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Highlights • The lncRNA SCHLAP1 predicts poor prognosis in multifocal primary prostate cancer • Expression of SCHLAP1 is heterogeneous within and between different malignant foci • Multiple samples per patient is crucial, otherwise high SCHLAP1 may be overlooked • High SCHLAP1 is associated with reactive stroma and other aggressive features, In primary prostate cancer, the common multifocality and heterogeneity are major obstacles in finding robust prognostic tissue biomarkers. The long noncoding RNA SCHLAP1 has been suggested, but its prognostic value has not been investigated in the context of tumor heterogeneity. In the present study, expression of SCHLAP1 was investigated using real-time RT-PCR in a multisampled series of 778 tissue samples from radical prostatectomies of 164 prostate cancer patients (median follow-up time 7.4 y). The prognostic value of SCHLAP1 was evaluated with biochemical recurrence as endpoint. In total, 29% of patients were classified as having high expression of SCHLAP1 in at least one malignant sample. Among these, inter- and intrafocal heterogeneity was detected in 72% and 56%, respectively. High expression of SCHLAP1 was shown to be a predictor of biochemical recurrence in both uni- and multivariable cox regression analyses (P < 0.001 and P = 0.02). High expression of SCHLAP1 was also significantly associated with adverse clinicopathological characteristics, including grade group, high pT stage, invasive cribriform growth/intraductal carcinoma of the prostate, and reactive stroma. In conclusion, high expression of SCHLAP1 in at least one malignant sample is a robust prognostic biomarker in primary prostate cancer. For the first time, high SCHLAP1 expression has been associated with the aggressive histopathologic feature reactive stroma. The expression of SCHLAP1 is highly heterogeneous, and analysis of multiple samples is therefore crucial in determination of the SCHLAP1 status of a patient.

Background Most primary prostate cancers are multifocal with individual tumors harboring different aggressiveness; however, the genomic heterogeneity among these tumors is poorly understood. Objective To better understand the biological basis for clinical variability among different lesions, we sought to comprehensively characterize the heterogeneity of somatic gene mutations in multifocal prostate cancer. Design, setting, and participants High-coverage whole-exome sequencing of 153 frozen tissue samples, taken from two to three distinct tumor foci and one non-cancerous area from each of 41 patients, covering a total of 89 tumor foci. Outcome measurements and statistical analysis State-of-the-art bioinformatics tools for mutation calling and copy number determination from whole-exome sequencing data. Results and limitations We found a very high degree of interfocal heterogeneity among tumors, that is, 76% of pairwise-compared tumor foci from the same prostatectomy specimen had no point mutations in common and DNA copy number changes were rarely shared across cancer foci. The few point mutations shared across tumor foci were seldom in cancer-critical genes. Conclusions In this first large genomic heterogeneity study of primary prostate cancer, we observe that different tumor foci within the same patient are genetically distinct, only rarely sharing any somatic gene mutations, including those in cancer driver genes. This heterogeneity affects how genomics-based management of prostate cancer can be implemented, as information from all tumor foci is necessary to draw valid conclusions about the cancer's genomic alterations. Patient summary Most primary prostate cancers consist of multiple tumors within the same organ, but little is known about their relationships. We have compared the sets of gene mutations among such tumors and found that they only exceptionally have any in common. This will influence treatment decisions in the future as each tumor's mutations will render it unique and have to be considered to gain the best treatment results.

Prostate cancer is a clinically and pathologically heterogeneous disease with a broad spectrum of molecular abnormalities in the genome and transcriptome. One key feature is the involvement of chromosomal rearrangements creating fusion genes. Recent RNA-sequencing technology has uncovered that fusions which are not caused by chromosomal rearrangements, but rather meditated at transcription level, are common in both healthy and diseased cells. Such fusion transcripts have been proven highly associated with prostate cancer development and progression. To discover novel fusion transcripts, we analyzed RNA sequencing data from 44 primary prostate tumors and matched benign tissues from The Cancer Genome Atlas. Twenty-one high-confident candidates were significantly enriched in malignant vs. benign samples. Thirteen of the candidates have not previously been described in prostate cancer, and among them, five long intergenic non-coding RNAs are involved as fusion partners. Their expressions were validated in 50 additional prostate tumor samples and seven prostate cancer cell lines. For four fusion transcripts, we found a positive correlation between their expression and the expression of the 3' partner gene. Among these, differential exon usage and qRT-PCR analyses in particular support that SLC45A3-ELK4 is mediated by an RNA polymerase read-through mechanism.

