Phase II study of cytarabine in men with docetaxel-refractory, castration-resistant prostate cancer with evaluation of TMPRSS2-ERG and SPINK1 as serum biomarkers

Identification of Molecular Markers Associated with Prostate Cancer Subtypes: An Integrative Bioinformatics Approach

Prostate cancer (PCa) is characterised by androgen dependency. Unfortunately, under anti-androgen treatment pressure, castration-resistant prostate cancer (CRPC) emerges, characterised by heterogeneous cell populations that, over time, lead to the development of different androgen-dependent or -independent phenotypes. Despite important advances in therapeutic strategies, CRPC remains incurable. Context-specific essential genes represent valuable candidates for targeted anti-cancer therapies. Through the investigation of gene and protein annotations and the integration of published transcriptomic data, we identified two consensus lists to stratify PCa patients' risk and discriminate CRPC phenotypes based on androgen receptor activity. ROC and Kaplan-Meier survival analyses were used for gene set validation in independent datasets. We further evaluated these genes for their association with cancer dependency. The deregulated expression of the PCa-related genes was associated with overall and disease-specific survival, metastasis and/or high recurrence risk, while the CRPC-related genes clearly discriminated between adeno and neuroendocrine phenotypes. Some of the genes showed context-specific essentiality. We further identified candidate drugs through a computational repositioning approach for targeting these genes and treating lethal variants of PCa. This work provides a proof-of-concept for the use of an integrative approach to identify candidate biomarkers involved in PCa progression and CRPC pathogenesis within the goal of precision medicine.

In Silico Prediction of Drug-Induced Liver Injury Based on Adverse Drug Reaction Reports

Drug-induced liver injury (DILI) is a major cause of drug attrition. Currently existing Quantitative Structure-Activity Relationship models have limited predictive capabilities for DILI. Furthermore, their practical applications were limited by lack of new hepatotoxicity data. In this study, we first collected and curated a novel set of 122 DILI-positive and 932 DILI-negative drugs from online adverse drug reports using proportional reporting ratios as the signal detection method. Second, three strategies (under-sampling the majority class, synthetic minority over-sampling technique, and adjusting decision threshold approach) were employed to develop predictive classification models to cope with the unbalanced dataset. Random forest (RF) models using CDK, MACCS, and Mold2 descriptors based on the under-sampling and over-sampling strategies afforded correct classification ratio (CCR) of ∼0.77 and 0.78, respectively. Recursive RF models based on the last strategy tremendously reduced modeling descriptors (at most 95.4% for Mold2) while apparently improved the predictability with a consensus CCR of 0.84 (sensitivity of 0.88 and specificity of 0.79). Structural analysis showed that pyrimidine derivatives, purine derivatives, and halogenated hydrocarbon were critical for drugs' hepatotoxicity. The reporting frequency of many drugs was gender-dependent (eg, antiviral and anti-cancer drugs for males and antibacterial drugs for females) as well as age-dependent (eg, antiviral and anti-cancer drugs for the middle age group of 20-29, 30-39, and 40-49). Approximately 84% of total cases were reported during the first 6 months of administration. The curated hepatotoxicity dataset along with the predictive classification models presented here should provide insight into future studies of DILI.

Androgen Receptor-CaMKK2 Axis in Prostate Cancer and Bone Microenvironment

The skeletal system is of paramount importance in advanced stage prostate cancer (PCa) as it is the preferred site of metastasis. Complex mechanisms are employed sequentially by PCa cells to home to and colonize the bone. Bone-resident PCa cells then recruit osteoblasts (OBs), osteoclasts (OCs), and macrophages within the niche into entities that promote cancer cell growth and survival. Since PCa is heavily reliant on androgens for growth and survival, androgen-deprivation therapy (ADT) is the standard of care for advanced disease. Although it significantly improves survival rates, ADT detrimentally affects bone health and significantly increases the risk of fractures. Moreover, whereas the majority patients with advanced PCa respond favorably to androgen deprivation, most experience a relapse of the disease to a hormone-refractory form within 1-2 years of ADT. The tumor adapts to surviving under low testosterone conditions by selecting for mutations in the androgen receptor (AR) that constitutively activate it. Thus, AR signaling remains active in PCa cells and aids in its survival under low levels of circulating androgens and additionally allows the cancer cells to manipulate the bone microenvironment to fuel its growth. Hence, AR and its downstream effectors are attractive targets for therapeutic interventions against PCa. Ca²⁺/calmodulin-dependent protein kinase kinase 2 (CaMKK2), was recently identified as a key downstream target of AR in coordinating PCa cell growth, survival, and migration. Additionally, this multifunctional serine/threonine protein kinase is a critical mediator of bone remodeling and macrophage function, thus emerging as an attractive therapeutic target downstream of AR in controlling metastatic PCa and preventing ADT-induced bone loss. Here, we discuss the role played by AR-CaMKK2 signaling axis in PCa survival, metabolism, cell growth, and migration as well as the cell-intrinsic roles of CaMKK2 in OBs, OCs, and macrophages within the bone microenvironment.

