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Comparative Evaluation of Expression Patterns and Cellular Functions for the Three ZBTB Methyl-CpG Binding Proteins in Prostate Cancer

ABSTRACT: To date, prostate cancer (PCa) remains the most frequently diagnosed cancer in men. While some genetic mutations have been correlated with prostate tumorigenesis, many PCa presentations do not harbor a clear genetic mutation driver. In many cancers, including PCa, aberrant alterations in DNA methylation patterns has been correlated with cancer promotion and progression. The ZBTB methyl-CpG binding proteins (MBPs), consisting of ZBTB33 (Kaiso), ZBTB4 and ZBTB38, constitute a family of transcription factors that selectively recognize mCpG-containing sites. Upon DNA recognition, these MBPs recruit enzyme complexes that act to remodel chromatin and alter transcriptional outcomes. Given the role of these proteins in eliciting epigenetic-based transcription, we sought to comparably analyze protein levels and cellular distribution patterns for all three ZBTB MBPs within 123 cases of prostate adenocarcinomas exhibiting variable Gleason scores. It was generally observed that relative to benign, nuclear and/or cytoplasmic levels of all three ZBTB MBPs increased in prostate tumors, though the expression and predominant localization trends varied between family members and Gleason score. These tumor observations were generally recapitulated in multiple PCa cell line models, prompting comparative analysis of phenotypic and transcriptome alterations after systematic depletion of each ZBTB MBP. While functional overlap between family members was evident, each ZBTB MBP was also found to modulate distinct disease relevant transcription, including at gene targets known to be hyper-methylated in PCa tumors. Collectively, these findings represent the first comparative analysis of all three ZBTB MBP family members within the same disease context and suggest these proteins may be epigenetic-drivers of aberrant transcription in PCa.

ORGANISM(S): Homo sapiens

PROVIDER: GSE114245 | GEO | 2021/05/09

REPOSITORIES: GEO

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Project description:The highly intra-tumoral heterogeneity and complex cell origination of PCa greatly limited the significance of traditional bulk RNA sequencing in finding better biomarker for disease stratification. In the context of these sequencing strategies, significant gene expression differences in specific cell population might be normalized or even shaded by genes in those less “important” but large in amount cells. Tissue specimens based single-cell RNA sequencing holds great promise for identification of novel stratification biomarkers. However, the preparation of enough viable cells for sequencing, in particular for prostate cancer (PCa), is very challenging when using this technique. In the current study, we, for the first time, employed single-cell RNA sequencing of PCa cells isolated from cancerous prostate tissues of two patients and identified fifteen cell groups including three luminal clusters with different expression profiles. One of these luminal clusters had the highest copy number variation level and marker genes mainly enriched in PCa-related metabolic process, thereafter, was considered as the malignant luminal cells in PCa. Further analysis indicates that the fifth subgroup of these cells highly expressed genes significantly correlated with PCa initiation and early development. In addition, we found this subgroup highly expressed PCa prognosis biomarkers such as AMACR and PCA3. These findings suggest that this cell subgroup might be a critical cell population for PCa diagnosis and stratification. Moreover, by further deciphering the gene expression of this subgroup, we identified another marker gene, HPN, with a 0.930 area under the curve (AUC) score distinguishing normal tissue from PCa lesion using the RNA-seq data from The Cancer Genome Atlas (TCGA). This finding was further validated by immunostaining of HPN in PCa tissue array. The expression of HPN in PCa with Gleason score > 6 is significantly higher than those in Gleason score = 6. Taken together, we provide a valuable resource for interpreting the tumor heterogeneity in PCa, and a novel candidate marker for PCa management.

Dataset Information

Comparative Evaluation of Expression Patterns and Cellular Functions for the Three ZBTB Methyl-CpG Binding Proteins in Prostate Cancer

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