|Ahead of print publication
Integrative molecular characterization of Chinese prostate cancer specimens
Shi-Dong Lv1,2,3, Hong-Yi Wang3, Xin-Pei Yu4, Qi-Liang Zhai3, Yao-Bin Wu1,2, Qiang Wei3, Wen-Hua Huang1,2
1 National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
2 Guangdong Engineering Research Center for Translation of Medical 3D Printing Application, Guangzhou 510515, China
3 Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
4 Department of Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou 510095, China
|Date of Submission||13-Sep-2018|
|Date of Acceptance||21-Feb-2019|
|Date of Web Publication||28-May-2019|
Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Guangdong Engineering Research Center for Translation of Medical 3D Printing Application, Guangzhou 510515, China
Source of Support: None, Conflict of Interest: None
Prostate cancer (PCa) exhibits epidemiological and molecular heterogeneity. Despite extensive studies of its phenotypic and genetic properties in Western populations, its molecular basis is not clear in Chinese patients. To determine critical molecular characteristics and explore correlations between genomic markers and clinical parameters in Chinese populations, we applied an integrative genetic/transcriptomic assay that combines targeted next-generation sequencing and quantitative real-time PCR (qRT-PCR) on samples from 46 Chinese patients with PCa. Lysine (K)-specific methyltransferase 2D (KMT2D), zinc finger homeobox 3 (ZFHX3), A-kinase anchoring protein 9 (AKAP9), and GLI family zinc finger 1 (GLI1) were frequently mutated in our cohort. Moreover, a clinicopathological analysis showed that RB transcriptional corepressor 1 (RB1) deletion was common in patients with a high risk of disease progression. Remarkably, four genomic events, MYC proto-oncogene (MYC) amplification, RB1 deletion, APC regulator of WNT signaling pathway (APC) mutation or deletion, and cyclin-dependent kinase 12 (CDK12) mutation, were correlated with poor disease-free survival. In addition, a close link between KMT2D expression and the androgen receptor (AR) signaling pathway was observed both in our cohort and in The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) data. In summary, our results demonstrate the feasibility and benefits of integrative molecular characterization of PCa samples in disease pathology research and personalized medicine.
Keywords: androgen receptor; molecular subtyping; next generation sequencing; prostate cancer; quantitative real-time-polymerase chain reaction
Article in PDF
|How to cite this URL:|
Lv SD, Wang HY, Yu XP, Zhai QL, Wu YB, Wei Q, Huang WH. Integrative molecular characterization of Chinese prostate cancer specimens. Asian J Androl [Epub ahead of print] [cited 2019 Aug 20]. Available from: http://www.ajandrology.com/preprintarticle.asp?id=259205
| Introduction|| |
Prostate cancer (PCa) is the second most frequent malignancy in men worldwide, accounting for more than 300 000 cancer-related deaths per year. In China, approximately 6.03% of adult males were suspected to have PCa in 2015, and the annual incidence of PCa in the Chinese population is increasing by 4.7%. Actionable molecular sequencing is a plausible and promising strategy for improving treatment results by targeted therapy. However, the incidence, prognosis, and treatment outcomes differ among ethnicities due to heterogeneity at the genetic and phenotypic levels., Genetic and transcriptional alterations have been studied extensively in Western populations; however, little is known about the genomic aberrations associated with the pathogenesis of PCa in Chinese populations.
Next-generation sequencing (NGS) has enabled extensive profiling of genome-wide alterations during PCa tumorigenesis. Recent sequencing studies have revealed various somatically acquired genetic, epigenetic, and transcriptional changes in PCa, such as alterations in phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), tumor protein P53(TP53), speckle type BTB/POZ protein (SPOP), chromodomain helicase DNA-binding protein 1 (CHD1), and external transcribed spacer (ETS) transcription factor family. Notably, NGS approaches not only provide numerous insights into the molecular-based pathogenesis but also identify specific biomarkers for better patient stratification and targeted therapy. The hyperactivation of oncogenic signaling pathways, such as phosphatidylinositol 3-kinase (PI3K)/phosphatase and tensin homolog (PTEN)/AKT, is considered a prognostic biomarker for PCa and is closely correlated with advanced localized or metastatic disease.SPOP, CHD1, andETS transcription factor (ERG) statuses can be used for segregation, as they suggest future androgen receptor (AR) loss and possibly aggressive cancer development. DNA repair pathway defects indicate that patients would benefit from treatment with a poly(ADP)-ribose polymerase (PARP) inhibitor that has been approved by the US Food and Drug Administration for metastatic castration-resistant PCa monotherapy. Hence, discovering and validating genomic aberrations is urgently needed for PCa prediction, prognosis, and treatment in Chinese patients.
