Clinical and Molecular Analysis of Pathologic Fracture-associated Osteosarcoma: MicroRNA profile Is Different and Correlates with Prognosis.

BACKGROUND: MicroRNAs are small, noncoding RNAs that regulate the expression of posttranslational genes. The presence of some specific microRNAs has been associated with increased risk of both local recurrence and metastasis and worse survival in patients with osteosarcoma. Pathologic fractures in osteosarcoma are considered to be more the manifestation of a neoplasm with a more aggressive biological behavior than the cause itself of worse prognosis. However, this has not been proved at the biological or molecular level. Currently, there has not been a microRNA profiling study of patients who have osteosarcoma with and without pathologic fractures that has described differences in terms of microRNA profiling between these two groups and their correlation with biologic behavior. QUESTIONS/PURPOSES: (1) In patients with osteosarcoma of the extremities, how do the microRNA profiles of those with and without pathologic fractures compare? (2) What relationship do microRNAs have with local recurrence, risk of metastasis, disease-specific survival, and overall survival in osteosarcoma patients with pathologic fractures? METHODS: Between 1994 and 2013, 217 patients were diagnosed and treated at our institution for osteosarcoma of the extremities. Patients were excluded if (1) they underwent oncologic resection of the osteosarcoma at an outside institution (two patients) or (2) they were diagnosed with an extraskeletal osteosarcoma (29 patients) or (3) they had less than 1 year of clinical follow-up and no oncologic outcome (local recurrence, metastasis, or death) (four patients). A total of 182 patients were eligible. Of those, 143 were high-grade osteosarcomas. After evaluation of tumor samples before chemotherapy treatment, a total of 80 consecutive samples were selected for sequencing. Demographic and clinical comparison between the sequenced and non-sequenced patients did not demonstrate any differences, confirming that both groups were comparable. Diagnostic samples from the extremities of 80 patients with high-grade extremity osteosarcomas who had not yet received chemotherapy underwent microRNA sequencing for an ongoing large-scale osteosarcoma genome profiling project at our institution. Six samples were removed after a second look by a musculoskeletal pathologist who verified cellularity and quality of samples to be sequenced, leaving a total of 74 patients. Of these, two samples were removed as they were confirmed to be pelvic tumors in a second check after sequencing. The final study sample was 72 patients (11 patients with pathologic fractures and 61 without). Sequencing data were correlated with fractures and local recurrence, risk of metastasis, disease-specific survival, and overall survival through Kaplan-Meier analyses. RESULTS: Several microRNAs were expressed differently between the two groups. Among the markers with the highest differential expression (edgeR and DESeq algorithms), Hsa-mIR 656-3p, hsa-miR 493-5p, and hsa-miR 381-3p were upregulated in patients with pathologic fractures, whereas hsa-miR 363, hsa-miR 885-5p, and has-miR 20b-5p were downregulated. The highest differential expression fracture and nonfracture-associated microRNA markers also distinguished groups of patients with different metastasis risk, a well as different disease-specific and overall survival. Furthermore, the profile of pathologic fractures demonstrated a higher differential expression for microRNA markers that were previously associated with a higher risk of metastasis and lower survival rates in patients with osteosarcoma. CONCLUSIONS: In patients who have osteosarcoma, the microRNA profiles of those with pathologic fractures are different than of patients without pathologic fractures. The highest differential expression mircroRNA molecules in patients with pathologic fractures predict also higher risk of metastatic disease as well as worse disease-specific survival and overall survival. Furthermore, we found higher differential expression of microRNAs in the pathologic fracture group previously associated with poor prognosis. The higher risk of metastasis and poorer overall survival in patients with pathologic fractures is inherent to tumor aggressive biologic behavior. It is plausible that the fracture itself is not the direct cause of worse prognosis but another manifestation of tumor biologic aggressiveness. Identification of these molecules through liquid biopsies may help to determine which patients may benefit from surgery before fractures occur. The same technology can be applied to identify patterns of response to conventional chemotherapy, assisting in more specific and accurate systemic therapy. LEVEL OF EVIDENCE LEVEL: III, prognostic study.

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

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 variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining 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, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Inference and validation of predictive gene networks from biomedical literature and gene expression data.

