Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Hsa_circ_0094606 promotes malignant progression of prostate cancer by inducing M2 polarization of macrophages through PRMT1-mediated arginine methylation of ILF3.

Circular RNA (circRNA), a type of noncoding RNAs, has been demonstrated to act vital roles in tumorigenesis and cancer deterioration. Although tumor-associated macrophages are involved in tumor malignancy, the interactions between circRNAs and tumor-associated macrophages in prostate cancer (PCa) remain unclear. In the present study, we found that hsa_circ_0094606 (subsequently named circ_0094606) could promote proliferation, epithelial-mesenchymal transition (EMT) as well as migration of PCa cells through cell viability and migration assays and the determination of EMT markers. Mass spectrometry analysis after RNA pull-down experiment identified that circ_0094606 bound to protein arginine methyltransferase 1 (PRMT1) in PCa cells, and further functional assays revealed that circ_0094606 promoted the malignant progression of PCa by binding to PRMT1. Moreover, co-immunoprecipitation (Co-IP), glutathione-S-transferase (GST) pull-down and immunofluorescence showed that PRMT1 mediated arginine methylation of ILF3 to stabilize the protein. Bioinformatics analysis combined with data from RNA-binding protein immunoprecipitation and RNA pull-down suggested that ILF3 could stabilize IL-8 mRNA, which promoted the M2 polarization in coculture study. Finally, in vivo experiments showed that circ_0094606 subserve PCa growth and promoted the M2 polarization of macrophages through the PRMT1/ILF3/IL-8 regulation pathway, supporting circ_0094606 as a potential novel effective target for PCa treatment.

Protocol for a prospective study evaluating circulating tumour cells status to predict radical prostatectomy treatment failure in localised prostate cancer patients (C-ProMeta-1).

BACKGROUND: Treatment decisions in prostate cancer (PCa) rely on disease stratification between localised and metastatic stages, but current imaging staging technologies are not sensitive to micro-metastatic disease. Circulating tumour cells (CTCs) status is a promising tool in this regard. The Parsortix® CTC isolation system employs an epitope-independent approach based on cell size and deformability to increase the capture rate of CTCs. Here, we present a protocol for prospective evaluation of this method to predict post radical prostatectomy (RP) PCa cancer recurrence. METHODS: We plan to recruit 294 patients diagnosed with unfavourable intermediate, to high and very high-risk localised PCa. Exclusion criteria include synchronous cancer diagnosis or prior PCa treatment, including hormone therapy. RP is performed according to the standard of care. Two blood samples (20 ml) are collected before and again 3-months after RP. The clinical team are blinded to CTC results and the laboratory researchers are blinded to clinical information. Treatment failure is defined as a PSA ≥ 0.2 mg/ml, start of salvage treatment or imaging-proven metastatic lesions. The CTC analysis entails enumeration and RNA analysis of gene expression in captured CTCs. The primary outcome is the accuracy of CTC status to predict post-RP treatment failure at 4.5 years. Observed sensitivity, positive and negative predictive values will be reported. Specificity will be presented over time. DISCUSSION: CTC status may reflect the true potential for PCa metastasis and may predict clinical outcomes better than the current PCa progression risk grading systems. Therefore establishing a robust biomarker for predicting treatment failure in localized high-risk PCa would significantly enhance guidance in treatment decision-making, optimizing cure rates while minimizing unnecessary harm from overtreatment. TRIAL REGISTRATION: ISRCTN17332543.

Facile One-Pot Nanoproteomics for Label-Free Proteome Profiling of 50-1000 Mammalian Cells.

