Novel Fusion Transcripts Associate with Progressive Prostate Cancer
2014; Elsevier BV; Volume: 184; Issue: 10 Linguagem: Inglês
10.1016/j.ajpath.2014.06.025
ISSN1525-2191
AutoresYan Yu, Ying Ding, Zhanghui Chen, Silvia Liu, Amantha Michalopoulos, Rui Chen, Zulfiqar Gulzar, Bing Yang, Kathleen Cieply, Alyssa Luvison, Bao‐Guo Ren, James D. Brooks, David F. Jarrard, Joel B. Nelson, George K. Michalopoulos, George C. Tseng, Jianhua Luo,
Tópico(s)Cancer-related gene regulation
ResumoThe mechanisms underlying the potential for aggressive behavior of prostate cancer (PCa) remain elusive. In this study, whole genome and/or transcriptome sequencing was performed on 19 specimens of PCa, matched adjacent benign prostate tissues, matched blood specimens, and organ donor prostates. A set of novel fusion transcripts was discovered in PCa. Eight of these fusion transcripts were validated through multiple approaches. The occurrence of these fusion transcripts was then analyzed in 289 prostate samples from three institutes, with clinical follow-up ranging from 1 to 15 years. The analyses indicated that most patients [69 (91%) of 76] positive for any of these fusion transcripts (TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, KDM4-AC011523.2, MAN2A1-FER, and CCNH-C5orf30) experienced PCa recurrence, metastases, and/or PCa-specific death after radical prostatectomy. These outcomes occurred in only 37% (58/157) of patients without carrying those fusion transcripts. Three fusion transcripts occurred exclusively in PCa samples from patients who experienced recurrence or PCa–related death. The formation of these fusion transcripts may be the result of genome recombination. A combination of these fusion transcripts in PCa with Gleason's grading or with nomogram significantly improves the prediction rate of PCa recurrence. Our analyses suggest that formation of these fusion transcripts may underlie the aggressive behavior of PCa. The mechanisms underlying the potential for aggressive behavior of prostate cancer (PCa) remain elusive. In this study, whole genome and/or transcriptome sequencing was performed on 19 specimens of PCa, matched adjacent benign prostate tissues, matched blood specimens, and organ donor prostates. A set of novel fusion transcripts was discovered in PCa. Eight of these fusion transcripts were validated through multiple approaches. The occurrence of these fusion transcripts was then analyzed in 289 prostate samples from three institutes, with clinical follow-up ranging from 1 to 15 years. The analyses indicated that most patients [69 (91%) of 76] positive for any of these fusion transcripts (TRMT11-GRIK2, SLC45A2-AMACR, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM135-CCDC67, KDM4-AC011523.2, MAN2A1-FER, and CCNH-C5orf30) experienced PCa recurrence, metastases, and/or PCa-specific death after radical prostatectomy. These outcomes occurred in only 37% (58/157) of patients without carrying those fusion transcripts. Three fusion transcripts occurred exclusively in PCa samples from patients who experienced recurrence or PCa–related death. The formation of these fusion transcripts may be the result of genome recombination. A combination of these fusion transcripts in PCa with Gleason's grading or with nomogram significantly improves the prediction rate of PCa recurrence. Our analyses suggest that formation of these fusion transcripts may underlie the aggressive behavior of PCa. CME Accreditation Statement: This activity ("ASIP 2014 AJP CME Program in Pathogenesis") has been planned and implemented in accordance with the Essential Areas and policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint sponsorship of the American Society for Clinical Pathology (ASCP) and the American Society for Investigative Pathology (ASIP). ASCP is accredited by the ACCME to provide continuing medical education for physicians.The ASCP designates this journal-based CME activity ("ASIP 2014 AJP CME Program in Pathogenesis") for a maximum of 48 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.CME Disclosures: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose. CME Accreditation Statement: This activity ("ASIP 2014 AJP CME Program in Pathogenesis") has been planned and implemented in accordance with the Essential Areas and policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint sponsorship of the American Society for Clinical Pathology (ASCP) and the American Society for Investigative Pathology (ASIP). ASCP is accredited by the ACCME to provide continuing medical education for physicians. The ASCP designates this journal-based CME activity ("ASIP 2014 AJP CME Program in Pathogenesis") for a maximum of 48 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity. CME Disclosures: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose. Despite a high incidence,1Jemal A. Bray F. Center M.M. Ferlay J. Ward E. Forman D. Global cancer statistics.CA Cancer J Clin. 2011; 61: 69-90Crossref PubMed Scopus (30939) Google Scholar, 2Siegel R. Naishadham D. Jemal A. Cancer statistics, 2012.CA Cancer J Clin. 2012; 62: 10-29Crossref PubMed Scopus (10558) Google Scholar only a fraction of men diagnosed with prostate cancer (PCa) develop metastases and even fewer die from the disease. Most prostate cancers remain asymptomatic and clinically indolent. The precise mechanisms for the development of progressive, clinically relevant PCa remain elusive. Furthermore, the inability to predict potential aggressiveness of PCa has resulted in significant overtreatment of the disease. The dichotomous nature of PCa—a subset of life-threatening malignancies in the larger background of histological alterations lacking the clinical features implicit with that label—is a fundamental challenge in disease management. To identify genome markers for PCa, tumor (T), adjacent normal prostate tissue (AT), and peripheral blood (B) samples were obtained from five prostate cancer patients who experienced recurrence with fast increase of prostate-specific antigen doubling time (PSADT; 1333-fold (average, 400 million reads per sample) coverage per gene. Total RNA from four age-matched, entirely histologically benign prostate tissues, harvested from organ donors, was similarly sequenced as a tissue control. The sequencing data were aligned to human reference genome HG19.3Li H. Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform.Bioinformatics. 2009; 25: 1754-1760Crossref PubMed Scopus (29919) Google Scholar Fusion transcripts were then identified, filtered, and validated. It was our hypothesis that the presence of these fusion transcripts in the primary tumor would be associated with disease recurrence, development of metastatic disease, or prostate cancer–specific death. Therefore, the fusion transcripts were analyzed on 90 PCa samples from men with known clinical outcomes and 10 benign prostates harvested at organ donation. A prediction model for PCa recurrence and short postoperative PSADT was built. This model was then applied to 89 additional PCa samples from the University of Pittsburgh Medical Center (UPMC; Pittsburgh, PA), 30 samples from Stanford University Medical Center (Stanford, CA), and 36 samples from the University of Wisconsin Madison Medical Center (Madison, WI), with follow-up ranging from 1 to 15 years. A total of 127 of these samples are from patients who experienced PCa recurrence after radical prostatectomy, and 106 are from patients with no evidence of recurrence for at least 5 years after the surgery. The remaining 46 samples are from patients who had 30× for all 14 samples. Picard tool (http://picard.sourceforge.net, last accessed October 11, 2013) was applied to remove duplicate reads after the alignment. RNA-seq reads (from five Ts, four matched ATs, and four organ donor prostate samples) were at an average of 1333× coverage. A maximum of two mismatches per read was allowed. To identify fusion transcript events, we applied the Fusioncatcher version 0.97 algorithm7Edgren H. Murumagi A. Kangaspeska S. Nicorici D. Hongisto V. Kleivi K. Rye I.H. Nyberg S. Wolf M. Borresen-Dale A.L. Kallioniemi O. Identification of fusion genes in breast cancer by paired-end RNA-sequencing.Genome Biol. 2011; 12: R6Crossref PubMed Scopus (245) Google Scholar to the RNA-seq samples. Embedded in Fusioncatcher, BOWTIE and BLAT were used to align sequences to the reference genome. The preliminary list of candidate fusion transcripts is filtered in Fusioncatcher on the basis of the existing biological knowledge of the literature, including the following: i) if the genes