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  • American Association for Cancer Research (AACR)  (8)
  • 1
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 25, No. 22_Supplement ( 2019-11-15), p. AP09-AP09
    Abstract: BACKGROUND: The genomic complexity of profound copy-number aberration has prevented effective molecular stratification of high grade serous ovarian carcinoma (HGSOC). Recent algorithmic advances have enabled interpretation of complex genomic changes by identifying mutational signatures—genomic patterns that are the imprint of mutagenic processes accumulated over the lifetime of a cancer cell. We hypothesized that specific features of copy-number (CN) abnormalities could represent the imprints of distinct mutational processes, and developed methods to identify signatures from copy-number features in HGSOC. METHODS: We derived copy-number signatures from absolute copy number profiles from 253 primary and relapsed HGSOC samples from 132 patients in the BriTROC-1 cohort using low-cost shallow whole-genome sequencing (sWGS; 0.1×). A subset of 56 of these cases had deep whole-genome sequencing (dWGS) performed for mutation analysis and comparison with sWGS data. Independent validation was performed using 112 dWGS HGSOC cases from PCAWG and 415 HGSOC cases with SNP array and whole exome sequence from TCGA. CN signature exposures were correlated with mutation data, SNV signatures, and other measures derived from deep WGS and exome sequencing to identify statistically significant genomic associations using a false discovery rate & lt;0.05. RESULTS: We identified 7 CN signatures that provided a molecular framework to rederive the major defining elements of HGSOC genomes, including defective homologous recombination (HRD), tandem duplication, amplification of CCNE1 and amplification-associated fold-back inversions. Almost all patients with HGSOC demonstrated a mixture of signatures indicative of combinations of mutational processes, including those with early driver events such as BRCA2 mutation (in addition to HRD signatures). High exposure to CN signature 3, characterised by BRCA1/2-related HRD, was associated with improved overall survival. Conversely, high exposure to signature 1, which was characterised by oncogenic RAS signaling (including NF1, KRAS and NRAS mutation), predicted platinum-resistant relapse and poor survival. CONCLUSIONS: HGSOC lacks clinically-relevant patient stratification, which is reflected in poor survival and is a significant barrier to precision medicine. Copy-number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Our results suggest that early TP53 mutation, the ubiquitous initiating event in HGSOC, may permit multiple mutational processes to co-evolve, potentially simultaneously and that additional signature exposures may alter the risk of developing therapeutic resistance. Thus, our results suggest that HGSOC is a continuum of genomes. We derived signatures using inexpensive sWGS of DNA from core biopsies. These approaches are rapid and cost effective, thus providing a clear path to clinical implementation. By dissecting the mutational forces shaping HGSOC genomes, our study paves the way to understanding extreme genomic complexity, as well as revealing the evolution of tumors as they relapse and acquire resistance to therapy. Citation Format: Geoff Macintyre, Teodora E. Goranova, Dilrini De Silva, Darren Ennis, Anna M. Piskorz, Matthew Eldridge, Daoud Sie, Liz-Anne Lewsley, Aishah Hanif, Cheryl Wilson, Suzanne Dowson, Rosalind M. Glasspool, Michelle Lockley, Elly Brockbank, Ana Montes, Axel Walther, Sudha Sundar, Richard Edmondson, Geoff D. Hall, Andrew Clamp, Charlie Gourley, Marcia Hall, Christina Fotopoulou, Hani Gabra, James Paul, Anna Supernat, David Millan, Aoisha Hoyle, Gareth Bryson, Craig Nourse, Laura Mincarelli, Luis Navarro Sanchez, Bauke Ylstra, Mercedes Jimenez-Linan, Luiza Moore, Oliver Hofmann, Florian Markowetz, Iain A. McNeish, James D. Brenton. COPY-NUMBER SIGNATURES AND MUTATIONAL PROCESSES IN HIGH GRADE SEROUS OVARIAN CARCINOMA [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Resear ch Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr AP09.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 2
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    American Association for Cancer Research (AACR) ; 2015
    In:  Cancer Research Vol. 75, No. 22_Supplement_2 ( 2015-11-15), p. B1-40-B1-40
