Andrea Sboner

The genomic complexity of primary human prostate cancer

Prostate cancer is the second most common cause of male cancer deaths in the United States. However, the full range of prostate cancer genomic alterations is incompletely characterized. Here we present the complete sequence of seven primary human prostate cancers and their paired normal counterparts. Several tumours contained complex chains of balanced (that is, ‘copy-neutral’) rearrangements that occurred within or adjacent to known cancer genes. Rearrangement breakpoints were enriched near open chromatin, androgen receptor and ERG DNA binding sites in the setting of the ETS gene fusion TMPRSS2–ERG, but inversely correlated with these regions in tumours lacking ETS fusions. This observation suggests a link between chromatin or transcriptional regulation and the genesis of genomic aberrations. Three tumours contained rearrangements that disrupted CADM2, and four harboured events disrupting either PTEN (unbalanced events), a prostate tumour suppressor, or MAGI2 (balanced events), a PTEN interacting protein not previously implicated in prostate tumorigenesis. Thus, genomic rearrangements may arise from transcriptional or chromatin aberrancies and engage prostate tumorigenic mechanisms.

Integrative clinical genomics of advanced prostate cancer

Toward development of a precision medicine framework for metastatic, castration-resistant prostate cancer (mCRPC), we established a multi-institutional clinical sequencing infrastructure to conduct prospective whole-exome and transcriptome sequencing of bone or soft tissue tumor biopsies from a cohort of 150 mCRPC affected individuals. Aberrations of AR, ETS genes, TP53, and PTEN were frequent (40%-60% of cases), with TP53 and AR alterations enriched in mCRPC compared to primary prostate cancer. We identified new genomic alterations in PIK3CA/B, R-spondin, BRAF/RAF1, APC, β-catenin, and ZBTB16/PLZF. Moreover, aberrations of BRCA2, BRCA1, and ATM were observed at substantially higher frequencies (19.3% overall) compared to those in primary prostate cancers. 89% of affected individuals harbored a clinically actionable aberration, including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. This cohort study provides clinically actionable information that could impact treatment decisions for these affected individuals.

Molecular Characterization of Neuroendocrine Prostate Cancer and Identification of New Drug Targets

UNLABELLED Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of prostate cancer that most commonly evolves from preexisting prostate adenocarcinoma (PCA). Using Next Generation RNA-sequencing and oligonucleotide arrays, we profiled 7 NEPC, 30 PCA, and 5 benign prostate tissue (BEN), and validated findings on tumors from a large cohort of patients (37 NEPC, 169 PCA, 22 BEN) using IHC and FISH. We discovered significant overexpression and gene amplification of AURKA and MYCN in 40% of NEPC and 5% of PCA, respectively, and evidence that that they cooperate to induce a neuroendocrine phenotype in prostate cells. There was dramatic and enhanced sensitivity of NEPC (and MYCN overexpressing PCA) to Aurora kinase inhibitor therapy both in vitro and in vivo, with complete suppression of neuroendocrine marker expression following treatment. We propose that alterations in Aurora kinase A and N-myc are involved in the development of NEPC, and future clinical trials will help determine from the efficacy of Aurora kinase inhibitor therapy. SIGNIFICANCE We report on the largest in-depth molecular analysis of NEPC and provide new insight into molecular events involved in the progression of prostate cancer.

Integrative annotation of variants from 1092 humans: application to cancer genomics.

