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.

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.

Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry.

Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS 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 GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . 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 OR 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. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 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 OR (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 data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.

Circulating tumour cells for early detection of clinically relevant cancer.

Given that cancer mortality is usually a result of late diagnosis, efforts in the field of early detection are paramount to reducing cancer-related deaths and improving patient outcomes. Increasing evidence indicates that metastasis is an early event in patients with aggressive cancers, often occurring even before primary lesions are clinically detectable. Metastases are usually formed from cancer cells that spread to distant non-malignant tissues via the blood circulation, termed circulating tumour cells (CTCs). CTCs have been detected in patients with early stage cancers and, owing to their association with metastasis, might indicate the presence of aggressive disease, thus providing a possible means to expedite diagnosis and treatment initiation for such patients while avoiding overdiagnosis and overtreatment of those with slow-growing, indolent tumours. The utility of CTCs as an early diagnostic tool has been investigated, although further improvements in the efficiency of CTC detection are required. In this Perspective, we discuss the clinical significance of early haematogenous dissemination of cancer cells, the potential of CTCs to facilitate early detection of clinically relevant cancers, and the technological advances that might improve CTC capture and, thus, diagnostic performance in this setting.

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.

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.

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.

Association between maternal MTHFR C677T/A1298C combination polymorphisms and IVF/ICSI outcomes: a retrospective cohort study.

STUDY QUESTION: What are the roles of maternal 5,10-methylenetetrahydrofolate reductase (MTHFR) C677T/A1298C combination polymorphisms on the embryological and clinical outcomes of IVF/ICSI? SUMMARY ANSWER: Our study reveals for the first time that the oocyte maturation potential gradually decreases with a reduction of maternal MTHFR activity determined by combined C677T/A1298C polymorphisms, while embryo quality was worse in women with intermediate MTHFR activity. WHAT IS KNOWN ALREADY: Although many previous studies have explored the association between MTHFR polymorphisms and IVF/ICSI outcomes, the results remain contradictory due to inadequate samples, no adjustment for potential confounders and/or the study of C677T and A1298C separately. Few studies have systematically investigated the exact role of MTHFR activity determined by combined C677T/A1298C polymorphisms on the embryological and clinical outcomes of IVF/ICSI. STUDY DESIGN SIZE DURATION: This is a retrospective cohort study investigating 1160 women who were referred for MTHFR genotyping and IVF/ICSI treatment at Peking University Third Hospital from May 2017 to May 2020. PARTICIPANTS/MATERIALS SETTING METHODS: Women who were referred for MTHFR genotyping and their first IVF/ICSI treatment at our hospital were included and those undergoing preimplantation genetic testing cycles were excluded. The included women were divided into different cohorts according to their C677T, A1298C and combined C677T/A1298C genotypes. The embryological outcomes, including oocytes retrieved, metaphase II oocytes, oocyte maturation rate, normal fertilization rate and transplantable embryo rate, were evaluated by generalized linear regression models. The clinical outcomes, including biochemical pregnancy rate, clinical pregnancy rate and live birth rate, were evaluated by log-binomial regression models. All outcomes were adjusted for potential confounders. MAIN RESULTS AND THE ROLE OF CHANCE: Women with the combined 677TT/1298AA genotype (hereafter abbreviated as TT/AA, as with other combined genotypes), whose enzyme activity was the lowest, had a lower oocyte maturation rate compared with those with the wild-type genotype (P = 0.007). Moreover, the oocyte maturation rate decreased linearly with the decline in MTHFR enzyme activity determined by combined C677T/A1298C genotypes (P-trend = 0.001). The combined CC/AC, CC/CC&CT/AA and CT/AC genotypes with intermediate enzyme activity were associated with a lower transplantable embryo rate (P = 0.013, 0.030 and 0.039, respectively). The differences in clinical outcomes between women with wild-type genotype and combined C677T/A1298C variant genotypes were not significant. LIMITATIONS REASONS FOR CAUTION: Our study population had comparable embryological outcomes but worse clinical outcomes than other women undergoing IVF/ICSI treatment at our hospital. Therefore, the results related to the clinical outcomes should be generalized with caution. In addition, we did not detect the folate concentration of each patient during pregnancy. However, this might not have much influence on our results because almost all of our study participants took sufficient folic acid around pregnancy. WIDER IMPLICATIONS OF THE FINDINGS: We provide a holistic view of the effect of MTHFR C677T and A1298C polymorphisms on the IVF/ICSI outcomes, which can contribute to providing reasonable folic acid supplementation suggestions for women with different MTHFR genotypes, especially for those with a low oocyte maturation rate and/or low embryo quality. STUDY FUNDING/COMPETING INTERESTS: This work was funded by the National Natural Science Foundation of China (31871447, and 82101677), the National Key Research and Development Program (2019YFA0801400) and the Natural Science Foundation of Beijing Municipality (7202226). The authors declare that they have no competing interests. TRIAL REGISTRATION NUMBER: N/A.