are known to be the other's paralog in Ensembl, ii) if one of the fusion transcripts is the partner's pseudogene, iii) if one of the fusion transcripts is micro/transfer/small-nuclear RNA, iv) if the fusion transcript is known to be a false-positive event (eg, Conjoin gene database8Prakash T. Sharma V.K. Adati N. Ozawa R. Kumar N. Nishida Y. Fujikake T. Takeda T. Taylor T.D. Expression of conjoined genes: another mechanism for gene regulation in eukaryotes.PLoS One. 2010; 5: e13284Crossref PubMed Scopus (81) Google Scholar), v) if it has been found in healthy samples (Illumina Body Map 2.0; http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-513, last accessed September 22, 2013), and vi) if the head and tail genes are overlapping with each other on the same strand. Fusion genes were visualized with CIRCOS software version 0.66 (BC Cancer Research Centre, Vancouver, British Columbia, Canada) (Supplemental Figure S1).9Zeng W, Fu C-W, Arisona SM, Qu H: Visualizing interchange patterns in massive movement data. Computer Graphics Forum, Proceedings of EuroVis 2013, 32:3, part 3, 271–280Google Scholar Eight fusion genes from five tumor samples validated by RT-PCR, Sanger sequencing, and fluorescence in situ hybridization (FISH) analyses were used as features to predict nonrecurrence versus recurrence and the nature of the recurrence (PSADT, <4 versus ≥15 months or nonrecurrent). We applied linear discriminant analysis (LDA) to construct the prediction model. In light of relatively rare occurrence of the fusion transcripts (4.4% to 9.0%) in our 90-sample Pittsburgh training cohort, we also applied a simple prediction rule on the basis of the presence in any subset of the eight fusion genes (ie, a patient is predicted as recurrence if any fusion transcript in a designated subset exists). Leave-one-out cross validation was first applied in the 90-sample Pittsburgh training cohort to construct the model and estimate the accuracy. The model with the highest Youden index (sensitivity + specificity − 1)10Youden W.J. Index for rating diagnostic tests.Cancer. 1950; 3: 32-35Crossref PubMed Scopus (7961) Google Scholar is selected from the training cohort, and is then evaluated in an 89-sample Pittsburgh test cohort, a 21-sample Stanford test cohort, and a 30-sample Wisconsin test cohort. To compare the statistical significance of the area under the curve (AUC) difference between two models, a bootstrap test is used to generate P values.11Robin X. Turck N. Hainard A. Tiberti N. Lisacek F. Sanchez J.C. Müller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves.BMC Bioinformatics. 2011; 12: 77Crossref PubMed Scopus (7096) Google Scholar To compare the accuracy of two models, a test for equal proportions using prop.test in R (http://www.r-project) was applied. To demonstrate the potential translational predictive value of these fusion transcripts, information on nomogram-estimated, 5-year, prostate-specific antigen (PSA)–free survival probability and Gleason scores of the patients was incorporated into our prediction models. The following models were generated: i) eight fusion transcripts alone, ii) Gleason scores alone, iii) nomogram values alone, iv) Gleason scores plus eight fusion transcripts, and v) nomogram values plus eight fusion transcripts. Complete information on prediction accuracy, sensitivity, specificity, and Youden index for these eight models is available in Supplemental Tables S2–S13. Double-stranded cDNA was synthesized as described previously.12Luo J.H. Yu Y.P. Cieply K. Lin F. Deflavia P. Dhir R. Finkelstein S. Michalopoulos G. Becich M. Gene expression analysis of prostate cancers.Mol Carcinog. 2002; 33: 25-35Crossref PubMed Scopus (210) Google Scholar, 13Yu Y.P. Landsittel D. Jing L. Nelson J. Ren B. Liu L. McDonald C. Thomas R. Dhir R. Finkelstein S. Michalopoulos G. Becich M. Luo J.H. Gene expression alterations in prostate cancer predicting tumor aggression and preceding development of malignancy.J Clin Oncol. 2004; 22: 2790-2799Crossref PubMed Scopus (599) Google Scholar PCR assays were performed with the primers indicated in Table 1 using the following conditions: 94°C for 5 minutes, followed by 30 cycles of 94°C for 30 seconds, 61°C for 1 minute, and 72°C for 2 minutes. The procedures of probe preparation (Supplemental Table S5) and FISH were described previously.14Ren B. Yu G. Tseng G.C. Cieply K. Gavel T. Nelson J. Michalopoulos G. Yu Y.P. Luo J.H. MCM7 amplification and overexpression are associated with prostate cancer progression.Oncogene. 