactory bulb regions of the brain. To explore the long-term pathophysiologic consequences of BAX/BAK deficiency in a stem cell niche, we generated Bak−/− mice with conditional deletion of Bax in Nestin-positive cells. Aged NestinCreBaxfl/flBak−/− mice manifest progressive brain enlargement with a profound accumulation of NeuN- and Sox2-positive neural progenitor cells within the subventricular zone. One-third of the mice develop frank masses comprised of neural progenitors, and in 20% of these cases, more aggressive, hypercellular tumors emerged. Unexpectedly, 60% of NestinCreBaxfl/flBak−/− mice harbored high-grade tumors within the testis, a peripheral site of Nestin expression. This in vivo model of severe apoptotic blockade highlights the constitutive role of BAX/BAK in long-term regulation of Nestin-positive progenitor cell pools, with loss of function predisposing to adult-onset tumorigenesis.
BAX; BAK; neural progenitor cell; apoptosis; tumorigenesis
Rhesus macaques (RMs) inoculated with live-attenuated Rev-Independent Nef¯ simian immunodeficiency virus (Rev-Ind Nef¯SIV) as adults or neonates controlled viremia to undetectable levels and showed no signs of immunodeficiency over 6-8 years of follow-up. We tested the capacity of this live-attenuated virus to protect RMs against pathogenic, heterologous SIVsmE660 challenges.
Three groups of four RM were inoculated with Rev-Ind Nef¯SIV and compared. Group 1 was inoculated 8 years prior and again 15 months before low dose intrarectal challenges with SIVsmE660. Group 2 animals were inoculated with Rev-Ind Nef¯SIV at 15 months and Group 3 at 2 weeks prior to the SIVsmE660 challenges, respectively. Group 4 served as unvaccinated controls. All RMs underwent repeated weekly low-dose intrarectal challenges with SIVsmE660. Surprisingly, all RMs with acute live-attenuated virus infection (Group 3) became superinfected with the challenge virus, in contrast to the two other vaccine groups (Groups 1 and 2) (P=0.006 for each) and controls (Group 4) (P=0.022). Gene expression analysis showed significant upregulation of innate immune response-related chemokines and their receptors, most notably CCR5 in Group 3 animals during acute infection with Rev-Ind Nef¯SIV.
We conclude that although Rev-Ind Nef¯SIV remained apathogenic, acute replication of the vaccine strain was not protective but associated with increased acquisition of heterologous mucosal SIVsmE660 challenges.
The disease course of chronic lymphocytic leukemia (CLL) varies significantly within cytogenetic groups. We hypothesized that high resolution genomic analysis of CLL would identify additional recurrent abnormalities associated with short time to first therapy (TTFT).
We undertook high resolution genomic analysis of 161 prospectively enrolled CLLs using Affymetrix 6.0 SNP arrays, and integrated analysis of this dataset with gene expression profiles.
Copy number analysis (CNA) of nonprogressive CLL reveals a stable genotype, with a median of only 1 somatic CNA per sample. Progressive CLL with 13q deletion was associated with additional somatic CNAs, and a greater number of CNAs was predictive of TTFT. We identified other recurrent CNAs associated with short TTFT: 8q24 amplification focused on the cancer susceptibility locus near MYC in 3.7%; 3q26 amplifications focused on PIK3CA in 5.6%; and 8p deletions in 5% of patients. Sequencing of MYC further identified somatic mutations in two CLLs. We determined which catalytic subunits of PI3K were in active complex with the p85 regulatory subunit, and demonstrated enrichment for the alpha subunit in three CLLs carrying PIK3CA amplification.
Our findings implicate amplifications of 3q26 focused on PIK3CA and 8q24 focused on MYC in CLL.
