Clonal evaluation of prostate cancer molecular heterogeneity in biopsy samples by dual immunohistochemistry and dual RNA in situ hybridization

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Experimental challenges to modeling prostate cancer heterogeneity

Tumor heterogeneity plays a key role in prostate cancer prognosis, therapy selection, relapse, and acquisition of treatment resistance. Prostate cancer presents a heterogeneous diversity at inter- and intra-tumor and inter-patient levels which are influenced by multiple intrinsic and/or extrinsic factors. Recent studies have started to characterize the complexity of prostate tumors and these different tiers of heterogeneity. In this review, we discuss the most common factors that contribute to tumoral diversity. Moreover, we focus on the description of the in vitro and in vivo approaches, as well as high-throughput technologies, that help to model intra-tumoral diversity. Further understanding tumor heterogeneities and the challenges they present will guide enhanced patient risk stratification, aid the design of more precise therapies, and ultimately help beat this chameleon-like disease.

Cell membrane and nuclear expression of programmed death ligand-1 in prostate needle biopsy tissue in prostate cancer patients undergoing primary radiation therapy

BACKGROUND

Programmed death ligand-1 (PD-L1) expression in cancer is often associated with cancer aggressiveness and responsiveness to treatment with PD-1 pathway inhibitors. We conducted a systematic study on the expression of membranous PD-L1 (mPD-L1) and nuclear PD-1-L1 (nPD-L1) in prostate needle biopsy specimens of prostate cancer patients who underwent primary radiotherapy and analyzed the association between PD-L1 expression and clinicopathological characteristics and prognosis of patients.

METHOD

A total of 971 cancer-containing prostate needle biopsy cores from 172 patients were immunohistochemically stained with anti-PD-L1 antibody. The association of PD-L1 expression with Gleason score and tumor volume percentage was evaluated for each biopsy core. Total of 171 patients were divided according to mPD-L1 or nPD-L1 expression, and clinicopathological characteristics were compared between the positive and negative groups. The prognostic significance of mPD-L1, nPD-L1 and common prognostic factors were analyzed in terms of biochemical recurrence.

RESULT

Total of 15% and 46% of biopsy cores were stained positive for mPD-L1 and nPD-L1, respectively. There was a positive correlation between Gleason score and mPD-L1 and a negative correlation between Gleason score and nPD-L1. Between mPD-L1 and nPD-L1, there was no significant correlation. There was intraindividual heterogeneity in PD-L1 expression among different Gleason scores. For mPD-L1, only pretreatment PSA was significantly higher in the positive group than in the negative, but not Gleason score and T stage. For nPD-L1, Gleason score and T stage were significantly higher in the positive group than in the negative. Both mPD-L1 and nPD-L1 expression were not predictive of BCR-free survival in univariate and multivariate analyses.

CONCLUSIONS

Our results suggest that PD-1 pathway inhibitor may be a potential therapeutic option in high risk prostate cancer patients as early as neoadjuvant setting. The novel discovery of PD-L1 expression in the nucleus of PC should be subjected to further research.

A novel DNA methylation 10-CpG prognostic signature of disease-free survival reveal that MYBL2 is associated with high risk in prostate cancer

BACKGROUND

Prostate cancer (PC) is the most common non-cutaneous malignancy among men in the western world. However, heterogeneity remains a pressing clinical problem.

RESEARCH DESIGN AND METHODS

The least absolute shrinkage and selection operator (LASSO) was used to screen the prognostic signature. Weighted correlation network analysis (WGCNA) was used to identify the target genes associated with high-risk characteristics. Gene set enrichment analysis was used to suggest the molecular mechanism of MYBL2 in PC. In addition, in vitro experiments were carried out to validate the role of MYBL2 in PC.

RESULTS

Ten DNA methylation sites were selected as the prognostic signature. A high expression of MYBL2 was associated with a poor prognosis in PC patients. The effect of MYBL2 in PC was related to KRAS, AKT, IL21, and ATM. MYBL2 facilitates the proliferation, migration, invasion, and metastasis of PC cells.

CONCLUSIONS

We developed a DNA methylation 10-CpG prognostic signature to predict the prognosis of PC patients. And the high expression of MYBL2 in PC may be related to poor prognosis.

ETV4 promotes late development of prostatic intraepithelial neoplasia and cell proliferation through direct and p53-mediated downregulation of p21

BACKGROUND

ETV4 is one of the ETS proteins overexpressed in prostate cancer (PC) as a result of recurrent chromosomal translocations. In human prostate cell lines, ETV4 promotes migration, invasion, and proliferation; however, its role in PC has been unclear. In this study, we have explored the effects of ETV4 expression in the prostate in a novel transgenic mouse model.

METHODS

We have created a mouse model with prostate-specific expression of ETV4 (ETV4 mice). By histochemical and molecular analysis, we have investigated in these engineered mice the expression of p21, p27, and p53. The implications of our in vivo findings have been further investigated in human cells lines by chromatin-immunoprecipitation (ChIP) and luciferase assays.

RESULTS

ETV4 mice, from two independent transgenic lines, have increased cell proliferation in their prostate and two-thirds of them, by the age of 10 months, developed mouse prostatic intraepithelial neoplasia (mPIN). In these mice, cdkn1a and its p21 protein product were reduced compared to controls; p27 protein was also reduced. By ChIP assay in human prostate cell lines, we show that ETV4 binds to a specific site (-704/-696 bp upstream of the transcription start) in the CDKN1A promoter that was proven, by luciferase assay, to be functionally competent. ETV4 further controls CDKN1A expression by downregulating p53 protein: this reduction of p53 was confirmed in vivo in ETV4 mice.

CONCLUSIONS

ETV4 overexpression results in the development of mPIN but not in progression to cancer. ETV4 increases prostate cell proliferation through multiple mechanisms, including downregulation of CDKN1A and its p21 protein product: this in turn is mediated through direct binding of ETV4 to the CDKN1A promoter and through the ETV4-mediated decrease of p53. This multi-faceted role of ETV4 in prostate cancer makes it a potential target for novel therapeutic approaches that could be explored in this ETV4 transgenic model.