Validation of an epigenetic field of susceptibility to detect significant prostate cancer from non-tumor biopsies

Prostate cancer: Molecular aspects, consequences, and opportunities of the multifocal nature

Prostate cancer is unique compared to other major cancers due to the presence of multiple primary malignant foci in the majority of patients at the time of diagnosis. Each malignant focus has distinct somatic mutations and gene expression patterns, which represents a challenge for the development of prognostic tests for localized prostate cancer. Additionally, the molecular heterogeneity of advanced prostate cancer has important implications for management, particularly for patients with metastatic and locally recurrent cancer. Studies have shown that prostate cancers with mutations in DNA damage response genes are more sensitive to drugs inhibiting the poly ADP-ribose polymerase (PARP) enzyme. However, testing for such mutations should consider both spatial and temporal heterogeneity. Here, we summarize studies where multiregional genomics and transcriptomics analyses have been performed for primary prostate cancer. We further discuss the vast interfocal heterogeneity and how prognostic biomarkers and a molecular definition of the index tumor should be developed. The concept of focal treatments in prostate cancer has been evolving as a demand from patients and clinicians and is one example where there is a need for defining an index tumor. Here, biomarkers must have proven value for individual malignant foci. The potential discovery and implementation of biomarkers that are agnostic to heterogeneity are also explored as an alternative to multisample testing. Thus, deciding upon whole-organ treatment, such as radical prostatectomy, should depend on information from biomarkers which are informative for the whole organ.

Molecular pathogenesis, mechanism and therapy of Cav1 in prostate cancer

Prostate cancer is the second incidence of malignant tumors in men worldwide. Its incidence and mortality are increasing year by year. Enhanced expression of Cav1 in prostate cancer has been linked to both proliferation and metastasis of cancer cells, influencing disease progression. Dysregulation of the Cav1 gene shows a notable association with prostate cancer. Nevertheless, there is no systematic review to report about molecular signal mechanism of Cav1 and drug treatment in prostate cancer. This article reviews the structure, physiological and pathological functions of Cav1, the pathogenic signaling pathways involved in prostate cancer, and the current drug treatment of prostate cancer. Cav1 mainly affects the occurrence of prostate cancer through AKT/mTOR, H-RAS/PLCε, CD147/MMPs and other pathways, as well as substance metabolism including lipid metabolism and aerobic glycolysis. Baicalein, simvastatin, triptolide and other drugs can effectively inhibit the growth of prostate cancer. As a biomarker of prostate cancer, Cav1 may provide a potential therapeutic target for the treatment of prostate cancer.

High Keratin-7 Expression in Benign Peri-Tumoral Prostatic Glands Is Predictive of Bone Metastasis Onset and Prostate Cancer-Specific Mortality

BACKGROUND

New predictive biomarkers are needed to accurately predict metastasis-free survival (MFS) and cancer-specific survival (CSS) in localized prostate cancer (PC). Keratin-7 (KRT7) overexpression has been associated with poor prognosis in several cancers and is described as a novel prostate progenitor marker in the mouse prostate.

METHODS

KRT7 expression was evaluated in prostatic cell lines and in human tissue by immunohistochemistry (IHC, on advanced PC, n = 91) and immunofluorescence (IF, on localized PC, n = 285). The KRT7 mean fluorescence intensity (MFI) was quantified in different compartments by digital analysis and correlated to clinical endpoints in the localized PC cohort.

RESULTS

KRT7 is expressed in prostatic cell lines and found in the basal and supra-basal compartment from healthy prostatic glands and benign peri-tumoral glands from localized PC. The KRT7 staining is lost in luminal cells from localized tumors and found as an aberrant sporadic staining (2.2%) in advanced PC. In the localized PC cohort, high KRT7 MFI above the 80th percentile in the basal compartment was significantly and independently correlated with MFS and CSS, and with hypertrophic basal cell phenotype.

CONCLUSION

High KRT7 expression in benign glands is an independent biomarker of MFS and CSS, and its expression is lost in tumoral cells. These results require further validation on larger cohorts.

Identification of a novel glycolysis-related gene signature for predicting the survival of patients with colon adenocarcinoma

BACKGROUND

The most frequent histologic subtype of colon cancer is colon adenocarcinoma (COAD). A major problem in the diagnosis and treatment of COAD is that there is lack of new biomarkers to indicate the early stage of COAD. Compared with normally differentiated cells, the glycolytic pathways of tumor cells are more active, thus making them more adaptable to the hypoxic environment of solid tumors, which is known as the Warburg effect. Therefore, establishing a diagnostic and prognostic model based on glycolysis-related genes may provide guidance for the precise treatment of colon cancer.

METHODS

The Cancer Genome Atlas (TCGA) mRNA data were used to identify differentially expressed genes (DEGs). The glycolysis-related DEGs were identified using Gene Set Enrichment Analysis (GSEA) with HALLMARK gene sets. Combined with clinical data, we identified prognostic genes in glycolysis-related DEGs based on Cox regression analysis. Four glycolysis-related genes were identified and a predictive model was developed using univariate and multivariate Cox regression analysis. cBioPortal investigated the chromosomal variations of these genes. Following that, survival analysis and receiver operating characteristic (ROC) curve validation were carried out. The correlations between glycolysis-related gene signatures and molecular features and cancer subtypes were analyzed.

RESULTS

We discovered five genes (SPAG4, P4HA1, STC2, ENO3, and GPC1) that are associated with COAD patients' prognosis. The risk score was more accurate in predicting prognosis when based on this gene signature in COAD patients. Furthermore, multivariate Cox regression analysis demonstrated that the glycolysis-related gene signature's predictive value was independent of clinical variables.

