Endometrial cancer is the 6th most commonly diagnosed cancer among women worldwide, causing ~74,000 deaths annually 1. Serous endometrial cancers are a clinically aggressive subtype with a poorly defined genetic etiology 2-4. We used whole exome sequencing (WES) to comprehensively search for somatic mutations within ~22,000 protein-encoding genes among 13 primary serous endometrial tumors. We subsequently resequenced 18 genes that were mutated in more than one tumor, and/or were genes that formed an enriched functional grouping, from 40 additional serous tumors. We identified high frequencies of somatic mutations in CHD4 (17%), EP300 (8%), ARID1A (6%), TSPYL2 (6%), FBXW7 (29%), SPOP (8%), MAP3K4 (6%) and ABCC9 (6%). Overall, 36.5% of serous tumors had mutated a chromatin-remodeling gene and 35% had mutated a ubiquitin ligase complex gene, implicating the frequent mutational disruption of these processes in the molecular pathogenesis of one of the deadliest forms of endometrial cancer.

EBV-encoded microRNAs (miRNAs) have been identified and their functions are being studied. The expression pattern of these miRNAs in clinical samples of EBV-associated nonHodgkin's lymphomas is unknown. We analyzed five primary ''endemic'' pediatric Burkitt's lymphomas (BL), two acquired immunodeficiency syndrome (AIDS)-related type I latency BL lines, a type III latency line, three EBV + primary effusion lymphomas (PEL), and three AIDS-related diffuse large B-cell lymphomas (DLBCL) for expression of EBV-encoded miRNAs.

IntroductionMicroRNAs (miRNAs) are a new class of genes that function as inhibitory RNA molecules that confer specificity to the RNAinduced silencing complex, which degrades the target mRNAs or inhibits protein translation. Because the biochemical function of miRNAs is to inhibit protein expression, it is not surprising that miRNAs can exhibit tumor suppressor phenotypes.Conversely, miRNAs have also been associated with growthpromoting phenotypes if their targets include tumor suppressor proteins or proteins that are required for cell differentiation. Many miRNAs are strictly cell lineage-associated, whereas others are found in multiple tissues, albeit at different levels. 1 Hence, miRNAs, like mRNAs, can be subjected to microarray profiling. Tumor signatures based on miRNA profiles have clinical predictive power, analogous to signatures based on mRNA profiles. 2 We have used real-time quantitative polymerase chain reaction-based arrays to profile miRNAs in 2 AIDS-defining cancers: primary effusion lymphoma (PEL) and Kaposi sarcoma (KS).PEL is a monoclonal CD138 ϩ , postgerminal center nonHodgkin B-cell lymphoma. 3 PELs express CD71 ϩ , CD38 ϩ activation markers and are invariably infected with KS-associated herpesvirus (KSHV). They can be dually infected with EpsteinBarr virus (EBV). EBV-positive and EBV-negative PEL can be differentiated based on their mRNA transcription pattern 4 but do not differ appreciably in culture or in animal models. 5,6 KS is also associated with KSHV infection. 7 KS is a malignancy of endothelial cells (ECs) and thought to be at the border between infectioninduced hyperplasia and clonal neoplasia.We find many known tumor suppressor miRNAs downregulated in PEL and KS. These include miR-155, miR-220/221, as well as miR-let7 family members. These miRNAs were more down-regulated in the monoclonal, fully transformed PEL than in KS biopsies or KSHV-infected, nontumorigenic ECs. This reinforces the importance of tumor suppressor miRNAs in oncogenic transformation and underscores their clinical utility for tumor classification. MethodsPELs are listed in Table S1 (available on the Blood website; see the Supplemental Materials link at the top of the online article). KS biopsies were obtained with informed consent obtained in accordance with the Declaration of Helsinki and used deidentified. Whole tonsil samples were used and obtained from the Cooperative Human Tissue Network. RNA was isolated as per our prior procedures, 8 and miRNA levels quantified using a commercial assay according to the manufacturer's recommendations (Applied Biosystems, Foster City, CA). Data were normalized to U6 RNA and clustered using Arrayminer (Optimal Design, Nivelles, Belgium). Analysis of variance, t test, and analysis of residuals after robust regression 9 were conducted in R (www.r-project.org). Results and discussionTo identify miRNAs that are down-regulated in KSHV-associated cancers, we profiled PELs, normal tonsil tissue, KSHV-infected and uninfected ECs, and, for the first time, primary KS biopsies. We had...