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 22_Supplement_2 ( 2015-11-15), p. B1-40-B1-40
    Abstract: The development of androgen resistance is a major limitation to androgen deprivation treatment in prostate cancer (PCa). We have developed an in vitro model of androgen-resistance using the androgen sensitive cell line LNCaP to characterize the phenotypic and transcriptomic changes occurring as androgen resistance develops. Our aim is to understand biological network profiles of transcriptomic changes during the transition to androgen-resistance and to validate these changes between our in vitro model and previously published clinical datasets (paired samples before and after androgen-deprivation therapy of patients with advanced PCa) (1). Methods: PCa cells, LNCaP, expressing mutated AR which are androgen-dependent (2,3), are used in the development of an androgen-resistant subline. Subline cells were established by prolonged cultures in media + 10% CS-FBS to mimic the clinical course of PCa. Cell proliferation, cell motility and invasion, morphology, AR expression were examined. RNA-sequencing was performed using the parental LNCaP cells and an androgen-resistant subline (LNCaP-AI) established by chronic exposure to the androgen-deprivation. Reads from cells and clinical samples (1), pre- vs. post-treatment, were processed through the same standard pipeline and quality control. Data outputs were analysed as differential expression [DEG] (EdgeR) (4) and top scoring protein-protein interaction (PPI) networks [PINA2 (5) and BioNet (6)]. Data outputs from the cell line model and clinical samples were compared. Results: LNCaP cells initially showed poor growth after prolonged exposure to androgen-deprived conditions but later adapted and started to grow well. After 24 weeks of androgen-deprivation, LNCaP-AI's growth was no longer responsive to addition of androgen [0.1 - 10 nM] . AR expression was not different in LNCaP and LNCaP-AI (P & gt;0.05). LNCaP-AI cells had increased proliferation and cell invasion compared to LNCaP. We identified key genes that overlap between our cell line and clinical RNAseq (1) datasets and analyzed the overlapping PPI network that showed the same pattern of behavior in both datasets. The network revealed several potential mechanisms and gene interactions that warrant further investigation, including cooperative behaviors of other nuclear receptors, TP63 mediated signalling pathway and Aryl hydrocarbon receptor transcriptional pathway. Conclusion: Cell line model of androgen-resistance will be used for further longitudinal study of the mechanism of castrate resistant prostate cancer (CRPC). Our approach allows for better characterization of biological processes of CRPC. Knowledge of the genetic profiles during transition to androgen resistance will improve our understanding of this common clinical scenario and may lead to biomarker discovery. References: 1. Rajan P, Sudbery IM, Villasevil ME, Mui E, Fleming J, Davis M, et al. Next-generation sequencing of advanced prostate cancer treated with androgen-deprivation therapy. Eur Urol 2013;66(1):32-9. 2. Marques RB, van Weerden WM, Erkens-Schulze S, de Ridder CM, Bangma CH, Trapman J, et al. The human PC346 xenograft and cell line panel: A model system for prostate cancer progression. Eur Urol 2006;49(2):245-57. 3. Pienta KJ, Bradley D. Mechanisms underlying the development of androgen-independent prostate cancer. Clin Cancer Res 2006;12(6):1665-71. 4. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010;26(1):139-40. 5. Cowley MJ, Pinese M, Kassahn KS, Waddell N, Pearson JV, Grimmond SM, et al. PINA v2.0: mining interactome modules. Nucleic Acids Res 2012;40(Database issue):D862-5. 6. Beisser D, Klau GW, Dandekar T, Müller T, Dittrich M. BioNet: an R-Package for the functional analysis of biological networks. Bioinformatics 2010;26(8):1129-30. Citation Format: Sujitra Detchokul, Aparna Elangovan, Melissa J. Davis, Geoff Macintyre, Edmund J. Crampin, Albert G. Frauman. Biological network analysis using an in vitro model of androgen-resistance in prostate cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-40.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 3000-3000