In this study, we performed a comprehensive molecular characterization of Chinese patients with PCa and explored correlations between identified genomic markers and clinical factors. We used quantitative real-time PCR (qRT-PCR) to detect the expression of focal PCa-related genes in 46 Chinese PCa samples. Moreover, we reanalyzed previously generated gene sequencing data and detected copy number variants (CNVs) by identifying clustered amplicons with significant changes in normalized log2 read depth. We provide an integrative overview of genetic/transcriptomic alterations in Chinese patients with PCa; these findings will improve our understanding of disease biology and have implications for personalized medicine.
| Patients and Methods|| |
Patients and samples
The study included a total of 46 PCa samples collected at Nanfang Hospital (Guangzhou, China). All samples were histologically confirmed as PCa by two independent pathologists. Patients who received preoperative hormone therapy, chemotherapy, and radiotherapy were excluded. Detailed information for all samples is summarized in [Supplementary Table 1 [Additional file 1]]. This study was approved by the Medical Ethics Committee of Nanfang Hospital (NFEC-2017-145), and the specimens were used with written informed consent by the Department of Pathology, Nanfang Hospital, in accordance with the Declaration of Helsinki.
DNA extraction, amplicon capture, next-generation sequencing, and analysis
Samples for targeted NGS were dissected from 4-mm unstained sections, and genomic DNA was extracted using a GeneRead DNA FFPE Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol. The extracted DNA was quantified using a Qubit fluorometer (Invitrogen, Carlsbad, CA, USA). Genomic DNA with a yield of >40 ng was used for library preparation. Amplicon enrichment was performed using the prostate cancer panel within the GeneRead DNAseq Targeted Panels V2 (Qiagen). Library preparation was performed using the GeneRead DNA Library Core Kit for Ion Torrent Proton (Qiagen) and barcoded with Ion Xpress™ Barcode Adapters (Thermo Fisher, Waltham, MA, USA). Sequencing of barcoded pools was performed using the Ion Torrent Proton, and the data were evaluated using Cloud-Based DNAseq Sequence Variant Analysis (Qiagen). Called variants were filtered by Ion Reporter (Thermo Fisher) to remove synonymous or noncoding variants and University of California, Santa Cruz (UCSC) common single-nucleotide polymorphisms (SNPs). High-confidence candidate somatic drivers were included in subsequent analyses.
For CNV determination, germline DNA (extracted from peripheral blood mononuclear cells) was collected from seven independent healthy males and sequenced to obtain the CNV baseline. CNV calling was performed using Cloud-Based DNAseq Sequence Variant Analysis. For targeted genes, CNVs were defined as clustered amplicons with significant changes in normalized log2 read depth, as previously reported. In particular, CNVs were evaluated as follows. 1) Amplicons were grouped into clusters of neighbors at a genomic locus (amplicon clustering). 2) The log2 read depth at each priming site was compared between sample and control datasets (filtered clustering). P-values were calculated by weighted t-tests (total read depth was used as the weight). 3) Only CNV calls with scores of >50 indicated strong evidence (CNV identification).
RNA extraction, reverse transcription, and PCR analysis
The same tissues for NGS were used to isolate RNA using the AllPrep DNA/RNA FFPE Kit (Qiagen) according to the manufacturer's protocol. The extracted RNA was quantified using a Qubit fluorometer (Thermo Fisher). Reverse transcription (RT) of 1 μg of RNA was performed using the QuantiTect Reverse Transcription Kit (Qiagen). The RT product was mixed with nuclease-free water, primers, and the SYBR Premix Ex Taq II Kit (Takara, Shiga, Japan). Quality PCR was performed using the CFX384 Touch Real-Time PCR system (Bio-Rad, Hercules, CA, USA). Data were analyzed using the 2−ΔΔCt method, and normalized target gene expression was visualized using R statistical software (GraphPad Software, La Jolla, CA, USA).
Kaplan–Meier analysis was performed using R statistical software. Disease-free survival (DFS) was defined as the time from diagnosis to recurrence or date of last follow-up. The log-rank test was used to calculate the P- values or the Kaplan–Meier analysis.
A large prostate cancer dataset from the Cancer Genome Atlas (TCGA), with both gene expression and clinical follow-up data, was used for the correlation analysis. Level 3 gene expression data were downloaded from TCGA data portal (https://tcga-data.nci.nih.gov/tcga/). RNA-seq by Expectation-Maximization (RSEM) normalized expression data were obtained.
