PBX3 is a putative biomarker of aggressive 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 expression profile of pre-B cell leukemia homeobox (PBX) transcription factors in prostate cancer with an emphasis on investigating whether PBX3 harbours any prognostic value. The expression profile of PBX3 and PBX1 in prostate tissue was determined by immunohistochemical and immunoblot analysis. Furthermore, the expression of PBX3 transcript variants was analyzed by RT-PCR, NanoString Technologies®, and by analyzing RNA sequence data. The potential of PBX3 to predict prognosis, either at mRNA or protein level, was studied in four independent cohorts. PBX3 was mainly expressed in the nucleus of normal prostate basal cells, while it showed cytosolic expression in prostatic intraepithelial neoplasia and cancer cells. We detected four PBX3 transcript variants in prostate tissue. Competing risk regression analysis revealed that high PBX3 expression was associated with slower progression to castration resistant prostate cancer (sub-hazard ratio (SHR) 0.18, 95% CI: 0.081-0.42, p values < 0.001). PBX3 expression had a high predictive accuracy (area under the curve (AUC) = 0.82) when combined with Gleason score and age. Patients undergoing radical prostatectomy, with high levels of PBX3 mRNA, had improved prostate cancer specific survival compared to patients expressing low levels (SHR 0.21, 95% CI: 0.46-0.93, p values < 0.001, and AUC = 0.75). Our findings strongly indicate that PBX3 has potential as a biomarker, both as part of a larger gene panel and as an immunohistochemical marker, for aggressive prostate cancer.

A novel transcript, VNN1-AB, as a biomarker for colorectal cancer.

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.

Survey of 548 oncogenic fusion transcripts in thyroid tumors supports the importance of the already established thyroid fusions 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.

Fusion gene microarray reveals cancer type-specificity among fusion genes.

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.

In situ expression of ERG protein in the context of tumor heterogeneity identifies prostate cancer patients with inferior prognosis.

Prognostic biomarkers for prostate cancer are needed to improve prediction of disease course and guide treatment decisions. However, biomarker development is complicated by the common multifocality and heterogeneity of the disease. We aimed to determine the prognostic value of candidate biomarkers transcriptional regulator ERG and related ETS family genes, while considering tumor heterogeneity. In a multisampled, prospective, and treatment-naïve radical prostatectomy cohort from one tertiary center (2010-2012, median follow-up 8.1 years), we analyzed ERG protein (480 patients; 2047 tissue cores), and RNA of several ETS genes in a subcohort (165 patients; 778 fresh-frozen tissue samples). Intra- and interfocal heterogeneity was identified in 29% and 33% (ERG protein) and 39% and 27% (ETS RNA) of patients, respectively. ERG protein and ETS RNA was identified exclusively in a nonindex tumor in 31% and 32% of patients, respectively. ERG protein demonstrated independent prognostic value in predicting biochemical (P = 0.04) and clinical recurrence (P = 0.004) and appeared to have greatest prognostic value for patients with Grade Groups 4-5. In conclusion, when heterogeneity is considered, ERG protein is a robust prognostic biomarker for prostate cancer.

High expression of SCHLAP1 in primary prostate cancer is an independent predictor of biochemical recurrence, despite substantial heterogeneity.

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.

Interfocal heterogeneity challenges the clinical usefulness of molecular classification of primary prostate cancer.

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.

Multifocal Primary Prostate Cancer Exhibits High Degree of Genomic Heterogeneity.

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.

Novel transcription-induced fusion RNAs in prostate cancer.

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.

Novel RNA variants in colorectal cancers.

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.

Assessment of fusion gene status in sarcomas using a custom made fusion gene microarray.

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.

Novel 5' fusion partners of ETV1 and ETV4 in prostate cancer.

Gene fusions involving the erythroblast transformation-specific (ETS) transcription factors ERG, ETV1, ETV4, ETV5, and FLI1 are a common feature of prostate carcinomas (PCas). The most common upstream fusion partner described is the androgen-regulated prostate-specific gene TMPRSS2, most frequently with ERG, but additional 5' fusion partners have been described. We performed 5' rapid amplification of cDNA ends in 18 PCas with ETV1, ETV4, or ETV5 outlier expression to identify the 5' fusion partners. We also evaluated the exon-level expression profile of these ETS genes in 14 cases. We identified and confirmed by fluorescent in situ hybridization (FISH) and reverse transcription-polymerase chain reaction the two novel chimeric genes OR51E2-ETV1 and UBTF-ETV4 in two PCas. OR51E2 encodes a G-protein-coupled receptor that is overexpressed in PCas, whereas UBTF is a ubiquitously expressed gene encoding an HMG-box DNA-binding protein involved in ribosome biogenesis. We additionally describe two novel gene fusion combinations of previously described genes, namely, SLC45A3-ETV4 and HERVK17-ETV4. Finally, we found one PCa with TMPRSS2-ETV1, one with C15orf21-ETV1, one with EST14-ETV1, and two with 14q133-q21.1-ETV1. In nine PCas (eight ETV1 and one ETV5), exhibiting ETS outlier expression and genomic rearrangement detected by FISH, no 5' fusion partner was found. Our findings contribute significantly to characterize the heterogeneous group of ETS gene fusions and indicate that all genes described as 5' fusion partners with one ETS gene can most likely be rearranged with any of the other ETS genes involved in prostate carcinogenesis.