Although many methods have been developed for inference of biological networks, the validation of the resulting models has largely remained an unsolved problem. Here we present a framework for quantitative assessment of inferred gene interaction networks using knock-down data from cell line experiments. Using this framework we are able to show that network inference based on integration of prior knowledge derived from the biomedical literature with genomic data significantly improves the quality of inferred networks relative to other approaches. Our results also suggest that cell line experiments can be used to quantitatively assess the quality of networks inferred from tumor samples.

Epstein-Barr virus nuclear antigen 3C regulated genes in lymphoblastoid cell lines.

EBV nuclear antigen 3C (EBNA3C) is an essential transcription factor for EBV transformed lymphoblast cell line (LCL) growth. To identify EBNA3C-regulated genes in LCLs, microarrays were used to measure RNA abundances in each of three different LCLs that conditionally express EBNA3C fused to a 4-OH-Tamoxifen-dependent estrogen receptor hormone binding domain (EBNA3CHT). At least three RNAs were assayed for each EBNA3CHT LCL under nonpermissive conditions, permissive conditions, and nonpermissive conditions with wild-type EBNA3C transcomplementation. Using a two-way ANOVA model of EBNA3C levels, we identified 550 regulated genes that were at least 1.5-fold up- or down-regulated with false discovery rates < 0.01. EBNA3C-regulated genes overlapped significantly with genes regulated by EBNA2 and EBNA3A consistent with coordinated effects on cell gene transcription. Of the 550 EBNA3C-regulated genes, 106 could be placed in protein networks. A seeded Bayesian network analysis of the 80 most significant EBNA3C-regulated genes suggests that RAC1, LYN, and TNF are upstream of other EBNA3C-regulated genes. Gene set enrichment analysis found enrichment for MAP kinase signaling, cytokine-cytokine receptor interactions, JAK-STAT signaling, and cell adhesion molecules, implicating these pathways in EBNA3C effects on LCL growth or survival. EBNA3C significantly up-regulated the CXCL12 ligand and its CXCR4 receptor and increased LCL migration. CXCL12 up-regulation depended on EBNA3C's interaction with the cell transcription factor, RBPJ, which is essential for LCL growth. EBNA3C also up-regulated MYC 1.3-fold and down-regulated CDKN2A exons 2 and 3, shared by p16 and p14, 1.4-fold, with false discovery rates < 5 × 10(-4).

Next-generation sequencing and microarray-based interrogation of microRNAs from formalin-fixed, paraffin-embedded tissue: preliminary assessment of cross-platform concordance.

Next-generation sequencing is increasingly employed in biomedical investigations. Strong concordance between microarray and mRNA-seq levels has been reported in high quality specimens but information is lacking on formalin-fixed, paraffin-embedded (FFPE) tissues, and particularly for microRNA (miRNA) analysis. We conducted a preliminary examination of the concordance between miRNA-seq and cDNA-mediated annealing, selection, extension, and ligation (DASL) miRNA assays. Quantitative agreement between platforms is moderate (Spearman correlation 0.514-0.596) and there is discordance of detection calls on a subset of miRNAs. Quantitative PCR (q-RT-PCR) performed for several discordant miRNAs confirmed the presence of most sequences detected by miRNA-seq but not by DASL but also that miRNA-seq did not detect some sequences, which DASL confidently detected. Our results suggest that miRNA-seq is specific, with few false positive calls, but it may not detect certain abundant miRNAs in FFPE tissue. Further work is necessary to fully address these issues that are pertinent for translational research.

Viral perturbations of host networks reflect disease etiology.

Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases), are also associated with viral infections (virally implicated diseases), either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV) and human papillomavirus (HPV), we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.

A microRNA activity map of human mesenchymal tumors: connections to oncogenic pathways; an integrative transcriptomic study.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

Ovarian reserve status in young women is associated with altered gene expression in membrana granulosa cells.

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.

COLD-PCR enrichment of rare cancer mutations prior to targeted amplicon resequencing.