Introduction Plummeting sequencing costs have led to a great increase in the number of personal genomes. Interpreting the large number of variants in them, particularly in noncoding regions, is a current challenge. This is especially the case for somatic variants in cancer genomes, a large proportion of which are noncoding. Prioritization of candidate noncoding cancer drivers based on patterns of selection. (Step 1) Filter somatic variants to exclude 1000 Genomes polymorphisms; (2) retain variants in noncoding annotations; (3) retain those in “sensitive” regions; (4) prioritize those disrupting a transcription-factor binding motif and (5) residing near the center of a biological network; (6) prioritize ones in annotation blocks mutated in multiple cancer samples. Methods We investigated patterns of selection in DNA elements from the ENCODE project using the full spectrum of variants from 1092 individuals in the 1000 Genomes Project (Phase 1), including single-nucleotide variants (SNVs), short insertions and deletions (indels), and structural variants (SVs). Although we analyzed broad functional annotations, such as all transcription-factor binding sites, we focused more on highly specific categories such as distal binding sites of factor ZNF274. The greater statistical power of the Phase 1 data set compared with earlier ones allowed us to differentiate the selective constraints on these categories. We also used connectivity information between elements from protein-protein-interaction and regulatory networks. We integrated all the information on selection to develop a workflow (FunSeq) to prioritize personal-genome variants on the basis of their deleterious impact. As a proof of principle, we experimentally validated and characterized a few candidate variants. Results We identified a specific subgroup of noncoding categories with almost as much selective constraint as coding genes: “ultrasensitive” regions. We also uncovered a number of clear patterns of selection. Elements more consistently active across tissues and both maternal and paternal alleles (in terms of allele-specific activity) are under stronger selection. Variants disruptive because of mechanistic effects on transcription-factor binding (i.e. “motif-breakers”) are selected against. Higher network connectivity (i.e. for hubs) is associated with higher constraint. Additionally, many hub promoters and regulatory elements show evidence of recent positive selection. Overall, indels and SVs follow the same pattern as SNVs; however, there are notable exceptions. For instance, enhancers are enriched for SVs formed by nonallelic homologous recombination. We integrated these patterns of selection into the FunSeq prioritization workflow and applied it to cancer variants, because they present a strong contrast to inherited polymorphisms. In particular, application to ~90 cancer genomes (breast, prostate and medulloblastoma) reveals nearly a hundred candidate noncoding drivers. Discussion Our approach can be readily used to prioritize variants in cancer and is immediately applicable in a precision-medicine context. It can be further improved by incorporation of larger-scale population sequencing, better annotations, and expression data from large cohorts. Identifying Important Identifiers Each of us has millions of sequence variations in our genomes. Signatures of purifying or negative selection should help identify which of those variations is functionally important. Khurana et al. (1235587) used sequence polymorphisms from 1092 humans across 14 populations to identify patterns of selection, especially in noncoding regulatory regions. Noncoding regions under very strong negative selection included binding sites of some chromatin and general transcription factors (TFs) and core motifs of some important TF families. Positive selection in TF binding sites tended to occur in network hub promoters. Many recurrent somatic cancer variants occurred in noncoding regulatory regions and thus might indicate mutations that drive cancer. Regions under strong selection in the human genome identify noncoding regulatory elements with possible roles in disease. Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations (“ultrasensitive”) and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, “motif-breakers”). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.

The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer

The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription.

Novel YAP1-TFE3 fusion defines a distinct subset of epithelioid hemangioendothelioma

Conventional epithelioid hemangioendotheliomas (EHE) have a distinctive morphologic appearance and are characterized by a recurrent t(1;3) translocation, resulting in a WWTR1‐CAMTA1 fusion gene. We have recently encountered a fusion‐negative subset characterized by a somewhat different morphology, including focally well‐formed vasoformative features, which was further investigated for recurrent genetic abnormalities. Based on a case showing strong transcription factor E3 (TFE3) immunoreactivity, fluorescence in situ hybridization (FISH) analysis for TFE3 gene rearrangement was applied to the index case as well as to nine additional cases, selected through negative WWTR1‐CAMTA1 screening. A control group, including 18 epithelioid hemangiomas, nine pseudomyogenic HE, and three epithelioid angiosarcomas, was also tested. TFE3 gene rearrangement was identified in 10 patients, with equal gender distribution and a mean age of 30 years old. The lesions were located in somatic soft tissue in six cases, lung in three and one in bone. One case with available frozen tissue was tested by RNA sequencing and FusionSeq data analysis to detect novel fusions. A YAP1‐TFE3 fusion was thus detected, which was further validated by FISH and reverse transcription polymerase chain reaction (RT‐PCR). YAP1 gene rearrangements were then confirmed in seven of the remaining nine TFE3‐rearranged EHEs by FISH. No TFE3 structural abnormalities were detected in any of the controls. The TFE3‐rearranged EHEs showed similar morphologic features with at least focally, well‐formed vascular channels, in addition to a variably solid architecture. All tumors expressed endothelial markers, as well as strong nuclear TFE3. In summary, we are reporting a novel subset of EHE occurring in young adults, showing a distinct phenotype and YAP1‐TFE3 fusions.

Discovery of non-ETS gene fusions in human prostate cancer using next-generation RNA sequencing

Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date, little is known about the presence of non-ETS fusion events in prostate cancer. We used next-generation transcriptome sequencing (RNA-seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and four involving non-ETS genes such as CDKN1A (p21), CD9, and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency, but, interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement-prone phenotype.