Prostate cancer is a highly heterogeneous disease and typically multiple distinct cancer foci are present at primary diagnosis. Molecular classification of prostate cancer can potentially aid the precision of diagnosis and treatment. A promising genomic classifier was published by The Cancer Genome Atlas (TCGA), successfully classifying 74% of primary prostate cancers into seven groups based on one cancer sample per patient. Here, we explore the clinical usefulness of this classification by testing the classifier’s performance in a multifocal context. We analyzed 106 cancer samples from 85 distinct cancer foci within 39 patients. By somatic mutation data from whole-exome sequencing and targeted qualitative and quantitative gene expression assays, 31% of the patients were uniquely classified into one of the seven TCGA classes. Further, different samples from the same focus had conflicting classification in 12% of the foci. In conclusion, the level of both intra- and interfocal heterogeneity is extensive and must be taken into consideration in the development of clinically useful molecular classification of primary prostate cancer.

There is a great need to identify new and better prognostic and predictive biomarkers to stratify prostate cancer patients for optimal treatment. The aims of this study were to characterize the exp ...

Author(s): Cornish-Bowden, Athel; Cornish-Bowden, Athel; Rasnick, David; Heng, Henry H; Horne, Steven; Abdallah, Batoul; Liu, Guo; Ye, Christine J; Bloomfield, Mathew; Vincent, Mark D; Aldaz, C Marcelo; Karlsson, Jenny; Valind, Anders; Jansson, Caroline; Gisselsson, David; Graves, Jennifer A Marshall; Stepanenko, Aleksei A; Andreieva, Svitlana V; Korets, Kateryna V; Mykytenko, Dmytro O; Huleyuk, Nataliya L; Baklaushev, Vladimir P; Kovaleva, Oksana A; Chekhonin, Vladimir P; Vassetzky, Yegor S; Avdieiev, Stanislav S; Bakker, Bjorn; Taudt, Aaron S; Belderbos, Mirjam E; Porubsky, David; Spierings, Diana CJ; de Jong, Tristan V; Halsema, Nancy; Kazemier, Hinke G; Hoekstra-Wakker, Karina; Bradley, Allan; de Bont, Eveline SJM; van den Berg, Anke; Guryev, Victor; Lansdorp, Peter M; Tatche, Maria Colome; Foijer, Floris; Liehr, Thomas; Baudoin, Nicolaas C; Nicholson, Joshua M; Soto, Kimberly; Quintanilla, Isabel; Camps, Jordi; Cimini, Daniela; Durrbaum, M; Donnelly, N; Passerini, V; Kruse, C; Habermann, B; Storchova, Z; Mandrioli, Daniele; Belpoggi, Fiorella; Silbergeld, Ellen K; Perry, Melissa J; Skotheim, Rolf I; Lovf, Marthe; Johannessen, Bjarne; Hoff, Andreas M; Zhao, Sen; SveeStromme, Jonas M; Sveen, Anita; Lothe, Ragnhild A; Hehlmann, R; Voskanyan, A; Fabarius, A; Bocking, Alfred; Biesterfeld, Stefan; Berynskyy, Leonid; Borgermann, Christof; Engers, Rainer; Dietz, Josef; Fritz, A; Sehgal, N; Vecerova, J; Stojkovicz, B; Ding, H; Page, N; Tye, C; Bhattacharya, S; Xu, J

