A prospective multicentre phase III validation study of AZGP1 as a biomarker in localized prostate cancer

AZGP1 deficiency promotes angiogenesis in prostate cancer

BACKGROUND

Loss of AZGP1 expression is a biomarker associated with progression to castration resistance, development of metastasis, and poor disease-specific survival in prostate cancer. However, high expression of AZGP1 cells in prostate cancer has been reported to increase proliferation and invasion. The exact role of AZGP1 in prostate cancer progression remains elusive.

METHOD

AZGP1 knockout and overexpressing prostate cancer cells were generated using a lentiviral system. The effects of AZGP1 under- or over-expression in prostate cancer cells were evaluated by in vitro cell proliferation, migration, and invasion assays. Heterozygous AZGP1± mice were obtained from European Mouse Mutant Archive (EMMA), and prostate tissues from homozygous knockout male mice were collected at 2, 6 and 10 months for histological analysis. In vivo xenografts generated from AZGP1 under- or over-expressing prostate cancer cells were used to determine the role of AZGP1 in prostate cancer tumor growth, and subsequent proteomics analysis was conducted to elucidate the mechanisms of AZGP1 action in prostate cancer progression. AZGP1 expression and microvessel density were measured in human prostate cancer samples on a tissue microarray of 215 independent patient samples.

RESULT

Neither the knockout nor overexpression of AZGP1 exhibited significant effects on prostate cancer cell proliferation, clonal growth, migration, or invasion in vitro. The prostates of AZGP1-/- mice initially appeared to have grossly normal morphology; however, we observed fibrosis in the periglandular stroma and higher blood vessel density in the mouse prostate by 6 months. In PC3 and DU145 mouse xenografts, over-expression of AZGP1 did not affect tumor growth. Instead, these tumors displayed decreased microvessel density compared to xenografts derived from PC3 and DU145 control cells, suggesting that AZGP1 functions to inhibit angiogenesis in prostate cancer. Proteomics profiling further indicated that, compared to control xenografts, AZGP1 overexpressing PC3 xenografts are enriched with angiogenesis pathway proteins, including YWHAZ, EPHA2, SERPINE1, and PDCD6, MMP9, GPX1, HSPB1, COL18A1, RNH1, and ANXA1. In vitro functional studies show that AZGP1 inhibits human umbilical vein endothelial cell proliferation, migration, tubular formation and branching. Additionally, tumor microarray analysis shows that AZGP1 expression is negatively correlated with blood vessel density in human prostate cancer tissues.

CONCLUSION

AZGP1 is a negative regulator of angiogenesis, such that loss of AZGP1 promotes angiogenesis in prostate cancer. AZGP1 likely exerts heterotypical effects on cells in the tumor microenvironment, such as stromal and endothelial cells. This study sheds light on the anti-angiogenic characteristics of AZGP1 in the prostate and provides a rationale to target AZGP1 to inhibit prostate cancer progression.

The prognostic value of immune-related genes AZGP1, SLCO5A1, and CTF1 in Uveal melanoma

Objective

Uveal melanoma (UM) is an aggressive malignancy with a poor prognosis and no available effective treatment. Therefore, exploring a potential prognostic marker for UM could provide new possibilities for early detection, recurrence, and treatment.

Methods

In this study, we used “ConsensusClusterPlus” to classify patients with UM into subgroups, screened for significant differences in immune prognostic factors between subgroups, selected three genes using LASSO (Least absolute shrinkage and selection operator) regression to construct a risk model, and performed tumor immune cell infiltration analysis on the risk model. infiltration analysis, and then verified the heterogeneous role of the 3 core genes in other cancers by pan-cancer analysis and validate its expression by RT-qPCR in normal and tumor cells.