Correlations between the recurrently altered genes and clinical parameters were evaluated using Fisher's tests; gene expression correlations were evaluated based on Pearson's correlation coefficients, as determined using R statistical software.
| Results|| |
Application of integrative genetic/transcriptomic assays for Chinese clinical formalin-fixed paraffin-embedded (FFPE) PCa samples
To identify the genetic and transcriptomic spectra of genes associated with the pathogenesis of PCa in Chinese patients, we performed integrative DNA- and RNA-based assays requiring only approximately 50 ng of FFPE DNA and 500 ng of FFPE RNA. The assays consist of a multiplex PCR-based panel for gene sequencing and a qRT-PCR array for the detection of gene expression. The gene sequencing panel was used for target enrichment of the exonic regions of the 32 most commonly mutated genes in human PCa samples, and the amplification or deletion of these genes was evaluated as described previously. The qRT-PCR assay included 28 genes, including robust housekeeping genes, AR transcriptional modules, cell cycle-related genes, and genes defining molecular subtypes or molecular drivers based on previous transcriptomic studies [Supplementary Table 1]. The integrative assays were performed using samples obtained from a cohort of 46 Chinese patients with PCa after radical prostatectomy or transurethral resection of the prostate [Supplementary Table 2 [Additional file 2]].
Mutation and copy number variant detection by targeted gene sequencing
Ion Torrent NGS after multiplex PCR-based targeted enrichment was applied to 46 FFPE PCa samples, yielding an average of 6 243 762 mapped reads and an average coverage of 3527× (1156–5419×) over targeted bases per sample. The complete coverage details are provided in [Supplementary Table 3 [Additional file 3]]. An initial 5909 variants were filtered for quality, SNPs, and functional relevance. As described previously, we identified 245 nonsynonymous (missense, in-frame deletion, nonsense, stop-loss, and frameshift) mutations with an allele frequency of ≥3% in all sequencing specimens (average: 5; range: 1–34) across 27 genes. All high-confidence mutations are shown in a heatmap in [Figure 1] and are detailed in [Supplementary Table 4 [Additional file 4]]. The most frequently mutated genes were lysine (K)-specific methyltransferase 2D(KMT2D, 63.04%), zinc finger homeobox 3 (ZFHX3, 50.00%), A-kinase anchoring protein 9 (AKAP9, 32.61%), GLI family zinc finger 1 (GLI1, 32.61%), thrombospondin type 1 domain containing 7B(THSD7B, 19.57%), APC regulator of WNT signaling pathway (APC, 15.22%), cyclin-dependent kinase 12 (CDK12, 15.22%), lysine demethylase 4B (KDM4B, 15.22%), mediator complex subunit 12 (MED12, 15.22%), and zinc finger protein 595 (ZNF595, 15.22%).
|Figure 1: Integrative molecular profiling of Chinese FFPE prostate cancer (PCa) samples. A heatmap of somatic alterations for each sample is shown. Clinicopathological information is provided in the header, including Gleason score, T stage, tumor percentage, and molecular subtype based on qRT-PCR analysis. High-level somatic CNVs and mutations are indicated according to the legend. FFPE: formalin-fixed paraffin-embedded; qRT-PCR: quantitative real-time polymerase chain reaction; CNVs: copy number variants. All abbreviated names of genes are defined in Supplementary Table 6|
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Using an approach adapted from multiplexed PCR-based targeted Ion Torrent NGS data, we simultaneously assessed CNVs in 25 genes, yielding a total of 312 high-level CNVs across the 46 PCa specimens (average: 7 high-level CNVs per sample; range: 0–15). A copy number heatmap for all samples is shown in [Figure 1].
Assessment of critical PCa transcriptomic alterations by qRT-PCR
We performed qRT-PCR using RNA isolated from the sequencing cohort of 43 FFPE PCa samples (the sequencing samples, excluding those with low RNA quality). Normalized target gene expression is shown in [Figure 2]. Combined with target sequencing, we performed basic PCa molecular subtyping for the 43 Chinese patients [Figure 1] and [Figure 2]. TMPRSS2:ERG was detected in nine cancer samples, which showed approximately 70-fold greater TMPRSS2:ERG expression than the median of the 34 other TMPRSS2:ERG-negative samples. Two samples showed marked ETS variant 4(ETV4) overexpression, indicating the presence of a gene fusion in this ETS family member. Overexpression of serine peptidase inhibitor, Kazal type 1(SPINK1), was identified in four samples (the SPINK1+ subtype). Moreover, by targeted gene sequencing, we observed high-confidence SPOP mutations in samples PR110, PR112, and PR203, each of which was ETS-negative by qRT-PCR. Among these samples, PR203 also showed high SPINK1 expression, suggesting the overlap of these alterations.