Colorectal cancer is a global health challenge with high incidence rate and mortality. The patients' prognosis is strongly associated with disease stage and currently there is a need for improved prognostic and predictive biomarkers. In this study, novel colorectal cancer-specific transcript structures were nominated from whole transcriptome sequencing of seven colorectal cancer cell lines, two primary colorectal carcinomas with corresponding normal colonic mucosa and 16 normal tissues. The nominated transcripts were combined with gene level outlier expression analyses in a cohort of 505 colorectal cancers to identify biomarkers with capacity to stratify colorectal cancer subgroups. The transcriptome sequencing data and outlier expression analysis revealed 11 novel colorectal cancer-specific exon-exon junctions, of which 3 were located in the gene VNN1. The junctions within VNN1 were further characterized using rapid amplification of cDNA ends (RACE) and the prevalence of the subsequently characterized novel transcript, VNN1-AB, was investigated by real-time RT-PCR in 291 samples of miscellaneous origins. VNN1-AB was not present in any of the 43 normal colorectal tissue samples investigated, but in 5 of the 6 polyps, and 102 of the 136 (75%) colorectal cancers. We have identified a novel transcript of the VNN1 gene, with an organ-confined complete specificity for colorectal neoplasia.

Introduction Prostate cancer is the most common cancer type among men in the Western developed world. The majority of cases are multifocal, with several distinct tumours within the same gland. It is of particular interest to classify prostate cancer into different molecular subgroups to stratify it´s aggressiveness. Recently, The Cancer Genome Atlas (TCGA) proposed seven subtypes based on the expression of particular fusion genes or fusion gene partners, or mutation in particular genes. However, TCGA based their classification on a single sample per patient and did therefore not take the multifocal nature of the disease into account. We have therefore utilised the proposed subtypes on a large series of multifocal primary prostate cancers to understand the distribution and heterogeneity of subtypes within each prostate gland. Material and methods In this study, 153 tumour and benign samples from 41 prostatectomies performed between 2010 and 2012 at Oslo university hospital were selected. The samples represent 89 distinct tumour foci, with 2–3 included tumours per patient. All samples were analysed with high-coverage whole exome sequencing. Mutations relevant for the molecular classification were validated with PCR and Sanger sequencing. Expression levels and fusion transcripts were investigated in all samples with regular and real-time RT-PCR. Results and discussions Our results show both intra- and interfocal heterogeneity in the observed subtypes. For individual samples, 60% can be classified into one defined subtype. However, heterogeneity is observed in 47% of patients where tumours belong to more than one of the proposed subtypes. Investigating individual tumour foci, 53% belong to one subtype whereas the rest are classified into either multiple subtypes (12%) or do not harbour any of the molecular traits used in the proposed classification (35%). Interestingly, classification of samples into more than one subtype was mainly due to overexpression or fusion of multiple ETS-transcription factors (7%). Conclusion In this study, we observe a large degree of genomic dissonance both within and between tumour foci in the same prostate, resulting in heterogeneity in the classification of individual tumours. In fact, in 47% of the cases, patients can be classified into several subtypes, depending on which tumour the sample originates from. This heterogeneity greatly complicates the implementation of this particular classification in a clinical setting.

// Andreas M. Hoff 1, 2, 3, * , Bjarne Johannessen 1, 2, 3, * , Sharmini Alagaratnam 1, 2, 3 , Sen Zhao 1, 2, 3 , Torfinn Nome 1, 2, 3 , Marthe Lovf 1, 2, 3 , Anne C. Bakken 1, 2, 3 , Merete Hektoen 1, 2, 3 , Anita Sveen 1, 2, 3 , Ragnhild A. Lothe 1, 2, 3 , Rolf I. Skotheim 1, 2, 3 1 Department of Molecular Oncology, Institute for Cancer Research, Oslo University Hospital-Norwegian Radium Hospital, Oslo, Norway 2 KG Jebsen Colorectal Cancer Research Centre, Oslo University Hospital, Oslo, Norway 3 Centre for Cancer Biomedicine, University of Oslo, Oslo, Norway * These authors have contributed equally to this work Correspondence to: Rolf I. Skotheim, e-mail: rolf.i.skotheim@rr-research.no Keywords: colorectal cancer, fusion genes, transcript variants, RACE-seq, splicing Received: July 01, 2015 Accepted: September 30, 2015 Published: October 12, 2015 ABSTRACT With an annual estimated incidence of 1.4 million, and a five-year survival rate of 60%, colorectal cancer (CRC) is a major clinical burden. To identify novel RNA variants in CRC, we analyzed exon-level microarray expression data from a cohort of 202 CRCs. We nominated 25 genes with increased expression of their 3′ parts in at least one cancer sample each. To efficiently investigate underlying transcript structures, we developed an approach using rapid amplification of cDNA ends followed by high throughput sequencing (RACE-seq). RACE products from the targeted genes in 23 CRC samples were pooled together and sequenced. We identified VWA2 - TCF7L2 , DHX35 - BPIFA2 and CASZ1 - MASP2 as private fusion events, and novel transcript structures for 17 of the 23 other candidate genes. The high-throughput approach facilitated identification of CRC specific RNA variants. These include a recurrent read-through fusion transcript between KLK8 and KLK7 , and a splice variant of S100A2 . Both of these were overrepresented in CRC tissue and cell lines from external RNA-seq datasets.