Discovery and validation of bladder cancer related excreted nucleosides biomarkers by dilution approach in cell culture supernatant and urine using UHPLC-MS/MS.

The exploration of nucleoside changes in human biofluids has profound potential for cancer diagnosis. Herein, we developed a rapid methodology to quantify 17 nucleosides by UHPLC-MS/MS. Five pairs of isomers were successfully separated within 8 min. The ME was mostly eliminated by sample dilution folds of 1000 for urine and 40 for CCS. The optimized method was firstly applied to screen potential nucleoside biomarkers in CCS by comprising bladder cancer cell lines (5637 and T24) and normal human bladder cell line SV-HUC-1 together with student's t-test and OPLS-DA. Nucleosides with significant differences in the supernatant of urine samples were also uncovered comparing BCa with the non-tumor group, as well as a comparison of BCa recurrence group with the non-recurrence group. By intersecting the differential nucleosides in CCS and urine supernatant, and then further confirmed using validation sets, the combination of m3C and m1A with AUC of 0.775 was considered as a potential biomarker for bladder cancer diagnosis. A panel of m3C, m1A, m1G, and m22G was defined as potential biomarkers for bladder cancer prognosis with an AUC of 0.819. Above all, this method provided a new perspective for diagnosis and recurrence monitoring of bladder cancer. SIGNIFICANCE: The exploration of nucleoside changes in body fluids has profound potential for the diagnosis and elucidation of the pathogenesis of cancer. In this study, we developed a rapid methodology for the simultaneous quantitative determination of 17 nucleosides in the supernatant of cells and urine samples using UHPLC-MS/MS to discover and validate bladder cancer related excreted nucleoside biomarkers. The results of this paper provide a new strategy for diagnosis and postoperative recurrence monitoring of bladder cancer and provide theoretical support for the exploration of its pathogenesis.

Rare Germline Variants Are Associated with Rapid Biochemical Recurrence After Radical Prostate Cancer Treatment: A Pan Prostate Cancer Group Study.

BACKGROUND: Germline variants explain more than a third of prostate cancer (PrCa) risk, but very few associations have been identified between heritable factors and clinical progression. OBJECTIVE: To find rare germline variants that predict time to biochemical recurrence (BCR) after radical treatment in men with PrCa and understand the genetic factors associated with such progression. DESIGN, SETTING, AND PARTICIPANTS: Whole-genome sequencing data from blood DNA were analysed for 850 PrCa patients with radical treatment from the Pan Prostate Cancer Group (PPCG) consortium from the UK, Canada, Germany, Australia, and France. Findings were validated using 383 patients from The Cancer Genome Atlas (TCGA) dataset. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A total of 15,822 rare (MAF <1%) predicted-deleterious coding germline mutations were identified. Optimal multifactor and univariate Cox regression models were built to predict time to BCR after radical treatment, using germline variants grouped by functionally annotated gene sets. Models were tested for robustness using bootstrap resampling. RESULTS AND LIMITATIONS: Optimal Cox regression multifactor models showed that rare predicted-deleterious germline variants in "Hallmark" gene sets were consistently associated with altered time to BCR. Three gene sets had a statistically significant association with risk-elevated outcome when modelling all samples: PI3K/AKT/mTOR, Inflammatory response, and KRAS signalling (up). PI3K/AKT/mTOR and KRAS signalling (up) were also associated among patients with higher-grade cancer, as were Pancreas-beta cells, TNFA signalling via NKFB, and Hypoxia, the latter of which was validated in the independent TCGA dataset. CONCLUSIONS: We demonstrate for the first time that rare deleterious coding germline variants robustly associate with time to BCR after radical treatment, including cohort-independent validation. Our findings suggest that germline testing at diagnosis could aid clinical decisions by stratifying patients for differential clinical management. PATIENT SUMMARY: Prostate cancer patients with particular genetic mutations have a higher chance of relapsing after initial radical treatment, potentially providing opportunities to identify patients who might need additional treatments earlier.