MicroRNAs are regulated by gene alteration, transcription, and processing. Thus far, few studies have simultaneously assessed all 3 levels of regulation. Using real-time quantitative polymerase chain reaction (QPCR)-based arrays, we determined changes in gene copy number, pre-miRNA, and mature miRNA levels for the largest set of primary effusion lymphomas (PELs) to date. We detected PELspecific miRNA gene amplifications, and concordant changes in pre-miRNA and mature miRNA. We identified 68 PELspecific miRNAs. This defines the miRNA signature of PEL and shows that transcriptional regulation of pre-miRNA as well as mature miRNA levels contribute nonredundant information that can be used for the classification of human tumors. Most miRNA gene loci are interspersed between coding regions or located within introns, though some can be embedded within an open reading frame. Thirty-seven percent of human miRNAs are organized in multi-miRNA clusters, 3 many of which can be found around fragile sites. 4,5 Clustered miRNAs are regulated by a common promoter and processed from a single primary transcript (pri-miRNA) that may contain several miRNAs, as well as coding exons. Hence, miRNAs are subject to (1) genomic alterations at the DNA level, (2) transcriptional regulation at the pre-miRNA level, and (3) processing control at the mature miRNA level. Thus far, few studies have evaluated these 3 modes of regulation simultaneously.In the nucleus, Drosha initiates miRNA processing ( Figure 1A) by cleaving the primary miRNA (pri-miRNA) to release the approximately 60-nt-long precursor miRNAs (pre-miRNAs). 6 After export to the cytoplasm, the pre-miRNAs are further processed by Dicer to yield an approximately 22-bp miRNA duplex. 7,8 One strand of this duplex is then incorporated into the RNA-induced silencing complex (RISC), where it guides the RISC to mRNAs bearing complementary sequences. 9,10 If the mRNA contains a perfectly complementary sequence, the RISC component Ago2 cleaves the target leading to mRNA degradation. 11,12 In the case of an imperfect complementary target, RISC binding can induce translational inhibition. 12 Translation inhibition is highly cooperative and requires several RISCs, potentially each with a different miRNA. 13,14 We hypothesized that cancer-specific miRNA profiles are determined by a combination of changes at the level of the gene locus, that is, mutations, deletions, or amplifications, changes at the level of transcriptional regulation, and changes at the level of miRNA processing. Hence, comprehensive miRNA profiling should query genomic loci, precursor miRNAs, as well as mature miRNAs. We hypothesized further that this information can be used for the differential diagnosis of lymphomas, specifically of primary effusion lymphoma (PEL).PELs are a unique type of post-germinal center diffuse large B-cell lymphoma (DLBCL). 15,16 Clinically PELs are defined by their effusion phenotype. Furthermore, all PEL tumors carry Kaposi sarcoma-associated herpesvirus (KSHV). KSHV also encodes viral miRNAs. 1...

MicroRNAs (miRNA) have emerged as key regulators of cell lineage differentiation and cancer. We used precursor miRNA profiling by a novel real-time QPCR method (i) to define progressive stages of endothelial cell transformation cumulating in Kaposi sarcoma (KS) and (ii) to identify specific miRNAs that serve as biomarkers for tumor progression. We were able to compare primary patient biopsies to well-established culture and mouse tumor models. Loss of mir-221 and gain of mir-15 expression demarked the transition from merely immortalized to fully tumorigenic endothelial cells. Mir-140 and Kaposi sarcoma–associated herpesvirus viral miRNAs increased linearly with the degree of transformation. Mir-24 emerged as a biomarker specific for KS.

Most sporadic endometrial cancers (ECs) can be histologically classified as endometrioid, serous, or clear cell. Each histotype has a distinct natural history, clinical behavior, and genetic etiology. Endometrioid ECs have an overall favorable prognosis. They are typified by high frequency genomic alterations affecting PIK3CA, PIK3R1, PTEN, KRAS, FGFR2, ARID1A (BAF250a), and CTNNB1 (β-catenin), as well as epigenetic silencing of MLH1 resulting in microsatellite instability. Serous and clear cell ECs are clinically aggressive tumors that are rare at presentation but account for a disproportionate fraction of all endometrial cancer deaths. Serous ECs tend to be aneuploid and are typified by frequent genomic alterations affecting TP53 (p53), PPP2R1A, HER-2/ERBB2, PIK3CA, and PTEN; additionally, they display dysregulation of E-cadherin, p16, cyclin E, and BAF250a. The genetic etiology of clear cell ECs resembles that of serous ECs, but it remains relatively poorly defined. A detailed discussion of the characteristic patterns of genomic alterations that distinguish the three major histotypes of endometrial cancer is reviewed herein.