2006; 25: 1090-1098Crossref PubMed Scopus (153) Google Scholar, 15Yu Y.P. Yu G. Tseng G. Cieply K. Nelson J. Defrances M. Zarnegar R. Michalopoulos G. Luo J.H. Glutathione peroxidase 3, deleted or methylated in prostate cancer, suppresses prostate cancer growth and metastasis.Cancer Res. 2007; 67: 8043-8050Crossref PubMed Scopus (186) Google ScholarTable 1Primer Sequences for RT-PCRGene(s)ForwardReverseTMEM135-CCDC675′-TTGGCATGATAGACCAGTCCC-3′5′-CAGCACCAAGGGAATGTGTAG-3′Mtor-TP53BP15′-TTGGCATGATAGACCAGTCCC-3′5′-CAGCACCAAGGGAATGTGTAG-3′TRMT11-GRIK25′-GCGCTGTCGTGTACCCTTAAC-3′5′-GGTAAGGGTAGTATTGGGTAGC-3′CCNH-C5orf305′-CCAGGGCTGGAATTACTATGG-3′5′-AAGCACCAGTCTGCACAATCC-3′SLC45A2-AMACR5′-TTGATGTCTGCTCCCATCAGG-3′5′-TGATATCGTGGCCAGCTAACC-3′KDM4B- AC011523.25′-AACACGCCCTACCTGTACTTC-3′5′-CTGAGCAAAGACAGCAACACC-3′MAN2A1-FER5′-TGGAAGTTCAAGTCAGCGCAG-3′5′-GCTGTCTTTGTGTGCAAACTCC-3′LRRC59-FLJ600175′-GTGACTGCTTGGATGAGAAGC-3′5′-CCAGCATGCAGCTTTTCTGAG-3′TMPRSS2-ERG5′-AGTAGGCGCGAGCTAAGCAGG-3′5′-GGGACAGTCTGAATCATGTCC-3′ACTB (β-Actin)5′-TCAAGATCATTGCTCCTCCTGAGC-3′5′-TGCTGTCACCTTCACCGTTCCAGT-3′ Open table in a new tab To identify fusion transcripts, analysis of RNA sequencing was performed on five PCa samples. A total of 76 RNA fusion events were identified using the Fusioncatcher7Edgren H. Murumagi A. Kangaspeska S. Nicorici D. Hongisto V. Kleivi K. Rye I.H. Nyberg S. Wolf M. Borresen-Dale A.L. Kallioniemi O. Identification of fusion genes in breast cancer by paired-end RNA-sequencing.Genome Biol. 2011; 12: R6Crossref PubMed Scopus (245) Google Scholar program. Thirteen of these fusion events were confirmed by genome sequencing. To control for tissue-based normal fusion transcript events, fusion transcripts present in any of the four age-matched organ donor prostate tissues were eliminated. Furthermore, fusion transcripts with <20 kb between each element and read in the cis-direction were also eliminated. As a result of this filtering, 28 of 76 fusion transcript events were identified as PCa specific (Supplemental Table S6 and Supplemental Figure S1). Among these fusion events, TMPRSS2-ERG, the most common PCa fusion transcript,16Tomlins S.A. Rhodes D.R. Perner S. Dhanasekaran S.M. Mehra R. Sun X.W. Varambally S. Cao X. Tchinda J. Kuefer R. Lee C. Montie J.E. Shah R.B. Pienta K.J. Rubin M.A. Chinnaiyan A.M. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer.Science. 2005; 310: 644-648Crossref PubMed Scopus (3208) Google Scholar, 17Berger M.F. Lawrence M.S. Demichelis F. Drier Y. Cibulskis K. Sivachenko A.Y. et al.The genomic complexity of primary human prostate cancer.Nature. 2011; 470: 214-220Crossref PubMed Scopus (998) Google Scholar, 18Baca S.C. Prandi D. Lawrence M.S. Mosquera J.M. Romanel A. Drier Y. et al.Punctuated evolution of prostate cancer genomes.Cell. 2013; 153: 666-677Abstract Full Text Full Text PDF PubMed Scopus (943) Google Scholar was found in two PCa samples. Most of the fusion events identified were novel. No fusion transcripts were identified in any of the AT samples, suggesting the somatic nature of these fusion transcripts. To validate these fusion transcripts, RT-PCR was performed using primers specific for fusion transcript regions encompassing the fusion breakpoints, and the PCR products were sequenced. Eight of these fusion transcript events were validated through sequencing (Figure 1). Five of the eight fusion events resulted in truncation of a head gene and frameshift in translation of a tail gene. One of the fusion transcripts produced a truncated cyclin H and an independent open reading frame of a novel protein whose function is not known. Two fusion events, however, are predicted to produce chimeras that possibly retain at least partial function of both genes. For example, a fusion transcript between the N-terminus 703 amino acids of α-mannosidase 2A (MAN2A1) and the C-terminus 250 amino acids of FER, a feline tyrosine kinase, retains the glycoside hydrolase domain of MAN2A1 but replaces the mannosidase domain with the tyrosine kinase domain from FER. Another