The interaction of p53 and DNA repair gene mutations and their impact on tumor mutation burden and immune response in human malignancies.

P53 suppresses tumorigenesis through multiple cellular functions/mechanisms, including genomic stability surveillance. Recently, it has also be reported for its role in cancer immune response modulation. Deficiency in DNA repair pathways lead to the accumulation of genomic alterations and tumor mutation burden and in consequence resulting in the activation of immune response. We investigated the interaction of p53 and DNA repair gene mutations and their impact on tumor mutation burden and immune response in human malignancies by mining cBioPortal data of a range of human cancers. We found that in the majority of human cancers, p53 mutations are equally distributed between DNA repair gene mutation positive and negative cases and in a number of human cancers, p53 and DNA repair gene mutations have a tendency of co-occurrence. Only in colorectal cancer, there is a tendency of 'mutual exclusivity' of mutations in p53 and DNA repair genes. In most tumors, p53 and DNA repair gene mutations have synergistic/additive effect in increasing tumor mutation burden, but not in colorectal cancer where they are mutually exclusive. The impact of p53 and DNA repair gene mutations and their interaction on tumor microenvironment immune cells are complex and tumor type specific and not always correlated with tumor mutation burden. In colorectal cancers, these two types of mutations resulted in similar immune cell subpopulation changes and in tumors where the mutations have a tendency of co-occurrence, p53 showed dominant roles on immune response, although they can also counter-act each other for their effect on certain immune cell subtypes.

Prostate cancer risk stratification improvement across multiple ancestries with new polygenic hazard score.

BACKGROUND: Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. METHODS: In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. RESULTS: The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively. CONCLUSIONS: We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

The potential of using circulating tumour cells and their gene expression to predict docetaxel response in metastatic prostate cancer.

Background: Docetaxel improves overall survival (OS) in castration-resistant prostate cancer (PCa) (CRPC) and metastatic hormone-sensitive PCa (mHSPC). However, not all patients respond due to inherent and/or acquired resistance. There remains an unmet clinical need for a robust predictive test to stratify patients for treatment. Liquid biopsy of circulating tumour cell (CTCs) is minimally invasive, can provide real-time information of the heterogeneous tumour and therefore may be a potentially ideal docetaxel response prediction biomarker. Objective: In this study we investigate the potential of using CTCs and their gene expression to predict post-docetaxel tumour response, OS and progression free survival (PFS). Methods: Peripheral blood was sampled from 18 mCRPC and 43 mHSPC patients, pre-docetaxel treatment, for CTC investigation. CTCs were isolated using the epitope independent Parsortix® system and gene expression was determined by multiplex RT-qPCR. We evaluated CTC measurements for post-docetaxel outcome prediction using receiver operating characteristics and Kaplan Meier analysis. Results: Detection of CTCs pre-docetaxel was associated with poor patient outcome post-docetaxel treatment. Combining total-CTC number with PSA and ALP predicted lack of partial response (PR) with an AUC of 0.90, p= 0.037 in mCRPC. A significantly shorter median OS was seen in mCRPC patients with positive CTC-score (12.80 vs. 37.33 months, HR= 5.08, p= 0.0005), ≥3 total-CTCs/7.5mL (12.80 vs. 37.33 months, HR= 3.84, p= 0.0053), ≥1 epithelial-CTCs/7.5mL (14.30 vs. 37.33 months, HR= 3.89, p= 0.0041) or epithelial to mesenchymal transitioning (EMTing)-CTCs/7.5mL (11.32 vs. 32.37 months, HR= 6.73, p= 0.0001). Significantly shorter PFS was observed in patients with ≥2 epithelial-CTCs/7.5mL (7.52 vs. 18.83 months, HR= 3.93, p= 0.0058). mHSPC patients with ≥5 CTCs/7.5mL had significantly shorter median OS (24.57 vs undefined months, HR= 4.14, p= 0.0097). In mHSPC patients, expression of KLK2, KLK4, ADAMTS1, ZEB1 and SNAI1 was significantly associated with shorter OS and/or PFS. Importantly, combining CTC measurements with clinical biomarkers increased sensitivity and specificity for prediction of patient outcome. Conclusion: While it is clear that CTC numbers and gene expression were prognostic for PCa post-docetaxel treatment, and CTC subtype analysis may have additional value, their potential predictive value for docetaxel chemotherapy response needs to be further investigated in large patient cohorts.