Global gene expression profiling reveals SPINK1 as a potential hepatocellular carcinoma marker

BACKGROUND

Liver cirrhosis is the most important risk factor for hepatocellular carcinoma (HCC) but the role of liver disease aetiology in cancer development remains under-explored. We investigated global gene expression profiles from HCC arising in different liver diseases to test whether HCC development is driven by expression of common or different genes, which could provide new diagnostic markers or therapeutic targets.

METHODOLOGY AND PRINCIPAL FINDINGS

Global gene expression profiling was performed for 4 normal (control) livers as well as 8 background liver and 7 HCC from 3 patients with hereditary haemochromatosis (HH) undergoing surgery. In order to investigate different disease phenotypes causing HCC, the data were compared with public microarray repositories for gene expression in normal liver, hepatitis C virus (HCV) cirrhosis, HCV-related HCC (HCV-HCC), hepatitis B virus (HBV) cirrhosis and HBV-related HCC (HBV-HCC). Principal component analysis and differential gene expression analysis were carried out using R Bioconductor. Liver disease-specific and shared gene lists were created and genes identified as highly expressed in hereditary haemochromatosis HCC (HH-HCC) were validated using quantitative RT-PCR. Selected genes were investigated further using immunohistochemistry in 86 HCC arising in liver disorders with varied aetiology. Using a 2-fold cut-off, 9 genes were highly expressed in all HCC, 11 in HH-HCC, 270 in HBV-HCC and 9 in HCV-HCC. Six genes identified by microarray as highly expressed in HH-HCC were confirmed by RT qPCR. Serine peptidase inhibitor, Kazal type 1 (SPINK1) mRNA was very highly expressed in HH-HCC (median fold change 2291, p = 0.0072) and was detected by immunohistochemistry in 91% of HH-HCC, 0% of HH-related cirrhotic or dysplastic nodules and 79% of mixed-aetiology HCC.

CONCLUSION

HCC, arising from diverse backgrounds, uniformly over-express a small set of genes. SPINK1, a secretory trypsin inhibitor, demonstrated potential as a diagnostic HCC marker and should be evaluated in future studies.

The TMPRSS2:ERG rearrangement, ERG expression, and prostate cancer outcomes: a cohort study and meta-analysis

BACKGROUND

Whether the genomic rearrangement transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (ERG) has prognostic value in prostate cancer is unclear.

METHODS

Among men with prostate cancer in the prospective Physicians' Health and Health Professionals Follow-Up Studies, we identified rearrangement status by immunohistochemical assessment of ERG protein expression. We used Cox models to examine associations of ERG overexpression with biochemical recurrence and lethal disease (distant metastases or cancer-specific mortality). In a meta-analysis including 47 additional studies, we used random-effects models to estimate associations between rearrangement status and outcomes.

RESULTS

The cohort consisted of 1,180 men treated with radical prostatectomy between 1983 and 2005. During a median follow-up of 12.6 years, 266 men experienced recurrence and 85 men developed lethal disease. We found no significant association between ERG overexpression and biochemical recurrence [hazard ratio (HR), 0.99; 95% confidence interval (CI), 0.78-1.26] or lethal disease (HR, 0.93; 95% CI, 0.61-1.43). The meta-analysis of prostatectomy series included 5,074 men followed for biochemical recurrence (1,623 events), and 2,049 men followed for lethal disease (131 events). TMPRSS2:ERG was associated with stage at diagnosis [risk ratio (RR)(≥T3 vs. T2), 1.23; 95% CI, 1.16-1.30) but not with biochemical recurrence (RR, 1.00; 95% CI, 0.86-1.17) or lethal disease (RR, 0.99; 95% CI, 0.47-2.09).

CONCLUSIONS

These results suggest that TMPRSS2:ERG, or ERG overexpression, is associated with tumor stage but does not strongly predict recurrence or mortality among men treated with radical prostatectomy.

IMPACT

This is the largest prospective cohort study to examine associations of ERG overexpression and lethal prostate cancer among men treated with radical prostatectomy.