[Supplementary Table 6 [Additional file 7]]
|Figure 2: Gene expression signatures of PCa assessed by qRT-PCR. Unsupervised hierarchical clustering of gene expression signatures for PCa-related genes. Normalized target gene expression (log2) for 28 robust target genes assessed by the qRT-PCR panel. qRT-PCR: quantitative real-time polymerase chain reaction; PCa: prostate cancer. All abbreviated names of genes are defined in Supplementary Table 6|
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AR-targeted genes were included based on previous microarray analyses of genes regulated by androgens in PCa. Our results showed that the AR signature was heterogeneous in all treatment-naïve PCa specimens. AR activity might predict the response to therapies targeting the AR axis. PR315 and PRY04 had markedly lower AR activity than that of other samples, suggesting different responses to anti-androgen therapy compared with those of samples with high AR activity.
In addition, four cell cycle-related genes, nucleolar and spindle-associated protein 1(NUSAP1), kinesin family member 11 (KIF11), cell division cycle 20(CDC20), and forkhead box M1 (FOXM1), were evaluated as indicators of cell proliferation, a fundamental aspect of tumor biology. Most of the samples showed relatively low expression of cell cycle progression genes, suggesting low aggressiveness in the early stages of PCa. Our results support the use of qRT-PCR as a complementary approach to target gene sequencing for assessing critical transcriptomic events in PCa.
Molecular features correlated with clinical characteristics and prognosis
We subdivided the genomic aberrations in Chinese PCa patients identified by integrative genetic/transcriptomic assays into nine specific pathways [Supplementary Table 5 [Additional file 5]]. These molecules are commonly altered in Western patients with PCa and have clinical implications. We analyzed the correlations between these genomic aberrations and clinicopathological characteristics, including prostate-specific antigen (PSA) level, Gleason score, T stage, distant metastasis, and clinical risk stratification from the National Comprehensive Cancer Network (NCCN) and the European Association of Urology (EAU). As shown in [Supplementary Table 5], activation of the PI3K/AKT/PTEN pathway and deletion of RB transcriptional corepressor 1(RB1) were dramatically correlated with older age (P = 0.035 and P = 0.041, respectively). The ETS fusion was more common in patients at an advanced T stage (P = 0.030). Notably, an increased risk of progression was found in patients with the RB1 deletion, both in NCCN risk stratification (P = 0.006) and in EAU risk classification (P = 0.022). In addition, recurrent mutated or copy number-altered genes were included in the correlation analysis. GLI mutation was notably correlated with distant metastasis (P = 0.030).
The prognostic impacts of the five specific pathways and recurrently altered genes were assessed. Log-rank tests were used to analyze the outcome for each individual subtype. MYC proto-oncogene (MYC) amplification (P = 0.036), RB1 deletion (P = 0.029), APC mutation/deletion (P = 0.032), and CDK12 mutation (P = 0.029) were associated with worse progression-free survival (PFS) in the 46 Chinese patients with PCa [Figure 3]. Furthermore, we explored the clinical characteristics related to prognosis in Chinese populations. As expected, PFS decreased with increasing T stage (P = 0.0024), distant metastasis (P = 0.0012), NCCN risk stratification (P = 0.0011), and EAU risk classification (P = 0.00039) [Supplementary Figure 1 [Additional file 6]]). These results indicated a high predictive value of these risk factors, which may contribute to clinical decision-making in Chinese patients with PCa.
KMT2D is positively correlated with the AR signaling pathway in PCa
Another advantage of the integrative genetic/transcriptomic assay is the ability to explore the correlations underlying recurrently altered genes. We performed a correlation analysis of the expression of the 27 robust target genes across all samples. We observed correlated expression of genes within the AR signaling pathway and cell cycle progression modules [Figure 4]a. In particular, positive correlations were identified between KMT2D and AR (r = 0.31, P = 0.046), the AR downstream target calcium/calmodulin-dependent protein kinase kinase 2(CAMKK2)(r = 0.45, P = 0.046), the cell cycle progression gene CDC20 (r = 0.32, P = 0.037), and SPINK1 (r = 0.40, P = 0.008) [Figure 4]b. Because the AR signaling pathway is indispensable for PCa carcinogenesis, we further validated the correlation between KMT2D and AR signaling using the Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) data. Consistent with our qRT-PCR results, KMT2D expression was strongly correlated with AR mRNA levels (r = 0.70, P < 0.001; [Figure 4]c left) and AR protein levels (r = 0.32, P < 0.001; [Figure 4]c right). Patients with AR-V7 had higher KMT2D expression (P = 0.036; [Figure 4]d), suggesting that KMT2D contributes to the AR splice variants. These findings highlight the close linkage between KMT2D and AR signaling and suggest that KMT2D plays a critical role in the activation of the AR axis in PCa.