Recent advances in sample preparation enable label-free mass spectrometry (MS)-based proteome profiling of small numbers of mammalian cells. However, specific devices are often required to downscale sample processing volume from the standard 50-200 µL to sub-µL for effective nanoproteomics, which greatly impedes the implementation of current nanoproteomics methods by the proteomics research community. Herein, we report a facile one-pot nanoproteomics method termed SOPs-MS (surfactant-assisted one-pot sample processing at the standard volume coupled with MS) for convenient robust proteome profiling of 50-1000 mammalian cells. Building upon our recent development of SOPs-MS for label-free single-cell proteomics at a low µL volume, we have systematically evaluated its processing volume at 10-200 µL using 100 human cells. The processing volume of 50 µL that is in the range of volume for standard proteomics sample preparation has been selected for easy sample handling with a benchtop micropipette. SOPs-MS allows for reliable label-free quantification of ∼1200-2700 protein groups from 50 to 1000 MCF10A cells. When applied to small subpopulations of mouse colon crypt cells, SOPs-MS has revealed protein signatures between distinct subpopulation cells with identification of ∼1500-2500 protein groups for each subpopulation. SOPs-MS may pave the way for routine deep proteome profiling of small numbers of cells and low-input samples.

Noninvasive Detection of Clinically Significant Prostate Cancer Using Circulating Tumor Cells.

PURPOSE: Prostate specific antigen testing results in unnecessary biopsy and over diagnosis with consequent overtreatment. Tissue biopsy is an invasive procedure associated with significant morbidity. More accurate noninvasive or minimally invasive diagnostic approaches should be developed to avoid unnecessary prostate biopsy and over diagnosis. We investigated the potential of using circulating tumor cell analysis in cancer diagnosis, particularly to predict clinically significant prostate cancer in prebiopsy cases. MATERIALS AND METHODS: We enrolled 155 treatment naïve patients with prostate cancer and 98 before biopsy for circulating tumor cell enumeration. RNA was extracted from circulating tumor cells of 184 patients for gene expression analysis. The Kruskal-Wallis and Spearman rank tests, multivariate logistic regression and the random forest method were applied to assess the association of circulating tumor cells with aggressive prostate cancer. RESULTS: Of patients with localized prostate cancer 54% were scored as having positive circulating tumor cells, which was associated with a higher Gleason score (p=0.0003), risk group (p <0.0001) and clinically significant prostate cancer (p <0.0001). In the prebiopsy group a positive circulating tumor cell score combined with prostate specific antigen predicted clinically significant prostate cancer (AUC 0.869). A 12-gene panel prognostic for clinically significant prostate cancer was also identified. When combining the prostate specific antigen level, the circulating tumor cell score and the 12-gene panel, the AUC of clinically significant prostate cancer prediction was 0.927. Adding those data to cases with available multiparametric magnetic resonance imaging data significantly increased prediction accuracy (AUC 0.936 vs 0.629). CONCLUSIONS: Circulating tumor cell analysis has the potential to significantly improve patient stratification by prostate specific antigen and/or multiparametric magnetic resonance imaging for biopsy and treatment.

Bladder cancer, a unique model to understand cancer immunity and develop immunotherapy approaches.

With the mechanistic understanding of immune checkpoints and success in checkpoint blockade using antibodies for the treatment of certain cancers, immunotherapy has become one of the hottest areas in cancer research, with promise of long-lasting therapeutic effect. Currently, however, only a proportion of cancers have a good response to checkpoint inhibition immunotherapy. Better understanding of the cancer response and resistance mechanisms is essential to fully explore the potential of immunotherapy to cure the majority of cancers. Bladder cancer, one of the most common and aggressive malignant diseases, has been successfully treated both at early and advanced stages by different immunotherapeutic approaches, bacillus Calmette-Guérin (BCG) intravesical instillation and anti-PD-1/PD-L1 immune checkpoint blockade, respectively. Therefore, it provides a good model to investigate cancer immune response mechanisms and to improve the efficiency of immunotherapy. Here, we review bladder cancer immunotherapy with equal weight on BCG and anti-PD-1/PD-L1 therapies and demonstrate why and how bladder cancer can be used as a model to study the predictors and mechanisms of cancer immune response and shine light on further development of immunotherapy approaches and response predictive biomarkers to improve immunotherapy of bladder cancer and other malignancies. We review the success of BCG and anti-PD-1/PD-L1 treatment of bladder cancer, the underlying mechanisms and the therapeutic response predictors, including the limits to our knowledge. We then highlight briefly the adaptation of immunotherapy approaches and predictors developed in other cancers for bladder cancer therapy. Finally, we explore the potential of using bladder cancer as a model to investigate cancer immune response mechanisms and new therapeutic approaches, which may be translated into immunotherapy of other human cancers. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.