    Abstract: We have characterised intra-tumour heterogeneity (ITH) across 2,778 whole genome sequences of tumours in the International Cancer Genome Consortium Pan-Cancer Analysis of Whole Genomes project, representing 36 distinct cancer types. We applied 6 copy number (CNA) callers and 11 subclonal reconstruction algorithms and developed approaches to integrate the results in robust, high-confidence CNA calls and subclonal architectures. The analysis reveals widespread ITH. We find at least one subclone in nearly all (96.7%) tumours with sufficient sequencing depth. Analysis using dN/dS ratios yields clear signs of positive selection in clonal and subclonal mutations and we find subclonal driver mutations in known driver genes. However, only 24% of subclones contain a driver mutation in a known driver gene, suggesting that a multitude of undiscovered late drivers exist and that tumours continue to undergo selection after tumourigenesis, at least until diagnosis. Consistent with other studies, we find that in 9% of tumours all clinically actionable mutations are subclonal, while 20% of tumours contain at least one subclonal actionable driver. These findings emphasise the relevance of ITH in treatment decision making. Distinct patterns of ITH emerge; for example, prostate, uterus and esophageal adenocarcinomas show high proportions of both subclonal single nucleotide variants (SNVs) and CNAs. Kidney chromophobe and pancreatic endocrine tumours also contain high proportions of subclonal SNVs, but few subclonal CNAs. On the other hand, hepatocellular carcinomas and head-and-neck and lung SCCs contain low proportions of subclonal SNVs and high proportions of subclonal CNAs. Mutational signature analysis reveals changes in signature activity. Exposures to UV light in melanomas and acid reflux in stomach and oesophageal cancers contribute more clonal mutations. While APOBEC and DNA damage repair response related signatures show increased activity in subclones. These findings highlight distinct evolutionary narratives between and within histologically distinct tumour types. Citation Format: Stefan Dentro, Ignaty Leshchiner, Kerstin Haase, Jeff Wintersinger, Amit Deshwar, Maxime Tarabichi, Yulia Rubanova, Kaixian Yu, Ignacio Vázquez García, Geoff Macintyre, Kortine Kleinheinz, Dimitri Livitz, Salem Malikic, Nilgun Donmez, Subhajit Sengupta, Yuan Ji, Jonas Demeulemeester, Pavana Anur, Clemency Jolly, Marek Cmero, Daniel Rosebrock, Steve Schumacher, Yu Fan, Matthew Fittall, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Hongtu Zhu, David Adams, Gad Getz, Paul Boutros, Marcin Imielinski, Rameen Beroukhim, Cenk Sahinalp, Martin Peifer, Inigo Martincorena, Florian Markowetz, Ville Mustonen, Ke Yuan, Moritz Gerstung, Wenyi Wang, Paul Spellman, Quaid Morris, David Wedge, Peter Van Loo. Pervasive intra-tumour heterogeneity and subclonal selection across cancer types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3000.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 4
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 26, No. 20 ( 2020-10-15), p. 5411-5423
    Abstract: Gene expression–based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. Results: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with & gt;95% accuracy that was maintained in all analytic and biological validations. Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications. See related commentary by McMullen et al., p. 5271
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 5
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 53-53
    Abstract: Background: High grade serous carcinoma (HGSC) is the most common and poorest prognosis subtype of ovarian cancer. The large majority of patients present with advanced (stage IIIC or IV) disease with a median survival of only 3-4 years. By contrast, approximately 10% patients are diagnosed with early stage disease, confined to the ovary/fallopian tube, of whom 90% are cured with surgery and platinum-based chemotherapy. Beyond TP53 mutation, classic activating oncogene mutations are rare in HGSC. Rather, HGSC is marked by extreme copy number (CN) abnormalities, and this complexity has prevented detailed understanding of the mutational processes underpinning outcomes in HGSC. We have used shallow whole genome sequencing (sWGS) to develop novel CN signatures that are able to deconvolute the complexity of HGSC genomes. However, nearly all genomics studies in HGSC have examined advanced stage disease, and little is known about the genomics of early stage HGSC - specifically, it is unclear whether these tumors are identified purely by chance or whether they represent a specific subset that does not metastasize. Hypotheses: We hypothesized that early