Prostate cancer is the most common cancer type among men in the Western world. Most prostate cancers are multifocal with individual tumors harboring different aggressiveness. In recent genomics studies, the multifocal nature of prostate cancer has been investigated only in small sample cohorts. Here we have investigated the intra-organ mutational spectra of multiple tumors from a large cohort of prostate cancer patients. From radical prostatectomies performed between 2010 and 2012 at Oslo University Hospital, 43 prostatectomy specimens with multiple and clearly separated tumors were identified based on histology. From each of these prostatectomy specimens, DNA from frozen samples from 2-3 different tumor foci and corresponding normal tissue samples were analyzed by high-coverage whole-exome sequencing, adding up to a total of 159 samples. We identified 3093 somatic substitutions, insertions and deletions, with an average of 27 alterations per tumor sample. Both known and novel significantly mutated genes were identified and their distribution among different tumor foci from the same prostate was examined. Mutations in genes such as SPOP, MED12, and FOXA1 have previously been identified in prostate cancer and were also found to be frequently mutated in this cohort. However, the same mutations were rarely found in multiple tumor foci within the same prostate. In fact, for 13 out of the 43 examined patients there were no common mutations among tumors from the same prostate. For 12 patients, we found only one overlapping mutation among tumor foci. Whereas the overall list of mutated genes (n = 2101) overlap significantly with the 594 genes of the Cancer Gene Census (100/594; p=9.6e-06), this was not the case for 142 genes with overlapping mutations among different tumor foci (2/594; p=0.63). This indicates that the overlapping mutations are not typical cancer driving genes. To conclude, results from exome sequencing of multifocal prostate cancer show a large degree of heterogeneity in genomic alterations between different tumor foci within the same prostate. With very few common inter-foci mutations, an implementation of genome-based personalized prostate cancer medicine will require sampling of all tumor foci to tailor optimal treatment. Citation Format: Marthe Løvf, Sen Zhao, Ulrika Axcrona, Bjarne Johannesen, Andreas M. Hoff, Anne Cathrine Bakken, Kristina Totland Carm, Ola Myklebost, Leonardo A. Meza-Zepeda, Agnes K. Lie, Karol Axcrona, Ragnhild A. Lothe, Rolf I. Skotheim. Multifocal prostate cancer has high degree of genomic heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1745. doi:10.1158/1538-7445.AM2017-1745

Colorectal cancer is a global health challenge with high incidence rate and mortality. The patients' prognosis is strongly associated with disease stage and currently there is a need for improved prognostic and predictive biomarkers. In this study, novel colorectal cancer-specific transcript structures were nominated from whole transcriptome sequencing of seven colorectal cancer cell lines, two primary colorectal carcinomas with corresponding normal colonic mucosa and 16 normal tissues. The nominated transcripts were combined with gene level outlier expression analyses in a cohort of 505 colorectal cancers to identify biomarkers with capacity to stratify colorectal cancer subgroups. The transcriptome sequencing data and outlier expression analysis revealed 11 novel colorectal cancer-specific exon-exon junctions, of which 3 were located in the gene VNN1. The junctions within VNN1 were further characterized using rapid amplification of cDNA ends (RACE) and the prevalence of the subsequently characterized novel transcript, VNN1-AB, was investigated by real-time RT-PCR in 291 samples of miscellaneous origins. VNN1-AB was not present in any of the 43 normal colorectal tissue samples investigated, but in 5 of the 6 polyps, and 102 of the 136 (75%) colorectal cancers. We have identified a novel transcript of the VNN1 gene, with an organ-confined complete specificity for colorectal neoplasia.