AA9int: SNP interaction pattern search using non-hierarchical additive model set.

Motivation: The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. Results: We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. Availability and implementation: The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. Supplementary information: Supplementary data are available at Bioinformatics online.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns.

Motivation: Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results: We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. Availability and Implementation: The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ . Contact: hlin1@lsuhsc.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

DNA replication-dependent induction of gene proximity by androgen.

The male hormone androgen, working through the androgen receptor (AR), plays a major role in physiological process and disease development. Previous studies of AR mainly focus on its transcriptional activity. Here, we found that androgen-induced TMPRSS2 and ERG gene proximity is mediated by AR control of DNA replication rather than gene transcription. We demonstrate that, in both AR transactivation-positive and -negative prostate cells, androgen regulates DNA replication and androgen-induced gene proximity relies on both DNA replication-licensing and actual DNA replication activity. Androgen stimulation advances DNA replication timing of certain genomic regions, which may potentially increase gene proximity through sharing the same replication factory at a similar time. Therefore, we have revealed novel mechanisms of AR biological function, which will stimulate new research directions.

Postchemotherapy changes in testicular germ cell tumours: biology and morphology.

Advances in modern chemotherapy and targeted treatments have resulted in lengthened survival in a variety of tumour types in the last decade. Increasingly in the 21st century, postchemotherapy resections are considered as a possible mode of treatment. Due to their exquisite chemosensitivity, resection of postchemotherapy masses has long been part of the armamentarium of treatment in testicular germ cell neoplasia, which has resulted in a variety of new morphological variants being described after treatment. Here we discuss the possible reasons for germ cell tumour chemosensitivity and hypotheses on the biological pathways leading to resistance to treatment, as well as an outline of the diverse morphology of those tumours which prove recalcitrant to standard treatment methods. The large range of morphologies and their diagnostic challenges may throw light upon the future problems to be encountered in non-germ cell solid tumour pathology, as the resection of postchemotherapy masses becomes increasingly important in patient management.

Protein S-palmitoylation and cancer.

Protein S-palmitoylation is a reversible posttranslational modification of proteins with fatty acids, an enzymatic process driven by a recently discovered family of protein acyltransferases (PATs) that are defined by a conserved catalytic domain characterized by a DHHC sequence motif. Protein S-palmitoylation has a prominent role in regulating protein location, trafficking and function. Recent studies of DHHC PATs and their functional effects have demonstrated that their dysregulation is associated with human diseases, including schizophrenia, X-linked mental retardation, and Huntington's Disease. A growing number of reports indicate an important role for DHHC proteins and their substrates in tumorigenesis. Whereas DHHC PATs comprise a family of 23 enzymes in humans, a smaller number of enzymes that remove palmitate have been identified and characterized as potential therapeutic targets. Here we review current knowledge of the enzymes that mediate reversible palmitoylation and their cancer-associated substrates and discuss potential therapeutic applications.

Amplification and over-expression of MAP3K3 gene in human breast cancer promotes formation and survival of breast cancer cells.