fusion transcript couples 5 of 10 transmembrane domains of the membrane transporter protein SLC45A2 with the methyl-acyl CoA transferase domain from AMACR. Interestingly, both MAN2A1-FER and SLC45A2-AMACR fusions are in the trans-direction, eliminating the possibility of a fusion event from simple chromosome deletion or collapse of an extremely large RNA transcript. The most frequent fusion events observed in PCa were TRMT11-GRIK2 [22 (7.9%) of 279] and SLC45A2-AMACR [20 (7.2%) of 279] (Supplemental Figures S2-S4). TRMT11-GRIK2 fusion represents a giant truncation of TRMT11, a tRNA methyltransferase, and elimination of GRIK2, a glutamate receptor but reported to possess tumor-suppressor activity.19Sinclair P.B. Sorour A. Martineau M. Harrison C.J. Mitchell W.A. O'Neill E. Foroni L. A fluorescence in situ hybridization map of 6q deletions in acute lymphocytic leukemia: identification and analysis of a candidate tumor suppressor gene.Cancer Res. 2004; 64: 4089-4098Crossref PubMed Scopus (50) Google Scholar Indeed, when GRIK2 expression was examined in 14 TRMT11-GRIK2–positive PCa samples, it was undetectable, whereas it was detected in organ donor prostate samples (Supplemental Figure S5). Only 4 of 14 samples with TRMT11-GRIK2 expressed full-length TRMT11 transcripts. Thus, the fusion event of TRMT11-GRIK2 likely produces a loss of function. To investigate the mechanism of these fusion events, FISH was performed on PCa tissues where the fusion transcripts were present. By using the probes surrounding the MAN2A1 breakpoint, a physical separation of signals between 5′ and 3′ MAN2A1 in cancer cells containing the fusion was observed, whereas the wild-type alleles in normal prostate epithelial cells showed overlapping fluorescent signals (Figure 2). Similar break-apart hybridization occurred in SLC45A2-AMACR–positive PCa samples (Figure 2B). These findings indicate that MAN2A1-FER and SLC45A2-AMACR fusions are the result of chromosomal recombination events and validate the fusion transcripts found by RNA-seq. Interestingly, in PCa cells containing break-apart signals of MAN2A1, only 31% of the cells retained the 3′ end signal, suggesting that the recombination event results in truncation of the C-terminus of MAN2A1 in most PCa cells. A similar collateral loss of the N-terminus of AMACR was found in PCa cells expressing the SLC45A2-AMACR fusion transcript (29% retaining the N-terminus signal of AMACR). Other FISH analyses confirmed that genome translocations occur in cancer cells expressing TRMT11-GRIK2, MTOR-TP53BP1, LRRC59-FLJ60017, TMEM137-CCDC67, CCNH-C5orf30, and KDM4B-AC011523.2 fusion transcripts (Figure 2, C–G). These fusion transcripts are either separated widely on a single chromosome (TRMT11-GRIK2, TMEM135-CCDC67, CCNH-C5orf30, and KDM4B- AC011523.2) or located on separate chromosomes (MTOR-TP53BP1 and LRRC59-FLJ60017). The overlapping signals of hybridizations in PCa cells offered additional validation of these fusion events. Finally, genomic breakpoints were identified in three fusion pairs through Sanger sequencing of the cancer genomic DNA (CCNH-C5orf30, TMEM135-CCDC67, and LRRC59-FLJ60017) (Supplemental Figure S6). To investigate the clinical and biological significance of the fusion transcripts, their presence was assessed in PCa specimens obtained from 213 men and in histologically confirmed benign prostate tissues obtained from 10 organ donors free of urological disease (aged 20 to 70 years). For 179 of the 223 PCa samples, clinical outcome data after radical prostatectomy were available, and 81 had no detectable PSA recurrence after a minimum of 5 years of follow-up, whereas 98 developed biochemical recurrence (defined as a measurable PSA ≥0.2 ng/mL). In the patients without recurrence, only 7.4% (6/81) primary prostate cancers expressed one of the fusion transcripts. In contrast, 52% (51/98) primary prostate cancers expressed at least one fusion in patients who developed biochemical recurrence (Figure 3 and Supplemental Figure S2A). No fusion transcripts were detected in benign prostate tissues obtained from healthy organ donors (Supplemental Figure S2B). Three fusion events were observed exclusively in recurrent PCa after radical prostatectomy (TRMT11-GRIK2, MTOR-TP53BP1, and LRRC59-FLJ60017) (Figure 3, A