BACKGROUND: Despite widespread interest in next-generation sequencing (NGS), the adoption of personalized clinical genomics and mutation profiling of cancer specimens is lagging, in part because of technical limitations. Tumors are genetically heterogeneous and often contain normal/stromal cells, features that lead to low-abundance somatic mutations that generate ambiguous results or reside below NGS detection limits, thus hindering the clinical sensitivity/specificity standards of mutation calling. We applied COLD-PCR (coamplification at lower denaturation temperature PCR), a PCR methodology that selectively enriches variants, to improve the detection of unknown mutations before NGS-based amplicon resequencing. METHODS: We used both COLD-PCR and conventional PCR (for comparison) to amplify serially diluted mutation-containing cell-line DNA diluted into wild-type DNA, as well as DNA from lung adenocarcinoma and colorectal cancer samples. After amplification of TP53 (tumor protein p53), KRAS (v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog), IDH1 [isocitrate dehydrogenase 1 (NADP(+)), soluble], and EGFR (epidermal growth factor receptor) gene regions, PCR products were pooled for library preparation, bar-coded, and sequenced on the Illumina HiSeq 2000. RESULTS: In agreement with recent findings, sequencing errors by conventional targeted-amplicon approaches dictated a mutation-detection limit of approximately 1%-2%. Conversely, COLD-PCR amplicons enriched mutations above the error-related noise, enabling reliable identification of mutation abundances of approximately 0.04%. Sequencing depth was not a large factor in the identification of COLD-PCR-enriched mutations. For the clinical samples, several missense mutations were not called with conventional amplicons, yet they were clearly detectable with COLD-PCR amplicons. Tumor heterogeneity for the TP53 gene was apparent. CONCLUSIONS: As cancer care shifts toward personalized intervention based on each patient's unique genetic abnormalities and tumor genome, we anticipate that COLD-PCR combined with NGS will elucidate the role of mutations in tumor progression, enabling NGS-based analysis of diverse clinical specimens within clinical practice.

Comparative gene expression analysis in mouse models for multiple sclerosis, Alzheimer's disease and stroke for identifying commonly regulated and disease-specific gene changes.

The brain responds to injury and infection by activating innate defense and tissue repair mechanisms. Working upon the hypothesis that the brain defense response involves common genes and pathways across diverse pathologies, we analysed global gene expression in brain from mouse models representing three major central nervous system disorders, cerebral stroke, multiple sclerosis and Alzheimer's disease compared to normal brain using DNA microarray expression profiling. A comparison of dysregulated genes across disease models revealed common genes and pathways including key components of estrogen and TGF-beta signaling pathways that have been associated with neuroprotection as well as a neurodegeneration mediator, TRPM7. Further, for each disease model, we discovered collections of differentially expressed genes that provide novel insight into the individual pathology and its associated mechanisms. Our data provide a resource for exploring the complex molecular mechanisms that underlie brain neurodegeneration and a new approach for identifying generic and disease-specific targets for therapy.

Proliferative genes dominate malignancy-risk gene signature in histologically-normal breast tissue.

Historical data have indicated the potential for the histologically-normal breast to harbor pre-malignant changes at the molecular level. We postulated that a histologically-normal tissue with "tumor-like" gene expression pattern might harbor substantial risk for future cancer development. Genes associated with these high-risk tissues were considered to be "malignancy-risk genes". From a total of 90 breast cancer patients, we collected a set of 143 histologically-normal breast tissues derived from patients harboring breast cancer who underwent curative mastectomy, as well as a set of 42 invasive ductal carcinomas (IDC) of various histologic grades. All samples were assessed for global gene expression differences using microarray analysis. For the purpose of this study we defined normal breast tissue to include histologically normal and benign lesions. Here we report the discovery of a "malignancy-risk" gene signature that may portend risk of breast cancer development in benign, but molecularly-abnormal, breast tissue. Pathway analysis showed that the malignancy-risk signature had a dramatic enrichment for genes with proliferative function, but appears to be independent of ER, PR, and HER2 status. The signature was validated by RT-PCR, with a high correlation (Pearson correlation = 0.95 with P < 0.0001) with microarray data. These results suggest a predictive role for the malignancy-risk signature in normal breast tissue. Proliferative biology dominates the earliest stages of tumor development.

Gene-environment interactions reveal a homeostatic role for cholesterol metabolism during dietary folate perturbation in mice.

Dietary folate supplementation can dramatically reduce the severity and incidence of several common birth defects and adult diseases that are associated with anomalies in homocysteine and folate metabolism. The common polymorphisms that adversely affect these metabolic pathways do not fully account for the particular birth defects and adult diseases that occur in at-risk individuals. To test involvement of folate, homocysteine, and other pathways in disease pathogenesis and treatment response, we analyzed global and pathway-specific changes in gene expression and levels of selected metabolites after depletion and repletion of dietary folate in two genetically distinct inbred strains of mice. Compared with the C57BL/6J strain, A/J showed greater homeostatic response to folate perturbation by retaining a higher serum folate level and minimizing global gene expression changes. Remarkably, folate perturbation led to systematic strain-specific differences only in the expression profile of the cholesterol biosynthesis pathway and to changes in levels of serum and liver total cholesterol. By genetically increasing serum and liver total cholesterol levels in APOE-deficient mice, we modestly but significantly improved folate retention during folate depletion, suggesting that homeostasis among the homocysteine, folate and cholesterol metabolic pathways contributes to the beneficial effects of dietary folate supplementation.

Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling.

RNA-seq is increasingly used for quantitative profiling of small RNAs (for example, microRNAs, piRNAs and snoRNAs) in diverse sample types, including isolated cells, tissues and cell-free biofluids. The accuracy and reproducibility of the currently used small RNA-seq library preparation methods have not been systematically tested. Here we report results obtained by a consortium of nine labs that independently sequenced reference, 'ground truth' samples of synthetic small RNAs and human plasma-derived RNA. We assessed three commercially available library preparation methods that use adapters of defined sequence and six methods using adapters with degenerate bases. Both protocol- and sequence-specific biases were identified, including biases that reduced the ability of small RNA-seq to accurately measure adenosine-to-inosine editing in microRNAs. We found that these biases were mitigated by library preparation methods that incorporate adapters with degenerate bases. MicroRNA relative quantification between samples using small RNA-seq was accurate and reproducible across laboratories and methods.

High Throughput Sequencing of Extracellular RNA from Human Plasma.

The presence and relative stability of extracellular RNAs (exRNAs) in biofluids has led to an emerging recognition of their promise as 'liquid biopsies' for diseases. Most prior studies on discovery of exRNAs as disease-specific biomarkers have focused on microRNAs (miRNAs) using technologies such as qRT-PCR and microarrays. The recent application of next-generation sequencing to discovery of exRNA biomarkers has revealed the presence of potential novel miRNAs as well as other RNA species such as tRNAs, snoRNAs, piRNAs and lncRNAs in biofluids. At the same time, the use of RNA sequencing for biofluids poses unique challenges, including low amounts of input RNAs, the presence of exRNAs in different compartments with varying degrees of vulnerability to isolation techniques, and the high abundance of specific RNA species (thereby limiting the sensitivity of detection of less abundant species). Moreover, discovery in human diseases often relies on archival biospecimens of varying age and limiting amounts of samples. In this study, we have tested RNA isolation methods to optimize profiling exRNAs by RNA sequencing in individuals without any known diseases. Our findings are consistent with other recent studies that detect microRNAs and ribosomal RNAs as the major exRNA species in plasma. Similar to other recent studies, we found that the landscape of biofluid microRNA transcriptome is dominated by several abundant microRNAs that appear to comprise conserved extracellular miRNAs. There is reasonable correlation of sets of conserved miRNAs across biological replicates, and even across other data sets obtained at different investigative sites. Conversely, the detection of less abundant miRNAs is far more dependent on the exact methodology of RNA isolation and profiling. This study highlights the challenges in detecting and quantifying less abundant plasma miRNAs in health and disease using RNA sequencing platforms.

Gender-Specific Molecular and Clinical Features Underlie Malignant Pleural Mesothelioma.

Malignant pleural mesothelioma (MPM) is an aggressive cancer that occurs more frequently in men, but is associated with longer survival in women. Insight into the survival advantage of female patients may advance the molecular understanding of MPM and identify therapeutic interventions that will improve the prognosis for all MPM patients. In this study, we performed whole-genome sequencing of tumor specimens from 10 MPM patients and matched control samples to identify potential driver mutations underlying MPM. We identified molecular differences associated with gender and histology. Specifically, single-nucleotide variants of BAP1 were observed in 21% of cases, with lower mutation rates observed in sarcomatoid MPM (P < 0.001). Chromosome 22q loss was more frequently associated with the epithelioid than that nonepitheliod histology (P = 0.037), whereas CDKN2A deletions occurred more frequently in nonepithelioid subtypes among men (P = 0.021) and were correlated with shorter overall survival for the entire cohort (P = 0.002) and for men (P = 0.012). Furthermore, women were more likely to harbor TP53 mutations (P = 0.004). Novel mutations were found in genes associated with the integrin-linked kinase pathway, including MYH9 and RHOA. Moreover, expression levels of BAP1, MYH9, and RHOA were significantly higher in nonepithelioid tumors, and were associated with significant reduction in survival of the entire cohort and across gender subgroups. Collectively, our findings indicate that diverse mechanisms highly related to gender and histology appear to drive MPM.