CLL; PIK3CA; MYC; genomics; copy number
Diminished ovarian reserve (DOR) is a challenging diagnosis of infertility, as there are currently no tests to predict who may become affected with this condition, or at what age. We designed the present study to compare the gene expression profile of membrana granulosa cells from young women affected with DOR with those from egg donors of similar age and to determine if distinct genetic patterns could be identified to provide insight into the etiology of DOR. Young women with DOR were identified based on FSH level in conjunction with poor follicular development during an IVF cycle (n = 13). Egg donors with normal ovarian reserve (NOR) comprised the control group (n = 13). Granulosa cells were collected following retrieval, RNA was extracted and microarray analysis was conducted to evaluate genetic differences between the groups. Confirmatory studies were undertaken with quantitative RT–PCR (qRT–PCR). Multiple significant differences in gene expression were observed between the DOR patients and egg donors. Two genes linked with ovarian function, anti-Mullerian hormone (AMH) and luteinizing hormone receptor (LHCGR), were further analyzed with qRT–PCR in all patients. The average expression of AMH was significantly higher in egg donors (adjusted P-value = 0.01), and the average expression of LHCGR was significantly higher in DOR patients (adjusted P-value = 0.005). Expression levels for four additional genes, progesterone receptor membrane component 2 (PGRMC2), prostaglandin E receptor 3 (subtype EP3) (PTGER3), steroidogenic acute regulatory protein (StAR), and StAR-related lipid transfer domain containing 4 (StarD4), were validated in a group consisting of five NOR and five DOR patients. We conclude that gene expression analysis has substantial potential to determine which young women may be affected with DOR. More importantly, our analysis suggests that DOR patients fall into two distinct subgroups based on gene expression profiles, indicating that different mechanisms may be involved during development of this pathology.
granulosa cells; oocyte quality; diminished ovarian reserve; IVF; microarray analysis
Despite widespread interest in the application of next-generation-sequencing (NGS) to the mutation profiling of individual cancer specimens, the onset of personalized clinical genomics is currently stalled due in part to technical hurdles. As tumors are genetically-heterogeneous and often mixed with normal/stromal cells, the resulting low-abundance DNA somatic mutations often produce ambiguous results or fall below the current NGS detection limit, thus hindering mutation calling that abides to clinical sensitivity/specificity standards. Here we examine the feasibility of applying COLD-PCR, a form of PCR that magnifies selectively the mutations, to boost the detection of unknown rare somatic mutations prior to applying NGS-based amplicon re-sequencing to clinical samples. We amplified DNA from serially-diluted mutation-containing human cell-lines into wild-type (WT) DNA, as well as lung adenocarcinoma and colorectal cancer specimens using COLD-PCR or conventional PCR for comparison. Following individual amplification of TP53, KRAS, IDH1, and EGFR regions, PCR products were barcoded, pooled for library preparation and sequenced on the Illumina-HiSeq2000 platform. Regardless of sequencing depth, sequencing errors dictated a mutation-detection limit of ~1–2% mutation abundance in conventional PCR amplicons analyzed by NGS. In contrast, COLD-PCR amplicons enabled genuine mutations to exceed the sequence noise levels, thus allowing reliable identification of mutation abundances of ~0.04%. Sequencing depth was not a significant factor in the identification of COLD-PCR-magnified mutations. The analyzed clinical specimens revealed several TP53 and KRAS missense mutations that could not be called following NGS of conventional amplicons, yet were clearly detectable in COLD-PCR amplicons. Extensive tumor heterogeneity in the TP53 gene was revealed in some samples. As cancer care shifts toward personalized intervention, based on the unique genetic abnormalities in each patient’s tumor genome, we anticipate that COLD-PCR-NGS will elucidate the role of rare mutations in tumors, enable NGS-based analysis of diverse clinical specimens and the broad inter-phasing of NGS with clinical practice.
COLD-PCR; mutation enrichment; low-abundance mutations; next generation sequencing; cancer
Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations1. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations2. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations3. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer.
MicroRNAs (miRNAs) are nucleic acid regulators of many human mRNAs, and are associated with many tumorigenic processes. miRNA expression levels have been used in profiling studies, but some evidence suggests that expression levels do not fully capture miRNA regulatory activity. In this study we integrate multiple gene expression datasets to determine miRNA activity patterns associated with cancer phenotypes and oncogenic pathways in mesenchymal tumors – a very heterogeneous class of malignancies.
Using a computational method, we identified differentially activated miRNAs between 77 normal tissue specimens and 135 sarcomas and we validated many of these findings with microarray interrogation of an independent, paraffin-based cohort of 18 tumors. We also showed that miRNA activity is imperfectly correlated with miRNA expression levels. Using next-generation miRNA sequencing we identified potential base sequence alterations which may explain differential activity. We then analyzed miRNA activity changes related to the RAS-pathway and found 21 miRNAs that switch from silenced to activated status in parallel with RAS activation. Importantly, nearly half of these 21 miRNAs were predicted to regulate integral parts of the miRNA processing machinery, and our gene expression analysis revealed significant reductions of these transcripts in RAS-active tumors. These results suggest an association between RAS signaling and miRNA processing in which miRNAs may attenuate their own biogenesis.