|Figure 3: MYC amplification, RB1 deletion, APC mutation/deletion, and CDK12 mutation are linked to worse prognosis in our cohort. Survival analysis was performed in Chinese PCa patients treated according to the presence or absence of (a) MYC amplification, (b) RB1 deletion, (c) APC mutation/deletion, and (d) CDK12 mutation. PCa: prostate cancer; MYC: MYC proto-oncogene, bHLH transcription factor; RB1: RB transcriptional corepressor 1; APC: APC regulator of WNT signaling pathway; CDK12: Cyclin-dependent kinase 12.|
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|Figure 4: KMT2D is positively correlated with the AR signaling pathway in PCa. (a) Heatmap of correlations (r) between normalized gene expression for the 27 robust target genes across all samples shown in Figure 2. (b) KMT2D mRNA levels were positively correlated with AR, CAMKK2, CDC20, and SPINK1 expression in PCa tissues in our cohort. (c) KMT2D mRNA levels were positively correlated with both gene and protein expression of AR in TCGA-PRAD. (d) mRNA expression of KMT2D in AR-V7-positive and AR-V7-negative cases from TCGA-PRAD. PCa: prostate cancer; TCGA-PRAD: The Cancer Genome Atlas Prostate Adenocarcinoma. All abbreviated names of genes are defined in [Supplementary Table 6].|
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| Discussion|| |
We used a rapid, robust, and high-throughput approach for the characterization of gene mutations, copy number variants, and crucial transcriptomic events in Chinese patients with PCa by combined multiple-PCR-based deep NGS and qRT-PCR. This integrative assay required only 50 ng of DNA and 500 ng of RNA, which can be co-isolated from most routine clinical samples, making it practical for academic research settings as well as routine clinical settings. In this study, we added to the current knowledge of the genetic heterogeneity of prostate tumors among ethnic populations and identified correlations between clinical and prognostic factors and recurrently altered genes, providing a basis for therapeutic decisions. Moreover, we observed a close relationship between KMT2D and AR signaling in a gene co-expression analysis, highlighting the important role of KMT2D in the activation of the AR axis in PCa.
Our findings expand our understanding of the ethnicity-specific molecular landscape of PCa. As a heterogeneous disease, previous studies have reported notable disparities in PCa epidemiology among ethnic groups. Emerging evidence suggests that these differences might be the result of distinct molecular characteristics., Ren et al. identified salient genetic characteristics of PCa in Chinese patients. Similarly, the molecular profiles of Chinese patients with PCa identified in our cohort differed from that of Western patients. The most frequently mutated genes were KMT2D, ZFHX3, AKAP9, and GLI1 in our cohort; recurrently mutated genes in Western populations are SPOP, titin(TTN), TP53, mucin 16(MUC16), MED12, and Forkhead Box A1 (FOXA1). These results might be due to either de novo ethnicity-specific mutations in Chinese patients or high-depth sequencing effects. Asian and Western populations have distinct genetic polymorphisms,, familial aggregation, and diet. Basic science and epidemiological studies have demonstrated that these factors have a role in the clinical heterogeneity of PCa. Thus, the differences in these factors might influence the tumor genome and contribute to the ethnic genetic heterogeneity of PCa. Moreover, unlike other large-scale sequencing studies in Western patients, in which the sequencing depth is about 100×, in this study, we focused on 32 PCa-correlated genes and the average sequencing depth was approximately 3527×. The higher sequencing depth can remarkably increase the sensitivity of single-nucleotide variant detection; hence, the high coverage might account for the high mutation frequency of some genes in our cohort.
In addition to mutation, using an algorithm developed by Grasso et al., we detected CNVs in our amplicon-based sequencing data. We observed copy number gains of KMT2D, AKAP9, MYC, and GLI and copy number losses of PTEN, RB1, and APC in Chinese patients. PTEN inactivation and copy number deletions account for the majority of PTEN loss-of-function cases. We found a low frequency of these genomic changes, i.e., 23.9% (11/46) in our cohort, compared with approximately 40% in Western samples.MYC amplification and RB1 deletion are two major CNVs detected in multiple genomic analyses. We also found MYC gains (60.9%, 28/46) and RB1 deletions (45.7%, 21/46) in our samples. However, the frequencies were higher than those in Western populations, in which MYC amplification and RB1 were deleted in 7.4% (37/498) and 16.3% (81/498) cases from TCGA-PRAD, respectively. For critical transcriptomic events, we identified a lower frequency of the ETS fusion (23.9%, 11/46) in our patients than in Caucasian patients (with a prevalence of approximately 50%). The results of other large-scale studies further support the low frequency of the ETS fusion in Asian patients,,, indicating regional differences in molecular subtypes.
