Naoki Kitabayashi

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 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.

MicroRNA analysis as a potential diagnostic tool for papillary thyroid carcinoma

MicroRNA (miRNA) microarray analysis has consistently found altered expression of miRNAs in thyroid tumors, suggesting their roles in thyroid carcinogenesis. To explore whether this differential expression can be used as a diagnostic tool in surgical pathology and fine-needle aspirate (FNA) specimens, the expression of selected miRNA was evaluated by quantitative RT-PCR, using total RNA from 84 formalin-fixed paraffin-embedded tissues and 40 ex vivo aspirate specimens. miRNA from all paraffin-embedded tissues and all but one FNA sample were found to be analyzable, with paraffin sections yielding better miRNA quality. Preliminary analysis of 6 miRNAs in 10 papillary thyroid carcinoma and 10 follicular adenoma identified significant overexpression of miR-146b, -221, and -222 in papillary thyroid carcinoma (P<0.02), but not miR-146a, -155, or -187 (P>0.08). The expression of these first three miRNAs was examined in a series of 5 normal thyroid, 11 hyperplastic nodules, 24 follicular adenoma, 27 classical papillary thyroid carcinoma, 5 follicular variant papillary thyroid carcinoma, 2 follicular carcinoma, and 10 encapsulated follicular lesions with partial nuclear features of papillary carcinoma. Results showed miR-146b to be most consistently overexpressed in both classical papillary carcinoma and follicular variants, whereas all other groups showed lower expression at a similar level (P<0.001 for pair-wise comparisons between papillary carcinoma and all other groups). Follicular lesions with partial features of papillary carcinoma all showed low miR-146b levels similar to other non-papillary carcinoma groups, suggesting that they are biologically distinctive from papillary carcinoma. miR-221 and miR-222 also showed higher expression in papillary carcinoma, but with substantial overlaps with the other groups. When applied to 40 FNA samples of various lesions, only miR-146b and miR-222 persisted as distinguishing markers for papillary carcinoma. We concluded that miRNAs, particularly miR-146b, might potentially be adjunct markers for diagnosing papillary thyroid carcinoma in both FNA and surgical pathology specimens.

AlleleSeq: analysis of allele‐specific expression and binding in a network framework

To study allele‐specific expression (ASE) and binding (ASB), that is, differences between the maternally and paternally derived alleles, we have developed a computational pipeline (AlleleSeq). Our pipeline initially constructs a diploid personal genome sequence (and corresponding personalized gene annotation) using genomic sequence variants (SNPs, indels, and structural variants), and then identifies allele‐specific events with significant differences in the number of mapped reads between maternal and paternal alleles. There are many technical challenges in the construction and alignment of reads to a personal diploid genome sequence that we address, for example, bias of reads mapping to the reference allele. We have applied AlleleSeq to variation data for NA12878 from the 1000 Genomes Project as well as matched, deeply sequenced RNA‐Seq and ChIP‐Seq data sets generated for this purpose. In addition to observing fairly widespread allele‐specific behavior within individual functional genomic data sets (including results consistent with X‐chromosome inactivation), we can study the interaction between ASE and ASB. Furthermore, we investigate the coordination between ASE and ASB from multiple transcription factors events using a regulatory network framework. Correlation analyses and network motifs show mostly coordinated ASB and ASE.

Gene fusions between TMPRSS2 and ETS family genes in prostate cancer: frequency and transcript variant analysis by RT-PCR and FISH on paraffin-embedded tissues.

Recurrent gene fusions between TMPRSS2 and ETS family genes have recently been shown to occur at a high frequency in prostate cancer. In this study, we used formalin-fixed paraffin-embedded tissue and evaluated both TMPRSS2-ERG and TMPRSS2-ETV1 fusions by reverse transcription polymerase chain reaction (RT-PCR) and fluorescence in situ hybridization (FISH). The results were correlated to overexpression of the downstream ERG and ETV1 sequences. Of 82 cases examined, TMPRSS2-ETV1 fusion was seen in only one case, by FISH. In comparison, TMPRSS2-ERG fusion was documented in 35 cases (43%) by either RT-PCR or FISH. Deletion, rather than translocation, was found to be the main mechanism for TMPRSS2-ERG gene fusion (81 vs 19%). RT-PCR and FISH results correlated well, with most positive cases resulting in overexpression of downstream ERG sequences. Several TMPRSS2-ERG fusion transcript variants were identified, most of which are predicted to encode truncated ERG proteins. Prostate cancer of Gleasons scores 6 or 7 had more frequent TMPRSS2-ERG fusions than higher-grade tumors, but this difference was not statistically significant (P=0.42). On the other hand, mucin-positive carcinomas more often harbor such gene fusions when compared to mucin-negative tumors (P=0.004). These morphological correlates, and more importantly the potential correlation of such fusions to clinical outcome and treatment responses, should be further explored.