Our study represents the first gene expression-based investigation of miRNA regulatory activity in human sarcomas, and our findings indicate that miRNA activity patterns derived from integrated transcriptomic data are reproducible and biologically informative in cancer. We identified an association between RAS signaling and miRNA processing, and demonstrated sequence alterations as plausible causes for differential miRNA activity. Finally, our study highlights the value of systems level integrative miRNA/mRNA assessment with high-throughput genomic data, and the applicability of paraffin-tissue-derived RNA for validation of novel findings.
MicroRNA; Microarray; RAS; Mesenchymal tumors; MicroRNA biogenesis
Cyclin D1 is a component of the core cell cycle machinery1. Abnormally high levels of cyclin D1 are detected in many human cancer types2. To elucidate the molecular functions of cyclin D1 in human cancers, here we performed a proteomic screen for cyclin D1 protein partners in several types of human tumors. Analyses of cyclin D1-interactors revealed a network of DNA repair proteins, including RAD51, a recombinase that drives the homologous recombination process3. We found that cyclin D1 directly binds RAD51, and that cyclin D1-RAD51 interaction is induced by radiation. Like RAD51, cyclin D1 is recruited to DNA damage sites in a BRCA2-dependent fashion. Reduction of cyclin D1 levels in human cancer cells impaired recruitment of RAD51 to damaged DNA, impeded the homologous recombination-mediated DNA repair, and increased sensitivity of cells to radiation in vitro and in vivo. This effect was seen in cancer cells lacking the retinoblastoma protein, which do not require D-cyclins for proliferation4, 5. These findings reveal an unexpected function of a core cell cycle protein in DNA repair and suggest that targeting cyclin D1 may be beneficial also in retinoblastoma-negative cancers which are currently thought to be oblivious to cyclin D1 inhibition.
Mounting evidence suggests that malignant tumors are initiated and maintained by a subpopulation of cancerous cells with biological properties similar to those of normal stem cells. However, descriptions of stem-like gene and pathway signatures in cancers are inconsistent across experimental systems. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), we have developed the Stem Cell Discovery Engine (SCDE)—an online database of curated CSC experiments coupled to the Galaxy analytical framework. The SCDE allows users to consistently describe, share and compare CSC data at the gene and pathway level. Our initial focus has been on carefully curating tissue and cancer stem cell-related experiments from blood, intestine and brain to create a high quality resource containing 53 public studies and 1098 assays. The experimental information is captured and stored in the multi-omics Investigation/Study/Assay (ISA-Tab) format and can be queried in the data repository. A linked Galaxy framework provides a comprehensive, flexible environment populated with novel tools for gene list comparisons against molecular signatures in GeneSigDB and MSigDB, curated experiments in the SCDE and pathways in WikiPathways. The SCDE is available at http://discovery.hsci.harvard.edu.
GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org.
Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ‘known’ interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/.
The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently presented using non-standard gene or probeset nomenclature. We present GeneSigDB (http://compbio.dfci.harvard.edu/genesigdb) a manually curated database of gene expression signatures. GeneSigDB release 1.0 focuses on cancer and stem cells gene signatures and was constructed from more than 850 publications from which we manually transcribed 575 gene signatures. Most gene signatures (n = 560) were successfully mapped to the genome to extract standardized lists of EnsEMBL gene identifiers. GeneSigDB provides the original gene signature, the standardized gene list and a fully traceable gene mapping history for each gene from the original transcribed data table through to the standardized list of genes. The GeneSigDB web portal is easy to search, allows users to compare their own gene list to those in the database, and download gene signatures in most common gene identifier formats.
CRX is a homeobox transcription factor whose expression and function is critical to maintain retinal and pineal lineage cells and their progenitors. To determine the biologic and diagnostic potential of CRX in human tumors of the retina and pineal, we examined its expression in multiple settings.
Using situ hybridization and immunohistochemistry we show that Crx RNA and protein expression are exquisitely lineage restricted to retinal and pineal cells during normal mouse and human development. Gene expression profiling analysis of a wide range of human cancers and cancer cell lines also supports that CRX RNA is highly lineage restricted in cancer. Immunohistochemical analysis of 22 retinoblastomas and 13 pineal parenchymal tumors demonstrated strong expression of CRX in over 95% of these tumors. Importantly, CRX was not detected in the majority of tumors considered in the differential diagnosis of pineal region tumors (n = 78). The notable exception was medulloblastoma, 40% of which exhibited CRX expression in a heterogeneous pattern readily distinguished from that seen in retino-pineal tumors.
These findings describe new potential roles for CRX in human cancers and highlight the general utility of lineage restricted transcription factors in cancer biology. They also identify CRX as a sensitive and specific clinical marker and a potential lineage dependent therapeutic target in retinoblastoma and pineoblastoma.