Furthermore, we identified clinical associations for the recurrently altered genes. Copy number deletion of RB1 was remarkably correlated with a high risk of disease progression. ETS fusion and GLI1 mutations were more common in patients with a higher T stage and distant metastasis, respectively, than in other patients. Importantly, poor prognosis was associated with various alterations, including MYC amplification, RB1 deletion, APC mutation or deletion, and CDK12 mutation. MYC and RB1 are involved in the regulation of the cell cycle; amplification of MYC prompts progression from G1 to S phase,, and MYC amplification status is predictive of biochemical recurrence after prostatectomy. However, its mRNA or protein levels show weak prognostic ability. RB1 is a critical negative regulator of the G1–S checkpoint and is responsible for repressing E2F family transcription factors. According to a recent study, RB1 deletion occurs early in PCa, prior to subclonal diversification. Consistent with our results, a large PCa tissue microarray study indicated that the deletion of RB1 is linked to an adverse phenotype and poor prognosis in this disease. APC is a multifunctional protein and is as a negative regulator of the Wnt pathway. The inactivation of APC by mutations or hypermethylation is associated with tumor aggressiveness., In Chinese populations, Geng et al. showed that APC mutations are associated with both PCa progression and all-cause mortality. CKD12 is a cyclin-dependent kinase; however, Wu et al. found that inactivation of CDK12 could define a distinct subtype of PCa, leading to increased neoantigen burden and T cell infiltration. Moreover, the loss of CDK12 is associated with genomic instability and predicts a worse poor prognosis in breast cancer. These findings further indicated that these genomic events are associated with clinical parameters and might serve as biomarkers in Chinese patients. However, given the small sample size, an independent cohort of patients is needed to confirm these results in the future.
Our integrative genetic/transcriptomic assays might also have utility for personalized medicine. The five main pathways involved in our analysis have clinical implications, and drugs targeting these alterations have been developed. For instance, the PI3K/AKT/PTEN pathway was upregulated in 34.78% of samples in our cohort. Therapeutically, to target this pathway, pan-PI3K and dual PI3K–mTOR inhibitors have been developed, and the AKT-targeting drugs BKM120 and MK-2206 show clinical efficacy in PCa. Cancer immunotherapies have become a revolutionized approach to the treatment of cancers, including PCa. The inactivation of CDK12 delineates a distinct immunogenic class of PCa, and a clinical study showed that patients with metastatic PCa who harbor a biallelic CDK12 loss have a higher likelihood of response to immunotherapy. In our cohort, 15.22% (7/46) of patients had CDK12 mutations. Among them, PR110, PR113, PR206, and PR309 were in an advanced state and relapsed after radical prostatectomy. These patients might benefit from immune checkpoint inhibitors after progression to the final stage of this disease. In addition, we evaluated AR signaling pathway activity. Consistent with previous results, most of our treatment-naïve cases showed high AR activity, indicating a better response to anti-androgen therapy. Compared with other cases, PR305 and PRY04 showed decreased AR activity, suggesting a heterogeneous response. Therefore, careful attention is needed when administering hormonal therapy. Above all, our findings suggest that molecular profiling using a targeted panel could provide valuable information, i.e., personalized mutation profiles for actionable targets, thereby contributing to clinical treatment decisions.
Notably, we detected a close link between KMT2D and the AR signaling pathway in our cohort using the integrative assays. These results were further confirmed using an additional dataset, TCGA-PRAD, showing that KMT2D expression was positively correlated with AR expression at the mRNA and protein level. Moreover, AR-V7-positive patients had high KMT2D expression levels. KMT2D is a histone lysine methyltransferase involved in the monomethylation of H3K4 residues (histone H3 lysine 4-monomethylation, H3K4me1). We previously concluded that, in PCa, KMT2D epigenetically upregulates LIF receptor alpha (LIFR)and Kruppel-like factor 4 (KLF4) expression, activating PI3K/AKT and epithelial–mesenchymal transition (EMT) oncogenic pathways and promoting PCa outgrowth and metastasis. Recent studies have reported that KMT2D is a transcriptional coactivator that recognizes target genes via DNA-bound transcription factors. In breast cancer, KMT2D is required for FOXA1, PBX homeobox 1 (PBX1), and estrogen receptor (ER) recruitment and activation and contributes to resistance to PI3Kα inhibitors. Thus, the positive correlation between KMT2D and the AR signaling pathway raises the possibility that KMT2D serves as a transcriptional coactivator and controls AR activation through posttranslational modification of epigenetic regulators. Further research is required to comprehensively clarify the role of KMT2D in PCa.
| Conclusion|| |
We applied an integrative approach to identify the critical genomic and transcriptomic events in 46 routine clinical Chinese PCa samples. This approach is helpful in characterizing retrospective material and analyzing correlations between clinical parameters and molecular changes. More importantly, focused assessments of genomic and transcriptomic features are important for disease pathology research as well as for advancements in personalized medicine.