stage HGSC has a distinct copy number landscape compared to stage IIIC/IV disease. Methods and results: We have identified 43 cases of FIGO stage I-IIA HGSC from the pathology archives of three large London Gynaecological Cancer Centres and 52 late-stage (stage IIIC-IV) cases from BriTROC-1 cohort. Median age at diagnosis was 61.3 years vs 62.3 years respectively. There were no significant differences in mutation rates of TP53 and BRCA1/2, and TP53 mutations were near-universal in both cohorts. We also did not find cohort-specific focal SCNA that could explain biological behavior. However, ploidy was significant higher in late-stage (median 3.0) than early-stage (median 1.9) samples. CN signature exposures were significantly different between early and late stage cohorts. Relative exposure of signature 3 was greater in early-stage and greater signature 4 in late-stage. Unsupervised clustering based on CN signatures identified three clusters that were prognostic. Summary:This project identifed that early stage and late stage HGSC have highly similar patterns of mutation and focal SCNA. However, genome-wide analysis indicates that the abnormalities seen in advanced disease are not present in early stage disease, which may represent a discrete subset with reduced metastatic potential. By identifying and characterizing the copy number signature changes, these data suggest that diagnosis at early-stage might reflect biological differences and not fortuitous chance. These data improve understanding of HGSC biology and may reveal potential new treatment strategies. Citation Format: Zhao Cheng, Hasan B. Mirza, Darren P. Ennis, Philip Smith, Lena Morrill Gavarró, Chishimba Sokota, Gaia Giannone, Teodora Goranova, Thomas Bradley, Anna Piskorz, Michelle Lockley, Baljeet Kaur, Naveena Singh, Laura A. Tookman, Jonathan Krell, Jackie McDermott, Geoff Macintyre, Florian Markowetz, James D. Brenton, Iain A. McNeish. The copy number landscape of early stage ovarian high grade serous carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 53.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 6
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    American Association for Cancer Research (AACR) ; 2017
    In:  Clinical Cancer Research Vol. 23, No. 3 ( 2017-02-01), p. 630-635
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 23, No. 3 ( 2017-02-01), p. 630-635
    Abstract: A concerted effort to sequence matched primary and metastatic tumors is vastly improving our ability to understand metastasis in humans. Compelling evidence has emerged that supports the existence of diverse and surprising metastatic patterns. Enhancing these efforts is a new class of algorithms that facilitate high-resolution subclonal modeling of metastatic spread. Here we summarize how subclonal models of metastasis are influencing the metastatic paradigm. Clin Cancer Res; 23(3); 630–5. ©2016 AACR.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
    detail.hit.zdb_id: 1225457-5
    detail.hit.zdb_id: 2036787-9
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 218-218
    Abstract: Cancer develops through a continuous process of somatic evolution. Whole genome sequencing provides a snapshot of the tumor genome at the point of sampling, however, the data can contain information that permits the reconstruction of a tumor's evolutionary past. Here, we apply such life history analyses on an unprecedented scale, to a set of 2,658 tumors spanning 39 cancer types. We estimated the timing of large chromosomal gains during tumor evolution, by comparing the rates of doubled to non-doubled point mutations within gained regions. Although we find that such events typically occur in the second half of clonal evolution, we also observe distinctive and early chromosomal gains in some cancer types, such as gains of chromosomes 7, 19 and 20 in glioblastoma, and isochromosome 17q in medulloblastoma. By integrating these results with the qualitative timing of individual driver mutations, we obtained an overall ranking, from early to late, of frequent somatic events per cancer type, which both identified novel patterns of tumor evolution, and incorporated additional detail into known models, such as the progression of APC-KRAS-TP53 in colorectal cancer proposed by Vogelstein and Fearon. To estimate how mutational processes acting on the tumor genome change over time, we classified mutations in each sample according to three broad time periods (early