and B). Fisher's exact test showed a significant difference in recurrent status between patients with at least one of the eight fusion transcripts and those without this transcript (P = 6.8 × 10−16). In the combined University of Pittsburgh Medical Center (UPMC), Stanford, and Wisconsin data sets, 91% (69/76) of patients positive for one of the fusion transcripts experienced prostate cancer recurrence in 5 years after prostate resection. On the basis of the hypothesis that the presence of at least one of the eight fusion transcripts would indicate a recurrence for a prostate cancer patient, a PCa prediction model was built and tested, using 90 randomly selected PCa samples from UPMC (training set). This training cohort yielded an accuracy of PCa recurrence prediction of 71%, with 89% specificity and 58% sensitivity (P < 0.005) (Supplemental Figure S7A and Supplemental Table S7). When this model was applied to a separate cohort of 89 samples (test set), the model correctly predicted recurrence in 70% of patients. To further validate this model, we tested its performance in a 30-patient (21 with qualified clinical follow-up) cohort from Stanford University Medical Center and a 36-patient (30 with qualified clinical follow-up) cohort from University of Wisconsin Madison Medical Center (Figure 3 and Supplemental Figures S4 and S5). Once again, the model correctly predicted recurrence, with 76.2% accuracy, 89% specificity, and 67% sensitivity on the PCa cohort from Stanford, and 80% accuracy, 100% specificity, and 63% sensitivity on the Wisconsin cohort (Supplemental Table S8). In itself, recurrence does not signal an aggressive prostate cancer, because many patients with PSA recurrence do not develop metastases or die from their disease. A PSADT 15 months.20Freedland S.J. Humphreys E.B. Mangold L.A. Eisenberger M. Dorey F.J. Walsh P.C. Partin A.W. Death in patients with recurrent prostate cancer after radical prostatectomy: prostate-specific antigen doubling time subgroups and their associated contributions to all-cause mortality.J Clin Oncol. 2007; 25: 1765-1771Crossref PubMed Scopus (159) Google Scholar, 21Antonarakis E.S. Zahurak M.L. Lin J. Keizman D. Carducci M.A. Eisenberger M.A. Changes in PSA kinetics predict metastasis-free survival in men with PSA-recurrent prostate cancer treated with nonhormonal agents: combined analysis of 4 phase II trials.Cancer. 2012; 118: 1533-1542Crossref PubMed Scopus (43) Google Scholar The presence of one or more fusion transcripts in the PCa tissue showed a strong association with PSADT <4 months (P = 6 × 10−9). To examine whether these fusion transcripts have prognostic value for PCa clinical outcome, a prediction model was built using the optimized weight of each fusion transcript calculated by LDA classifier on the basis of the P value of each fusion transcript with short PSADT. The panel of eight fusion transcripts correctly predicted 74.4% for PSA doubling time in the 90-sample training cohort (Supplemental Figure S6). When the same algorithm was applied to a separate 89-sample test set from UPMC and a 21-sample cohort from Stanford University Medical Center, the prediction rate for PSADT ≤4 months was found to be 78% and 71%, respectively (Figure 4B). To examine the impact of fusion transcripts on patients' PSA-free survival, a Kaplan-Meier analysis was performed on the PCa cohort from University of Pittsburgh. Patients (84.2%) had an observed disease recurrence within 5 years of radical prostatectomy if they carried any of the eight fusion transcripts (Figure 4C). No patient survived 5 years without recurrence if his or her primary PCa contained a TRMT11-GRIK2 or MTOR-TP53BP1 transcript fusion. In contrast, 68% of the patients were free of disease recurrence if none of the fusion transcripts was detected in their primary PCa. Similar findings were also identified in the Stanford cohort: 88.9% of the patients experienced recurrence of PCa if they carried any fusion transcript, whereas 66.7% were free of the disease recurrence if they were negative for the transcript. Prostate cancer samples with at least one fusion transcript correlate with more advanced stage of prostate cancer (P = 0.004), lymph node involvement status (P
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