| Author Contributions|| |
SDL carried out the study design, data acquisition, statistical analysis, and interpretation and drafted and revised the manuscript. HYW carried out the data acquisition and statistical analysis. XPY participated in the study design and coordination and helped draft the manuscript. QLZ helped data acquisition. YBW provided the important suggestions for manuscript revision. QW and WHH supervised the study and provided the fund support. All authors read and approved the final manuscript.
| Competing Interests|| |
All authors declared no competing interests.
| Acknowledgments|| |
This work was mainly supported by the National Key R&D Program of China (No. 2017YFC1103403), the National Natural Science Foundation of China (No. 21773199, No. 61427807 and No. 81872092), the Sanming Project of Medicine in Shenzhen (No. SZSM201612019), and the PhD Start-up Fund of Natural Science Foundation of Guangdong Province of China (No. 2016A030310287).
Supplementary Information is linked to the online version of the paper on the Asian Journal of Andrology website.
| References|| |
Chen W, Zheng R, Baade PD, Zhang S, Zeng H, et al.
Cancer statistics in China, 2015. CA Cancer J Clin
2016; 66: 115–32.
Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, et al.
Global cancer statistics, 2012. CA Cancer J Clin
2015; 65: 87–108.
Kimura T. East meets West: ethnic differences in prostate cancer epidemiology between East Asians and Caucasians. Chin J Cancer
2012; 31: 421–9.
Cancer Genome Atlas Research Network. The molecular taxonomy of primary prostate cancer. Cell
2015; 163: 1011–25.
Barbieri CE, Bangma CH, Bjartell A, Catto JW, Culig Z, et al.
The mutational landscape of prostate cancer. Eur Urol
2013; 64: 567–76.
Yadav SS, Li J, Lavery HJ, Yadav KK, Tewari AK. Next-generation sequencing technology in prostate cancer diagnosis, prognosis, and personalized treatment. Urol Oncol
2015; 33: 267.e1–13.
Mateo J, Boysen G, Barbieri CE, Bryant HE, Castro E, et al.
DNA repair in prostate cancer: biology and clinical implications. Eur Urol
2017; 71: 417–25.
Lv S, Ji L, Chen B, Liu S, Lei C, et al.
Histone methyltransferase KMT2D sustains prostate carcinogenesis and metastasis via epigenetically activating LIFR and KLF4. Oncogene
2017; 37: 1354–68.
Grasso C, Butler T, Rhodes K, Quist M, Neff TL, et al.
Assessing copy number alterations in targeted, amplicon-based next-generation sequencing data. J Mol Diagn
2015; 17: 53–63.
Mendiratta P, Mostaghel E, Guinney J, Tewari AK, Porrello A, et al.
Genomic strategy for targeting therapy in castration-resistant prostate cancer. J Clin Oncol
2009; 27: 2022–9.
Cuzick J, Swanson GP, Fisher G, Brothman AR, Berney DM, et al.
Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol
2011; 12: 245–55.
Spratt DE, Zumsteg ZS, Feng FY, Tomlins SA. Translational and clinical implications of the genetic landscape of prostate cancer. Nat Rev Clin Oncol
2016; 13: 597–610.
Zhau HE, Li Q, Chung LW. Interracial differences in prostate cancer progression among patients from the United States, China and Japan. Asian J Androl
2013; 15: 705–7.
Ren S, Wei GH, Liu D, Wang L, Hou Y, et al.
Whole-genome and transcriptome sequencing of prostate cancer identify new genetic alterations driving disease progression. Eur Urol
2017. Doi: 10.1016/j.eururo.2017.08.027. [Epub ahead of print].
Mao X, Yu Y, Boyd LK, Ren G, Lin D, et al.
Distinct genomic alterations in prostate cancers in Chinese and Western populations suggest alternative pathways of prostate carcinogenesis. Cancer Res
2010; 70: 5207–12.
Ren S, Wei GH, Liu D, Wang L, Hou Y, et al.
Whole-genome and transcriptome sequencing of prostate cancer identify new genetic alterations driving disease progression. Eur Urol
2018; 48: 86.
Fraser M, Sabelnykova VY, Yamaguchi TN, Heisler LE, Livingstone J, et al.
Genomic hallmarks of localized, non-indolent prostate cancer. Nature
2017; 541: 359–64.
Edwards A, Hammond HA, Jin L, Caskey CT, Chakraborty R. Genetic variation at five trimeric and tetrameric tandem repeat loci in four human population groups. Genomics
1992; 12: 241–53.