BackgroundEndometrial cancer (EC) is the 8th leading cause of cancer death amongst American women. Most ECs are endometrioid, serous, or clear cell carcinomas, or an admixture of histologies. Serous and clear ECs are clinically aggressive tumors for which alternative therapeutic approaches are needed. The purpose of this study was to search for somatic mutations in the tyrosine kinome of serous and clear cell ECs, because mutated kinases can point to potential therapeutic targets.MethodsIn a mutation discovery screen, we PCR amplified and Sanger sequenced the exons encoding the catalytic domains of 86 tyrosine kinases from 24 serous, 11 clear cell, and 5 mixed histology ECs. For somatically mutated genes, we next sequenced the remaining coding exons from the 40 discovery screen tumors and sequenced all coding exons from another 72 ECs (10 clear cell, 21 serous, 41 endometrioid). We assessed the copy number of mutated kinases in this cohort of 112 tumors using quantitative real time PCR, and we used immunoblotting to measure expression of these kinases in endometrial cancer cell lines.ResultsOverall, we identified somatic mutations in TNK2 (tyrosine kinase non-receptor, 2) and DDR1 (discoidin domain receptor tyrosine kinase 1) in 5.3% (6 of 112) and 2.7% (3 of 112) of ECs. Copy number gains of TNK2 and DDR1 were identified in another 4.5% and 0.9% of 112 cases respectively. Immunoblotting confirmed TNK2 and DDR1 expression in endometrial cancer cell lines. Three of five missense mutations in TNK2 and one of two missense mutations in DDR1 are predicted to impact protein function by two or more in silico algorithms. The TNK2P761Rfs*72 frameshift mutation was recurrent in EC, and the DDR1R570Q missense mutation was recurrent across tumor types.ConclusionsThis is the first study to systematically search for mutations in the tyrosine kinome in clear cell endometrial tumors. Our findings indicate that high-frequency somatic mutations in the catalytic domains of the tyrosine kinome are rare in clear cell ECs. We uncovered ten new mutations in TNK2 and DDR1 within serous and endometrioid ECs, thus providing novel insights into the mutation spectrum of each gene in EC.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2407-14-884) contains supplementary material, which is available to authorized users.

Uterine cancer is the 6 th leading cause of cancer death amongst American women. Most uterine cancers are endometrial carcinomas (ECs), which are classified into histological subtypes including endometrioid, serous, and clear cell ECs. Somatic copy number alterations (SCNAs) are frequent in serous EC, infrequent in endometrioid ECs, and poorly defined in clear cell ECs. The purpose of this study was to evaluate the occurrence of SCNAs in clinically diagnosed clear cell ECs. Paired tumor-normal DNAs for 51 ECs were hybridized to Illumina Infinium HumanHap650Y or Human660W-Quad Beadchips. Copy number calls were made using the Hidden Markov Model based SNP-FASST2 segmentation algorithm within Nexus Copy Number software (v.6.1). High-level SCNAs were defined as gain of ≥5 copies or homozygous deletion, both <10Mb. GISTIC 1.0, in Nexus, was used to identify statistically significant SCNAs, corrected for multiple testing. One or more high-level SCNAs were detected in 50% of 6 clear cell ECs, 78.6% of 28 serous ECs, and 17.6% of 17 endometrioid ECs. A positive association was found between high-level SCNAs and TP53 mutation across ECs (two-tailed p value<0.0001). Classifying tumors according to POLE, MSI, and TP53 status yielded four molecular subgroups; copy number altered tumors were more frequent in the TP53-mutated subgroup (95.8%) than in the unspecified subgroup (22.2%), and absent from the POLE and MSI subgroups. In conclusion, our study provides evidence of inter-tumor heterogeneity in the extent to which SCNAs occur in clinically diagnosed clear cell EC, and across molecular subgroups of EC. The co-occurrence of high-level SCNAs and TP53 mutations in some clear cell ECs is consistent with the view that a subset of clinically diagnosed clear cell ECs have molecular similarities to serous ECs.