CONCLUSION

We identified a glycolysis-related five-gene signature and developed a risk staging model potentially valuable for the clinical management of COAD patients. Our results suggest that prognostic markers based on glycolysis-related genes may be a reliable predictive tool for the prognosis of COAD patients.

Epigenetic field alterations in non-tumor prostate tissues detect prostate cancer in urine

Prostate cancer (PC) development involves epigenetic DNA methylation changes that occur in the tumor. However, distinct DNA methylation changes have been previously found to encompass a widespread cancer field defect involving normal prostate tissue. In the current study, we analyzed a series of DNA methylation field markers to determine if they predict the presence of PC in urine. Urine samples were collected from patients undergoing prostate biopsy with biopsy-proven PC (90), and without PC (77). From the urine pellet, methylated DNA was quantified across several previously identified CpG island regions near the caveolin 1 (CAV1), even-skipped homeobox 1 (EVX1), fibroblast growth factor 1 (FGF1), natural cytotoxicity triggering receptor 2 (NCR2) and phospholipase A and acyltransferase 3 (PLA2G16) genes using bisulfite pyrosequencing. Univariate and multivariate analyses were performed. Urine cell pellets show significant increases in methylation in four of the markers from patients with PC compared to those without PC including EVX1 12.2 vs. 7.7%, CAV1 15.7 vs. 10.36%, FGF1 12.0 vs. 7.1%, and PLA2G16 12.2 vs. 8.3% [all P<0.01]. Area under the ROC Curve (AUCs) were generated for EXV1 (0.74, Odds ratios (OR) 1.09; 95% confidence intervals (CI) 0.94-1.25, CAV1 (0.72, OR 1.18; 95% CI 1.09-1.28) and PLA2G16 (0.76, OR 1.35; 95% CI 1.199-1.51). In combination, a two-marker assay performs better than prostate specific antigen (PSA), AUC 0.77 vs. PSA AUC of 0.6 (P = 0.01) with the lowest error. In addition, FGF1 distinguished between grade group 1 (GG1) and higher grade cancers (P<0.03). In conclusion, applying methylation of field defect loci to urine samples provides a novel approach to distinguish patients with and without cancer.

How to Better Understand the Influence of Host Genetics on Developing an Effective Immune Response to Thoracic Cancers

Thoracic cancers pose a significant global health burden. Immune checkpoint blockade therapies have improved treatment outcomes, but durable responses remain limited. Understanding how the host immune system interacts with a developing tumor is essential for the rational development of improved treatments for thoracic malignancies. Recent technical advances have improved our understanding of the mutational burden of cancer cells and changes in cancer-specific gene expression, providing a detailed understanding of the complex biology underpinning tumor-host interactions. While there has been much focus on the genetic alterations associated with cancer cells and how they may impact treatment outcomes, how host genetics affects cancer development is also critical and will greatly determine treatment response. Genome-wide association studies (GWAS) have identified genetic variants associated with cancer predisposition. This approach has successfully identified host genetic risk factors associated with common thoracic cancers like lung cancer, but is less effective for rare cancers like malignant mesothelioma. To assess how host genetics impacts rare thoracic cancers, we used the Collaborative Cross (CC); a powerful murine genetic resource designed to maximize genetic diversity and rapidly identify genes associated with any biological trait. We are using the CC in conjunction with our asbestos-induced MexTAg mouse model, to identify host genes associated with mesothelioma development. Once genes that moderate tumor development and progression are known, human homologues can be identified and human datasets interrogated to validate their association with disease outcome. Furthermore, our CC-MexTAg animal model enables in-depth study of the tumor microenvironment, allowing the correlation of immune cell infiltration and gene expression signatures with disease development. This strategy provides a detailed picture of the underlying biological pathways associated with mesothelioma susceptibility and progression; knowledge that is crucial for the rational development of new diagnostic and therapeutic strategies. Here we discuss the influence of host genetics on developing an effective immune response to thoracic cancers. We highlight current knowledge gaps, and with a focus on mesothelioma, describe the development and application of the CC-MexTAg to overcome limitations and illustrate how the knowledge gained from this unique study will inform the rational design of future treatments of mesothelioma.

PUMA and NOXA Expression in Tumor-Associated Benign Prostatic Epithelial Cells Are Predictive of Prostate Cancer Biochemical Recurrence

BACKGROUND

Given that treatment decisions in prostate cancer (PC) are often based on risk, there remains a need to find clinically relevant prognostic biomarkers to stratify PC patients. We evaluated PUMA and NOXA expression in benign and tumor regions of the prostate using immunofluorescence techniques and determined their prognostic significance in PC.

METHODS

PUMA and NOXA expression levels were quantified on six tissue microarrays (TMAs) generated from radical prostatectomy samples (n = 285). TMAs were constructed using two cores of benign tissue and two cores of tumor tissue from each patient. Association between biomarker expression and biochemical recurrence (BCR) at 3 years was established using log-rank (LR) and multivariate Cox regression analyses.

RESULTS

Kaplan-Meier analysis showed a significant association between BCR and extreme levels (low or high) of PUMA expression in benign epithelial cells (LR = 8.831, p = 0.003). Further analysis revealed a significant association between high NOXA expression in benign epithelial cells and BCR (LR = 14.854, p < 0.001). The combination of extreme PUMA and high NOXA expression identified patients with the highest risk of BCR (LR = 16.778, p < 0.001) in Kaplan-Meier and in a multivariate Cox regression analyses (HR: 2.935 (1.645-5.236), p < 0.001).

CONCLUSIONS

The combination of PUMA and NOXA protein expression in benign epithelial cells was predictive of recurrence following radical prostatectomy and was independent of PSA at diagnosis, Gleason score and pathologic stage.