Irvine RA, Yu MC, Ross RK, Coetzee GA. The CAG and GGC microsatellites of the androgen receptor gene are in linkage disequilibrium in men with prostate cancer. Cancer Res
1995; 55: 1937–40.
Fukabori Y, Ohtake N, Nakata S, Suzuki K. [Characteristics of hereditary and familial prostate cancer in Japan 2011]. Nihon Rinsho
2011; 69 Suppl 5: 197–202. [Article in Japanese].
Norie K, Motoki I, Manami I, Shizuka S, Shoichiro T. Plasma isoflavones and subsequent risk of prostate cancer in a nested case-control study: the Japan Public Health Center. J Clin Oncol
2008; 26: 5923–9.
Kazuto I. Prostate cancer in Asian men. Nat Rev Urol
2014; 11: 197–212.
Ming-Tseh L, Mosier SL, Michele T, Beierl KF, Marija D, et al.
Clinical validation of KRAS, BRAF,
mutation detection using next-generation sequencing. Am J Clin Pathol
2014; 141: 856–66.
Magigalluzzi C, Tsusuki T, Elson P, Simmerman K, Lafargue C, et al.TMPRSS2-ERG
gene fusion prevalence and class are significantly different in prostate cancer of Caucasian, African-American and Japanese patients. Prostate
2011; 71: 489–97.
Miyagi Y, Sasaki T, Fujinami K, Sano J, Senga Y, et al.ETS
family-associated gene fusions in Japanese prostate cancer: analysis of 194 radical prostatectomy samples. Mod Pathol
2010; 23: 1492.
Boutros PC, Fraser M, Harding NJ, De BR, Trudel D, et al.
Spatial genomic heterogeneity within localized, multifocal prostate cancer. Nat Genet
2015; 47: 736–45.
Fromont G, Godet J, Peyret A, Irani J, Celhay O, et al.
8q24 amplification is associated with Myc expression and prostate cancer progression and is an independent predictor of recurrence after radical prostatectomy. Hum Pathol
2013; 44: 1617–23.
Pettersson A, Gerke T, Penney KL, Lis RT, Stack EC, et al.
MYC overexpression at the protein and mRNA level and cancer outcomes among men treated with radical prostatectomy for prostate cancer. Cancer Epidemiol Biomarkers Prev
2018; 27: 201–7.
Knudsen ES, Knudsen KE. Tailoring to RB: tumour suppressor status and therapeutic response. Nat Rev Cancer
2008; 8: 714–24.
Smg E, Liu LY, Rubanova Y, Bhandari V, Holgersen EM, et al.
The evolutionary landscape of localized prostate cancers drives clinical aggression. Cell
Kluth M, Scherzai S, Büschek F, Fraune C, Möller K, et al.
13q deletion is linked to an adverse phenotype and poor prognosis in prostate cancer. Genes Chromosomes Cancer
2018; 57: 504–12.
Näthke IS. The adenomatous polyposis coli protein: the Achilles heel of the gut epithelium. Annu Rev Cell Dev Biol
2004; 20: 337–66.
Cho NY, Kim JH, Moon KC, Kang GH. Genomic hypomethylation and CpG island hypermethylation in prostatic intraepithelial neoplasm. Virchows Arch
2009; 454: 17–23.
Costa VL, Henrique R, Jerónimo C. Epigenetic markers for molecular detection of prostate cancer. Dis Markers
2007; 23: 31–41.
Geng JH, Lin VC, Yu CC, Huang CY, Yin HL, et al.
Inherited variants in Wnt pathway genes influence outcomes of prostate cancer patients receiving androgen deprivation therapy. Int J Mol Sci
2016; 17: 1970.
Wu YM, Cieślik M, Lonigro RJ, Vats P, Reimers MA, et al.
Inactivation of CDK12 delineates a distinct immunogenic class of advanced prostate cancer. Cell
2018; 173: 1770–82.e14.
Guffanti F, Fruscio R, Rulli E, Damia G. The impact of DNA damage response gene polymorphisms on therapeutic outcomes in late stage ovarian cancer. Sci Rep
2016; 6: 38142.
Sharma P, Allison JP. Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential. Cell
2015; 161: 205–14.
Kim DH, Kim J, Kwon JS, Sandhu J, Tontonoz P, et al.
Critical roles of the histone methyltransferase MLL4/KMT2D in murine hepatic steatosis directed by ABL1 and PPARγ2. Cell Rep
2016; 17: 1671–82.
Toska E, Osmanbeyoglu HU, Castel P, Chan C, Hendrickson RC, et al.
PI3K pathway regulates ER-dependent transcription in breast cancer through the epigenetic regulator KMT2D. Science
2017; 355: 1324–30.
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