Discovery and Validation of a Panel of Methylation Biomarkers for the Detection of Aggressive Prostate Cancer

Prostate cancer (PCa) ranges from indolent to aggressive tumors with the challenge of identifying high-risk PCa patients that will benefit from multi-modal aggressive treatments, without overtreatment. Radical prostatectomy (RP) remains the gold standard for curative treatment of localized PCa. Approximately 30-50% of men experience recurrent cancer within 10-years post-surgery. Intraductal carcinoma and cribriform (IDC/C) is a prognostic indicator of biochemical recurrence(BCR), metastasis and prostate cancer-specific mortality. Approximately 70% of PCa patients are IDC/C negative yet up-to 20% experience BCR post-RP. Thus, tumor histopathologic characteristics are limited in their ability to predict BCR. Similar to IDC/C, several biomarkers, panels and nomograms have been developed to improve patient risk stratification and prognosis. However, lack of large-scale validation in well characterized cohorts have limited translation to clinic. This thesis focuses on the discovery, development, and validation of novel biomarkers and panels in well-characterized multi-institutional cohorts of patients undergoing RP. Through the use of genome-wide DNA methylation profiling we have identified key hypermethylated genes associated with PCa progression. One such candidate was gastrulation of the brain homeobox 2 (GBX2) significantly associated with GG, pT, and an independent predictor of BCR. GBX2 methylation was able to discriminate patients diagnosed with intermediate disease suspected to have a poorer prognosis (≤GG2 versus ≥ GG3). Additionally, GBX2 methylation has additive potential to IDC/C. Especially among IDC/C negative patients, those with high GBX2 methylation had a shorter time to BCR (P=0.002). The development of panels outperforms the predictive accuracy of any single marker for BCR alone. To address this, I developed and validated a 4-G model consisting of APC, HOXD3, TGFβ2 and CRIP3 (AUC=0.670, Cohort 3), an Integrative gene model combining the 4-G and CAPRA-S (AUC=0.726, Cohort 3) and a clinic-pathological based model integrating IDC/C+CAPRA-S. The investigation of IDC/C features among CAPRA-S low-risk and conversely the investigation of CAPRA-S among IDC/C negative patients improved the prognostication of time to BCR. The integration of epigenetic markers, CAPRA-S and IDC/C can serve as an informative model for improved prediction of tumor behavior. The findings in this thesis with further validation, may lead to improved post-operative risk-stratification tools for PCa patient management.  Ph.D

Multilevel interrogation of H3.3 reveals a primordial role in transcription regulation

Abstract Background Eukaryotic cells can rapidly adjust their transcriptional profile in response to molecular needs. Such dynamic regulation is, in part, achieved through epigenetic modifications and selective incorporation of histone variants into chromatin. H3.3 is the ancestral H3 variant with key roles in regulating chromatin states and transcription. Although H3.3 has been well studied in metazoans, information regarding the assembly of H3.3 onto chromatin and its possible role in transcription regulation remain poorly documented outside of Opisthokonts. Results We used the nuclear dimorphic ciliate protozoan, Tetrahymena thermophila, to investigate the dynamics of H3 variant function in evolutionarily divergent eukaryotes. Functional proteomics and immunofluorescence analyses of H3.1 and H3.3 revealed a highly conserved role for Nrp1 and Asf1 histone chaperones in nuclear influx of histones. Cac2, a putative subunit of H3.1 deposition complex CAF1, is not required for growth, whereas the expression of the putative ortholog of the H3.3-specific chaperone Hir1 is essential in Tetrahymena. Our results indicate that Cac2 and Hir1 have distinct localization patterns during different stages of the Tetrahymena life cycle and suggest that Cac2 might be dispensable for chromatin assembly. ChIP-seq experiments in growing Tetrahymena show H3.3 enrichment over the promoters, gene bodies, and transcription termination sites of highly transcribed genes. H3.3 knockout followed by RNA-seq reveals large-scale transcriptional alterations in functionally important genes. Conclusion Our results provide an evolutionary perspective on H3.3’s conserved role in maintaining the transcriptional landscape of cells and on the emergence of specialized chromatin assembly pathways

Temporal Stability and Prognostic Biomarker Potential of the Prostate Cancer Urine miRNA Transcriptome

BackgroundThe development of noninvasive tests for the early detection of aggressive prostate tumors is a major unmet clinical need. miRNAs are promising noninvasive biomarkers: they play essential roles in tumorigenesis, are stable under diverse analytical conditions, and can be detected in body fluids.MethodsWe measured the longitudinal stability of 673 miRNAs by collecting serial urine samples from 10 patients with localized prostate cancer. We then measured temporally stable miRNAs in an independent training cohort (n = 99) and created a biomarker predictive of Gleason grade using machine-learning techniques. Finally, we validated this biomarker in an independent validation cohort (n = 40).ResultsWe found that each individual has a specific urine miRNA fingerprint. These fingerprints are temporally stable and associated with specific biological functions. We identified seven miRNAs that were stable over time within individual patients and integrated them with machine-learning techniques to create a novel biomarker for prostate cancer that overcomes interindividual variability. Our urine biomarker robustly identified high-risk patients and achieved similar accuracy as tissue-based prognostic markers (area under the receiver operating characteristic = 0.72, 95% confidence interval = 0.69 to 0.76 in the training cohort, and area under the receiver operating characteristic curve = 0.74, 95% confidence interval = 0.55 to 0.92 in the validation cohort).ConclusionsThese data highlight the importance of quantifying intra- and intertumoral heterogeneity in biomarker development. This noninvasive biomarker may usefully supplement invasive or expensive radiologic- and tissue-based assays

Temporal stability and prognostic biomarker potential of the prostate cancer urine transcriptome

BackgroundThe development of noninvasive tests for the early detection of aggressive prostate tumors is a major unmet clinical need. miRNAs are promising noninvasive biomarkers: they play essential roles in tumorigenesis, are stable under diverse analytical conditions, and can be detected in body fluids.MethodsWe measured the longitudinal stability of 673 miRNAs by collecting serial urine samples from 10 patients with localized prostate cancer. We then measured temporally stable miRNAs in an independent training cohort (n = 99) and created a biomarker predictive of Gleason grade using machine-learning techniques. Finally, we validated this biomarker in an independent validation cohort (n = 40).ResultsWe found that each individual has a specific urine miRNA fingerprint. These fingerprints are temporally stable and associated with specific biological functions. We identified seven miRNAs that were stable over time within individual patients and integrated them with machine-learning techniques to create a novel biomarker for prostate cancer that overcomes interindividual variability. Our urine biomarker robustly identified high-risk patients and achieved similar accuracy as tissue-based prognostic markers (area under the receiver operating characteristic = 0.72, 95% confidence interval = 0.69 to 0.76 in the training cohort, and area under the receiver operating characteristic curve = 0.74, 95% confidence interval = 0.55 to 0.92 in the validation cohort).ConclusionsThese data highlight the importance of quantifying intra- and intertumoral heterogeneity in biomarker development. This noninvasive biomarker may usefully supplement invasive or expensive radiologic- and tissue-based assays