Gene amplifications in the 17q chromosomal region are observed frequently in breast cancers. An integrative bioinformatics analysis of this region nominated the MAP3K3 gene as a potential therapeutic target in breast cancer. This gene encodes mitogen-activated protein kinase kinase kinase 3 (MAP3K3/MEKK3), which has not yet been reported to be associated with cancer-causing genetic aberrations. We found that MAP3K3 was amplified in approximately 8-20% of breast cancers. Knockdown of MAP3K3 expression significantly inhibited cell proliferation and colony formation in MAP3K3-amplified breast cancer cell lines MCF-7 and MDA-MB-361 but not in MAP3K3 non-amplified breast cancer cells. Knockdown of MAP3K3 expression in MAP3K3-amplified breast cancer cells sensitized breast cancer cells to apoptotic induction by TNFα and TRAIL, as well as doxorubicin, VP-16 and fluorouracil, three commonly used chemotherapeutic drugs for treating breast cancer. In addition, ectopic expression of MAP3K3, in collaboration with Ras, induced colony formation in both primary mouse embryonic fibroblasts and immortalized human breast epithelial cells (MCF-10A). Combined, these results suggest that MAP3K3 contributes to breast carcinogenesis and may endow resistance of breast cancer cells to cytotoxic chemotherapy. Therefore, MAP3K3 may be a valuable therapeutic target in patients with MAP3K3-amplified breast cancers, and blocking MAP3K3 kinase activity with a small molecule inhibitor may sensitize MAP3K3-amplified breast cancer cells to chemotherapy.

Identification of ZDHHC14 as a novel human tumour suppressor gene.

Genomic changes affecting tumour suppressor genes are fundamental to cancer. We applied SNP array analysis to a panel of testicular germ cell tumours to search for novel tumour suppressor genes and identified a frequent small deletion on 6q25.3 affecting just one gene, ZDHHC14. The expression of ZDHHC14, a putative protein palmitoyltransferase with unknown cellular function, was decreased at both RNA and protein levels in testicular germ cell tumours. ZDHHC14 expression was also significantly decreased in a panel of prostate cancer samples and cell lines. In addition to our findings of genetic and protein expression changes in clinical samples, inducible overexpression of ZDHHC14 led to reduced cell viability and increased apoptosis through the classic caspase-dependent apoptotic pathway and heterozygous knockout of ZDHHC14 increased [CORRECTED] cell colony formation ability. Finally, we confirmed our in vitro findings of the tumour suppressor role of ZDHHC14 in a mouse xenograft model, showing that overexpression of ZDHHC14 inhibits tumourigenesis. Thus, we have identified a novel tumour suppressor gene that is commonly down-regulated in testicular germ cell tumours and prostate cancer, as well as given insight into the cellular functional role of ZDHHC14, a potential protein palmitoyltransferase that may play a key protective role in cancer.

Gonorrhea and Prostate Cancer Incidence: An Updated Meta-Analysis of 21 Epidemiologic Studies.

BACKGROUND: The association between gonorrhea and prostate cancer risk has been investigated widely, but the results remain inconsistent and contradictory. We conducted an updated meta-analysis to obtain a more precise estimate of this association. MATERIAL AND METHODS: PubMed, EMBASE, and the Cochrane Library were searched for papers up to June 2014 to identify eligible studies. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the influence of gonorrhea on prostate cancer risk. RESULTS: Twenty-one observational studies (19 case-control and 2 cohort) were eligible, comprising 9965 prostate cancer patients and 118 765 participants. Pooled results indicated that gonorrhea was significantly associated with increased incidence of prostate cancer (OR 1.31, 95% CI 1.14-1.52). The association between gonorrhea and prostate cancer was stronger in African American males (OR 1.32, 95% CI 1.06-1.65) than in Whites (OR 1.05, 95% CI 0.90-1.21). CONCLUSIONS: Our findings suggest that gonorrhea is associated with an increased risk of prostate cancer, especially among African American males. These results warrant further well-designed, large-scale cohort studies to draw definitive conclusions.

Direct interaction of platelet with tumor cell aggravates hepatocellular carcinoma metastasis by activating TLR4/ADAM10/CX3CL1 axis.