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.

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.

Recurrent NCOA2 gene rearrangements in congenital/infantile spindle cell rhabdomyosarcoma

Spindle cell rhabdomyosarcoma (RMS) is a rare form of RMS with different clinical characteristics between children and adult patients. Its genetic hallmark remains unknown and it remains debatable if there is pathogenetic relationship between the spindle cell and the so‐called sclerosing RMS. We studied two pediatric and one adult spindle cell RMS by next generation RNA sequencing and FusionSeq data analysis to detect novel fusions. An SRF‐NCOA2 fusion was detected in a spindle cell RMS from the posterior neck in a 7‐month‐old child. The fusion matched the tumor karyotype and was confirmed by FISH and RT‐PCR, which showed fusion of SRF exon 6 to NCOA2 exon 12. Additional 14 spindle cell (from 8 children and 6 adults) and 4 sclerosing (from 2 children and 2 adults) RMS were tested by FISH for the presence of abnormalities in NCOA2, SRF, as well as for PAX3 and NCOA1. NCOA2 rearrangements were found in two additional spindle cell RMS from a 3‐month‐old and a 4‐week‐old child. In the latter tumor, TEAD1 was identified by rapid amplification of cDNA ends (RACE) to be the NCOA2 gene fusion partner. None of the adult tumors were positive for NCOA2 rearrangement. Despite similar histomorphology in adults and young children, these results suggest that spindle cell RMS is a heterogeneous disease genetically as well as clinically. Our findings also support a relationship between NCOA2‐rearranged spindle cell RMS occurring in young childhood and the so‐called congenital RMS, which often displays rearrangements at 8q13 locus (NCOA2).

Testing mutual exclusivity of ETS rearranged prostate cancer

Prostate cancer is a clinically heterogeneous and multifocal disease. More than 80% of patients with prostate cancer harbor multiple geographically discrete cancer foci at the time of diagnosis. Emerging data suggest that these foci are molecularly distinct consistent with the hypothesis that they arise as independent clones. One of the strongest arguments is the heterogeneity observed in the status of E26 transformation specific (ETS) rearrangements between discrete tumor foci. The clonal evolution of individual prostate cancer foci based on recent studies demonstrates intertumoral heterogeneity with intratumoral homogeneity. The issue of multifocality and interfocal heterogeneity is important and has not been fully elucidated due to lack of the systematic evaluation of ETS rearrangements in multiple tumor sites. The current study investigates the frequency of multiple gene rearrangements within the same focus and between different cancer foci. Fluorescence in situ hybridization (FISH) assays were designed to detect the four most common recurrent ETS gene rearrangements. In a cohort of 88 men with localized prostate cancer, we found ERG, ETV1, and ETV5 rearrangements in 51% (44/86), 6% (5/85), and 1% (1/86), respectively. None of the cases demonstrated ETV4 rearrangements. Mutual exclusiveness of ETS rearrangements was observed in the majority of cases; however, in six cases, we discovered multiple ETS or 5′ fusion partner rearrangements within the same tumor focus. In conclusion, we provide further evidence for prostate cancer tumor heterogeneity with the identification of multiple concurrent gene rearrangements.

MicroRNA Expression Aids the Preoperative Diagnosis of Pancreatic Ductal Adenocarcinoma

Objectives This study aimed to evaluate microRNA (miRNA) expression in pancreatic resection specimens and fine needle aspiration biopsies and determine which, if any, miRNAs aid the distinction between benign and malignant pancreatic tumors in limited cytology material. Methods Resection specimens containing adenocarcinoma (n = 17), intraductal papillary mucinous neoplasms (n = 11), and nonneoplastic tissues (n = 15) were evaluated for miR-21, miR-221, miR-100, miR-155, and miR-181b expression by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), and a subset of carcinomas and intraductal papillary mucinous neoplasms was analyzed with miRNA microarrays. Cellblocks containing carcinoma (n = 26) or benign pancreatic lesions (n = 11) from fine needle aspiration biopsies were subjected to qRT-PCR for miR-21, miR-221, miR-181b, miR-196a, and miR-217. Results Carcinomas showed higher expression of miR-21, miR-221, miR-155, miR-100, and miR-181b than benign lesions by qRT-PCR, and overexpression of miR-21, miR-221, and miR-181b was confirmed by microarray analysis. Cellblocks containing carcinoma showed higher expression of miR-21, miR-221, and miR-196a than those from benign lesions (P < 0.001, P = 0.009, and P < 0.001, respectively). Conclusions Pancreatic ductal adenocarcinomas show differential expression of miRNAs compared to benign pancreatic lesions. A select panel of miRNAs aids the distinction between pancreatic lesions in cytology specimens.