A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.

PURPOSE: Bladder cancer (BLCA) is one of the most common cancers worldwide. In a large proportion of BLCA patients, disease recurs and/or progress after resection, which remains a major clinical issue in BLCA management. Therefore, it is vital to identify prognostic biomarkers for treatment stratification. We investigated the efficiency of CpG methylation for the potential to be a prognostic biomarker for patients with BLCA. PATIENTS AND METHODS: Overall, 357 BLCA patients from The Cancer Genome Atlas (TCGA) were randomly separated into the training and internal validation cohorts. Least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) were used to select candidate CpGs and build the methylation risk score model, which was validated for its prognostic value in the validation cohort by Kaplan-Meier analysis. Hazard curves were generated to reveal the risk nodes throughout the follow-up. Gene Set Enrichment Analysis (GSEA) was used to reveal the potential biological pathways associated with the methylation model. Quantitative real-time polymerase chain reaction (PCR) and western blotting were performed to verify the expression level of the methylated genes. RESULTS: After incorporating the CpGs obtained by the two algorithms, CpG methylation of eight genes corresponding to TNFAIP8L3, KRTDAP, APC, ZC3H3, COL9A2, SLCO4A1, POU3F3, and ADARB2 were prominent candidate predictors in establishing a methylation risk score for BLCA (MRSB), which was used to divide the patients into high- and low-risk progression groups (p < 0.001). The effectiveness of the MRSB was validated in the internal cohort (p < 0.001). In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. Furthermore, a nomogram comprising MRSB, age, sex, and tumor clinical stage was developed to predict the individual progression risk, and it performed well. Survival analysis implicated the effectiveness of MRSB, which remains significant in all the subgroup analysis based on the clinical features. A functional analysis of MRSB and the corresponding genes revealed potential pathways affecting tumor progression. Validation of quantitative real-time PCR and western blotting revealed that TNFAIP8L3 was upregulated in the BLCA tissues. CONCLUSION: We developed the MRSB, an eight-gene-based methylation signature, which has great potential to be used to predict the post-surgery progression risk of BLCA.

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.

Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.

Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p < 10-180). Comparing the 80th/20th PHS2 percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS2 risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.

The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis.

Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate sample types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and individual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research.

The Identification of Plasma Exosomal miR-423-3p as a Potential Predictive Biomarker for Prostate Cancer Castration-Resistance Development by Plasma Exosomal miRNA Sequencing.

Castration-resistant prostate cancer (CRPC) is the major cause of death from prostate cancer. Biomarkers to improve early detection and prediction of CRPC especially using non-invasive liquid biopsies could improve outcomes. Therefore, we investigated the plasma exosomal miRNAs associated with CRPC and their potential for development into non-invasive early detection biomarkers for resistance to treatment. RNA-sequencing, which generated approximately five million reads per patient, was performed to identify differentially expressed plasma exosomal miRNAs in 24 treatment-naive prostate cancer and 24 CRPC patients. RT-qPCR was used to confirm the differential expressions of six exosomal miRNAs, miR-423-3p, miR-320a, miR-99a-5p, miR-320d, miR-320b, and miR-150-5p (p = 7.3 × 10-8, 0.0020, 0.018, 0.0028, 0.0013, and 0.0058, respectively) firstly in a validation cohort of 108 treatment-naive prostate cancer and 42 CRPC patients. The most significant differentially expressed miRNA, miR-423-3p, was shown to be associated with CRPC with area under the ROC curve (AUC) = 0.784. Combining miR-423-3p with prostate-specific antigen (PSA) enhanced the prediction of CRPC (AUC = 0.908). A separate research center validation with 30 treatment-naive and 30 CRPC patients also confirmed the differential expression of miR-423-3p (p = 0.016). Finally, plasma exosomal miR-423-3p expression in CRPC patients was compared to 36 non-CRPC patients under androgen depletion therapy, which showed significantly higher expression in CRPC than treated non-CRPC patients (p < 0.0001) with AUC = 0.879 to predict CRPC with no difference between treatment-naive and treated non-CRPC patients. Therefore, our findings demonstrate that a number of plasma exosomal miRNAs are associated with CRPC and miR-423-3p may serve as a biomarker for early detection/prediction of castration-resistance.

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.