Using shRNA experiments to validate gene regulatory networks.

Quantitative validation of gene regulatory networks (GRNs) inferred from observational expression data is a difficult task usually involving time intensive and costly laboratory experiments. We were able to show that gene knock-down experiments can be used to quantitatively assess the quality of large-scale GRNs via a purely data-driven approach (Olsen et al. 2014). Our new validation framework also enables the statistical comparison of multiple network inference techniques, which was a long-standing challenge in the field. In this Data in Brief we detail the contents and quality controls for the gene expression data (available from NCBI Gene Expression Omnibus repository with accession number GSE53091) associated with our study published in Genomics (Olsen et al. 2014). We also provide R code to access the data and reproduce the analysis presented in this article.

Meeting report: discussions and preliminary findings on extracellular RNA measurement methods from laboratories in the NIH Extracellular RNA Communication Consortium.

Extracellular RNAs (exRNAs) have been identified in all tested biofluids and have been associated with a variety of extracellular vesicles, ribonucleoprotein complexes and lipoprotein complexes. Much of the interest in exRNAs lies in the fact that they may serve as signalling molecules between cells, their potential to serve as biomarkers for prediction and diagnosis of disease and the possibility that exRNAs or the extracellular particles that carry them might be used for therapeutic purposes. Among the most significant bottlenecks to progress in this field is the lack of robust and standardized methods for collection and processing of biofluids, separation of different types of exRNA-containing particles and isolation and analysis of exRNAs. The Sample and Assay Standards Working Group of the Extracellular RNA Communication Consortium is a group of laboratories funded by the U.S. National Institutes of Health to develop such methods. In our first joint endeavour, we held a series of conference calls and in-person meetings to survey the methods used among our members, placed them in the context of the current literature and used our findings to identify areas in which the identification of robust methodologies would promote rapid advancements in the exRNA field.

Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancer.

Ovarian cancer is the fifth leading cause of cancer death for women in the U.S. and the seventh most fatal worldwide. Although ovarian cancer is notable for its initial sensitivity to platinum-based therapies, the vast majority of patients eventually develop recurrent cancer and succumb to increasingly platinum-resistant disease. Modern, targeted cancer drugs intervene in cell signaling, and identifying key disease mechanisms and pathways would greatly advance our treatment abilities. In order to shed light on the molecular diversity of ovarian cancer, we performed comprehensive transcriptional profiling on 129 advanced stage, high grade serous ovarian cancers. We implemented a, re-sampling based version of the ISIS class discovery algorithm (rISIS: robust ISIS) and applied it to the entire set of ovarian cancer transcriptional profiles. rISIS identified a previously undescribed patient stratification, further supported by micro-RNA expression profiles, and gene set enrichment analysis found strong biological support for the stratification by extracellular matrix, cell adhesion, and angiogenesis genes. The corresponding "angiogenesis signature" was validated in ten published independent ovarian cancer gene expression datasets and is significantly associated with overall survival. The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials.

Therapeutic implications of GIPC1 silencing in cancer.

GIPC1 is a cytoplasmic scaffold protein that interacts with numerous receptor signaling complexes, and emerging evidence suggests that it plays a role in tumorigenesis. GIPC1 is highly expressed in a number of human malignancies, including breast, ovarian, gastric, and pancreatic cancers. Suppression of GIPC1 in human pancreatic cancer cells inhibits in vivo tumor growth in immunodeficient mice. To better understand GIPC1 function, we suppressed its expression in human breast and colorectal cancer cell lines and human mammary epithelial cells (HMECs) and assayed both gene expression and cellular phenotype. Suppression of GIPC1 promotes apoptosis in MCF-7, MDA-MD231, SKBR-3, SW480, and SW620 cells and impairs anchorage-independent colony formation of HMECs. These observations indicate GIPC1 plays an essential role in oncogenic transformation, and its expression is necessary for the survival of human breast and colorectal cancer cells. Additionally, a GIPC1 knock-down gene signature was used to interrogate publically available breast and ovarian cancer microarray datasets. This GIPC1 signature statistically correlates with a number of breast and ovarian cancer phenotypes and clinical outcomes, including patient survival. Taken together, these data indicate that GIPC1 inhibition may represent a new target for therapeutic development for the treatment of human cancers.