Identification of a Disease-Defining Gene Fusion in Epithelioid Hemangioendothelioma

A newly identified gene fusion defines the vascular cancer epithelioid hemangioendothelioma and encodes a chimeric transcription factor. FISHing for a Gene Fusion Mother was right: There is a time and place for everything. And at the molecular level, inappropriate behavior can have consequences much more severe than being grounded. Using an unbiased deep-sequencing approach coupled with traditional chromosomal karyotyping, Tanas et al. now describe the genes involved in a fusion event that defines epithelioid hemangioendothelioma (EHE), a rare vascular cancer. This genetic aberration may instigate the bad behavior—an improper transcriptional program in endothelial cells. A rare sarcoma, EHE is difficult to diagnose because it shares many characteristics with normal endothelial cells and resembles other abnormal vascular neoplasms, such as epithelioid hemangioma, a benign condition, and epithelioid angiosarcoma, an aggressive vascular cancer. Treatment for patients with localized EHE includes surgical removal, when possible, or liver transplantation in the case of hepatic involvement, and there is no treatment for metastatic disease. To aid in diagnosis and decipher the pathological processes behind this mysterious cancer, researchers and clinicians need a defining biomarker for EHE. Traditional cytogenetic techniques for identifying the genes involved in a genetic translocation are labor-intensive, especially for a rare cancer for which no cell lines are available. So, Tanas et al. took a shortcut; the authors combined cytogenetic methods with deep transcriptome sequencing, which they used to search in an unbiased way for the product of the t(1;3)(p36;q25) chromosomal translocation characteristic of EHE. The translocation involved two genes, WWTR1, which encodes a transcriptional coactivator that is highly expressed in endothelial cells, and CAMTA1, a DNA binding transcriptional regulatory protein that is normally expressed during brain development. The WWTR1/CAMTA1 gene fusion contains the strong endothelial cell promoter of WWTR1, which may drive the inappropriate expression of a protein-encoding fragment of CAMTA1 in endothelial cells. The authors suggest that this promoter switch initiates an ill-suited and ill-timed transcriptional program that may play a role in cancer biology. If this is the case, then the chimeric WWTR1/CAMTA1 transcription factor may represent a therapeutic target for EHE-specific drugs. To aid in disease diagnosis, Tanas et al. also devised a sensitive and specific fluorescence in situ hybridization assay to detect the EHE translocation. Together, these tools should teach researchers about the biology and prognosis of this rare cancer and eventually help bring the bad behavior under control. Integrating transcriptomic sequencing with conventional cytogenetics, we identified WWTR1 (WW domain–containing transcription regulator 1) (3q25) and CAMTA1 (calmodulin-binding transcription activator 1) (1p36) as the two genes involved in the t(1;3)(p36;q25) chromosomal translocation that is characteristic of epithelioid hemangioendothelioma (EHE), a vascular sarcoma. This WWTR1/CAMTA1 gene fusion is under the transcriptional control of the WWTR1 promoter and encodes a putative chimeric transcription factor that joins the amino terminus of WWTR1, a protein that is highly expressed in endothelial cells, in-frame to the carboxyl terminus of CAMTA1, a protein that is normally expressed only in brain. Thus, CAMTA1 expression is activated inappropriately through a promoter-switch mechanism. The gene fusion is present in virtually all EHEs tested but is absent from all other vascular neoplasms, demonstrating it to be a disease-defining genetic alteration. A sensitive and specific break-apart fluorescence in situ hybridization assay was also developed to detect the translocation and will assist in the evaluation of this diagnostically challenging neoplasm. The chimeric WWTR1/CAMTA1 transcription factor may represent a therapeutic target for EHE and offers the opportunity to shed light on the functions of two poorly characterized proteins.

PRC2 is recurrently inactivated through EED or SUZ12 loss in malignant peripheral nerve sheath tumors

Malignant peripheral nerve sheath tumors (MPNSTs) represent a group of highly aggressive soft-tissue sarcomas that may occur sporadically, in association with neurofibromatosis type I (NF1 associated) or after radiotherapy. Using comprehensive genomic approaches, we identified loss-of-function somatic alterations of the Polycomb repressive complex 2 (PRC2) components (EED or SUZ12) in 92% of sporadic, 70% of NF1-associated and 90% of radiotherapy-associated MPNSTs. MPNSTs with PRC2 loss showed complete loss of trimethylation at lysine 27 of histone H3 (H3K27me3) and aberrant transcriptional activation of multiple PRC2-repressed homeobox master regulators and their regulated developmental pathways. Introduction of the lost PRC2 component in a PRC2-deficient MPNST cell line restored H3K27me3 levels and decreased cell growth. Additionally, we identified frequent somatic alterations of CDKN2A (81% of all MPNSTs) and NF1 (72% of non-NF1-associated MPNSTs), both of which significantly co-occur with PRC2 alterations. The highly recurrent and specific inactivation of PRC2 components, NF1 and CDKN2A highlights their critical and potentially cooperative roles in MPNST pathogenesis.

FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data.

We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.