Metastasis is the main culprit of cancer-related death and account for the poor prognosis of hepatocellular carcinoma. Although platelets have been shown to accelerate tumor cell metastasis, the exact mechanism remained to be fully understood. Here, we found that high blood platelet counts and increased tumor tissue ADAM10 expression indicated the poor prognosis of HCC patients. Meanwhile, blood platelet count has positive correlation with tumor tissue ADAM10 expression. In vitro, we revealed that platelet increased ADAM10 expression in tumor cell through TLR4/NF-κB signaling pathway. ADAM10 catalyzed the shedding of CX3CL1 which bound to CX3CR1 receptor, followed by inducing epithelial to mesenchymal transition and activating RhoA signaling in cancer cells. Moreover, knockdown HCC cell TLR4 (Tlr4) or inhibition of ADAM10 prevented platelet-increased tumor cell migration, invasion and endothelial permeability. In vivo, we further verified in mice lung metastatic model that platelet accelerated tumor metastasis via cancer cell TLR4/ADAM10/CX3CL1 axis. Overall, our study provides new insights into the underlying mechanism of platelet-induced HCC metastasis. Therefore, targeting the TLR4/ADAM10/CX3CL1 axis in cancer cells hold promise for the inhibition of platelet-promoted lung metastasis of HCC.

Genomic evolution shapes prostate cancer disease type.

The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.

Identification of frequent BRAF copy number gain and alterations of RAF genes in Chinese prostate cancer.

We recently found that TMPRSS2:ERG fusion genes and PTEN loss, which are common in Western prostate cancers are infrequent in Chinese cases. As previous studies indicated a higher frequency of RAS and BRAF mutation rates in Eastern Asian than in Western prostate cancers and fusion genes involving the RAF family genes BRAF and RAF1 were recently identified in prostate cancer in the American population, we investigated BRAF and RAF1 alterations in Chinese prostate cancer. Using fluorescence in situ hybridization, we found that BRAF was truncated in five of 200 informative Chinese cases (2.5%) and that RAF1 was truncated in three of 204 informative cases (1.5%) and genomic rearrangements of these genes were significantly correlated with high Gleason scores (>7; P < 0.01) and have a trend to appear in high clinical stage disease. A high frequency of BRAF and RAF1 copy number gain was found (29 and 15%, respectively). BRAF copy number gain in Chinese cancers was significantly higher than in UK cases (9.2%)(P < 0.001) and correlated with a number of clinical parameters. High-level expression of BRAF was found by immunohistochemistry in Chinese cancer samples compared with adjacent nonmalignant epithelial cells, which was correlated with high BRAF copy number. We also identified KRAS codon 12 mutations in three of 96 Chinese cases, no BRAF V600E mutations were observed. Our finding suggests that the activation of the RAS/RAF/MEK/ERK pathway may be frequent in Chinese prostate cancer, with RAF gene copy number gain potentially being the main contributor.

High-resolution genome-wide copy-number analysis suggests a monoclonal origin of multifocal prostate cancer.

Many human cancers present as multifocal lesions. Understanding the clonal origin of multifocal cancers is of both etiological and clinical importance. The molecular basis of multifocal prostate cancer has previously been explored using a limited number of isolated markers and, although independent origin is widely believed, the clonal origin of multifocal prostate cancer is still debatable. We attempted to address clonal origin using a genome-wide copy-number analysis of individual cancer and high-grade prostatic intraepithelial neoplasia (HGPIN) lesions. Using Affymetrix array 6.0 copy-number analysis, we compared the genomic changes detected in 48 individual cancer and HGPIN lesions, isolated from 18 clinically localized prostate cancer cases. Identical genomic copy-number changes, shared by all same-case cancer foci, were detected in all 13 informative cases displaying multiple tumor foci. In addition, individual HGPIN lesions in the two multifocal-HGPIN cases available shared identical genomic changes. Commonly known genomic alterations, including losses at 6q15, 8p21.3-8p21.2, 10q23.2-10q23.31, 16q22.3, 16q23.2-16q23.3 and 21q22.2-21q22.3 regions and gain of 8q24.3 were the most frequently detected changes in this study and each was detected in all same-case foci in at least one case. Microarray data were confirmed by fluorescence in situ hybridization in selected foci. Our high-resolution genome-wide copy-number data suggest that many multifocal cases derive from a single prostate cancer precursor clone and that this precursor may give rise to separate HGPIN foci and may further progress to multifocal invasive prostate cancer. These findings, which demonstrate the monoclonal origin of multifocal prostate cancer, should significantly enhance our understanding of prostate carcinogenesis.