Sarcomas are relatively rare malignancies and include a large number of histological subgroups. Based on morphology alone, the differential diagnoses of sarcoma subtypes can be challenging, but the identification of specific fusion genes aids correct diagnostication. The presence of individual fusion products are routinely investigated in Pathology labs. However, the methods used are time-consuming and based on prior knowledge about the expected fusion gene and often the most likely break-point. In this study, 16 sarcoma samples, representing seven different sarcoma subtypes with known fusion gene status from a diagnostic setting, were investigated using a fusion gene microarray. The microarray was designed to detect all possible exon-exon breakpoints between all known fusion genes in a single analysis. An automated scoring of the microarray data from the 38 known sarcoma-related fusion genes identified the correct fusion gene among the top-three hits in 11 of the samples. The analytical sensitivity may be further optimised, but we conclude that a sarcoma-fusion gene microarray is suitable as a time-saving screening tool to identify the majority of the correct fusion genes.

Neoplasms frequently present structural chromosomal aberrations that can alter the level of expression of a protein or to the expression of an aberrant chimeric protein. In the thyroid, the PAX8-PPARG fusion is present in the neoplastic lesions that have a follicular architecture—follicular thyroid carcinoma (FTC) and follicular variant of papillary thyroid carcinoma (FVPTC), and less frequently in follicular thyroid adenoma (FTA), while the presence of RET/PTC fusions are largely restricted to papillary thyroid carcinoma (PTC). The ability to detect fusion genes is relevant for a correct diagnosis and for therapy. We have developed a new fusion gene microarray-based approach for simultaneous analysis of all known and predicted fusion gene variants. We did a comprehensive screen for 548 known and putative fusion genes in 27 samples of thyroid tumors and three positive controls—one thyroid cancer cell line (TPC-1) and two PTCs with known CCDC6-RET (alias RET/PTC1) fusion gene, using this microarray. Within the thyroid tumors tested, only well known, previously reported fusion genes in thyroid oncology were identified. Our results reinforce the pathogenic role played by RET/PTC1, RET/PTC3, and PAX8-PPARG fusion genes in thyroid tumorigenesis. © 2012 Wiley Periodicals, Inc.

Detection of fusion genes for diagnostic purposes and as a guide to treatment is well-established in hematological malignancies, and the prevalence of fusion genes in epithelial cancers is also increasingly appreciated. To study whether established fusion genes are present within additional cancer types, we have used an updated version of our fusion gene microarray in a systematic survey of reported fusion genes in multiple cancer types. We assembled a comprehensive database of published fusion genes, including those reported only in individual studies and samples, and fusion genes resulting from deep sequencing of cancer genomes and transcriptomes. From the total set of 548 fusion genes, we designed 599,839 oligonucleotides, targeting both chimeric transcript junctions as well as sequences internal to each of the fusion gene partners. We investigated the presence of fusion genes in a series of 67 cell lines representing 15 different cancer types. Data from ten leukemia cell lines with known fusion gene status were used to develop an automated scoring algorithm, and in five cell lines the correct fusion gene was the top scoring hit, and one came second. Two additional fusion genes, BCAS4-BCAS3 in the MCF-7 breast cancer cell line and CCDC6-RET in the TPC-1 thyroid cancer cell line were validated as true positive fusion transcripts. However, these fusion genes were not new to these cancer types, and none of 548 fusion genes were identified from a novel cancer type. We therefore find it unlikely that the assayed fusion genes are commonly present across multiple cancer types.