clonal, late clonal, and subclonal), and quantified the activity of mutational signatures in each period. Most mutational processes appear to remain remarkably constant, however, certain signatures show clear and consistent changes during clonal evolution. Particularly, mutational signatures associated with exposure to carcinogens, such as smoking and UV light, tend to decrease over time. In contrast, signatures associated with defective endogenous processes, such as APOBEC mutagenesis and defective double strand break repair, show an increase between early and late phases of tumor evolution. Making use of clock-like mutational signatures, we converted mutational time estimates for large events, such as whole genome duplication (WGD), and the emergence of the most recent common ancestor (MRCA), into real time estimates, which allowed us to combine our analyses into overall timelines of cancer evolution, per tumor type. For example, the typical timeline of ovarian adenocarcinoma development shows that early tumor evolution is characterized by mutations in TP53, and widespread genome instability, with WGD events taking place on average 8 years prior to diagnosis. In later stages of evolution, signatures of defective repair processes increase, and the MRCA emerges on average 1 year before diagnosis. Taken together, these data reveal the common and divergent evolutionary trajectories available to a cancer, which might be crucial in understanding specific tumor biology, and in providing new opportunities for early detection and cancer prevention. Citation Format: Clemency Jolly, Moritz Gerstung, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Daniel Rosebrock, Kaixian Yu, Maxime Tarabichi, Amit Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vásquez-García, Kerstin Haase, Subhajit Sengupta, Geoff Macintyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Mark Cmero, Jonas Demeulemeester, Steve Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, S Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Juan, Wenyi Wang, Quaid D. Morris, Paul T. Spellman, David C. Wedge, Peter Van Loo, PCAWG Evolution and Heterogeneity Working Group. The evolutionary history of 2,658 cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 218.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 8
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 20, No. 21 ( 2014-11-01), p. 5547-5557
    Abstract: Purpose: It has been recognized for almost a decade that concentrations of signaling androgens sufficient to activate the androgen receptor are present in castration-resistant prostate cancer tissue. The source of these androgens is highly controversial, with three competing models proposed. We, therefore, wished to determine the androgenic potential of human benign and malignant (hormone-naïve and treated) prostate tissue when incubated with various precursors and examine concomitant changes in enzyme expression. Experimental Design: Freshly harvested prostate tissue [benign, hormone-naïve, and hormone-refractory prostate cancer (HRPC)] was incubated in excess concentrations of cholesterol, progesterone, DHEA, androstenedione, or testosterone for 96 hours, and steroid concentrations in the conditioned media measured by gas chromatography–mass spectroscopy. Changes in the expression of androgen synthetic and/or degradative enzymes were determined by expression microarray and qPCR. Significant changes were confirmed in an independent dataset. Results: Of the precursor molecules tested, only incubation with androstenedione gave rise to significant concentrations of signaling androgens. Although this was observed in all tissue types, it occurred to a significantly greater degree in hormone-refractory compared with hormone-naïve cancer. Consistent with this, gene set enrichment analysis of the expression microarray data revealed significant upregulation of 17HSD17B activity, with overexpression of the canonical enzyme AKR1C3 confirmed by qPCR in the same samples and in a publicly available expression dataset. Importantly, we found no evidence to support a significant contribution from either the “backdoor” or “5-α dione” pathway. Conclusions: Reduction of androstenedione to testosterone by the canonical HSD17B AKR1C3 is the predominant source of signaling androgens in HRPC. Clin Cancer Res; 20(21); 5547–57. ©2014 AACR.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2014
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