Results

We consistently categorized 80 UM patients into two subgroups after the immunogenetic set, where the UM1 subgroup had a better prognosis than the UM2 subgroup, and used 3 immune-related genes AZGP1, SLCO5A1, and CTF1 to derive risk scores as independent prognostic markers and predictors of UM clinicopathological features. We found significant differences in overall survival (OS) between low- and high-risk groups, and prognostic models were negatively correlated with B cell and myeloid dendritic cell and positively correlated with CD8+ T cell AZGP1 and CTF1 were significantly upregulated in UM cells compared with normal UM cells.

Conclusion

Immunogens are significantly associated with the prognosis of UM, and further classification based on genetic characteristics may help to develop immunotherapeutic strategies and provide new approaches to develop customized treatment strategies for patients.

Identification of potential salivary biomarker panels for oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide with the maximum number of incidences and deaths reported from India. One of the major causes of poor survival rate associated with OSCC has been attributed to late presentation due to non-availability of a biomarker. Identification of early diagnostic biomarker will help in reducing the disease morbidity and mortality. We validated 12 salivary proteins using targeted proteomics, identified initially by relative quantification of salivary proteins on LC-MS, in OSCC patients and controls. Salivary AHSG (p = 0.0041**) and KRT6C (p = 0.002**) were upregulated in OSCC cases and AZGP1 (p ≤ 0.0001***), KLK1 (p = 0.006**) and BPIFB2 (p = 0.0061**) were downregulated. Regression modelling resulted in a significant risk prediction model (p < 0.0001***) consisting of AZGP1, AHSG and KRT6C for which ROC curve had AUC, sensitivity and specificity of 82.4%, 78% and 73.5% respectively for all OSCC cases and 87.9%, 87.5% and 73.5% respectively for late stage (T3/T4) OSCC. AZGP1, AHSG, KRT6C and BPIFB2 together resulted in ROC curve (p < 0.0001***) with AUC, sensitivity and specificity of 94%, 100% and 77.6% respectively for N0 cases while KRT6C and AZGP1 for N+ cases with ROC curve (p < 0.0001***) having AUC sensitivity and specificity of 76.8%, 73% and 69.4%. Our data aids in the identification of biomarker panels for the diagnosis of OSCC cases with a differential diagnosis between early and late-stage cases.

AZGP1 Protein Expression in Hormone-Naïve Advanced Prostate Cancer Treated with Primary Androgen Deprivation Therapy

Biomarkers for predicting the risk of castration-resistant prostate cancer (CRPC) in men treated with primary androgen deprivation therapy (ADT) are lacking. We investigated whether Zinc-alpha 2 glycoprotein (AZGP1) expression in the diagnostic biopsies of men with hormone-naïve prostate cancer (PCa) undergoing primary ADT was predictive of the development of CRPC and PCa-specific mortality. The study included 191 patients who commenced ADT from 2000 to 2011. The AZGP1 expression was evaluated using immunohistochemistry and scored as high or low expression. The risks of CRPC and PCa-specific mortality were analyzed using stratified cumulative incidences and a cause-specific COX regression analysis for competing risk assessment. The median follow-up time was 9.8 (IQR: 6.1-12.7) years. In total, 94 and 97 patients presented with low and high AZGP1 expression, respectively. A low AZGP1 expression was found to be associated with a shorter time to CRPC when compared to patients with a high AZGP1 expression (HR: 1.5; 95% CI: 1.0-2.1; p = 0.03). However, the multivariable analysis demonstrated no added benefit by adding the AZGP1 expression to prediction models for CRPC. No differences for PCa-specific mortality between the AZGP1 groups were observed. In conclusion, a low AZGP1 expression was associated with a shorter time to CRPC for PCa patients treated with first-line ADT but did not add any predictive information besides well-established clinicopathological variables.

Predictive value of AZGP1 following radical prostatectomy for prostate cancer: a cohort study and meta-analysis

AIMS

Zinc-alpha 2-glycoprotein (AZGP1) is a promising tissue biomarker to predict outcomes in men undergoing treatment for localised prostate cancer (PCa). We aimed to examine the association between AZGP1 expression and the endpoints: risk of biochemical failure (BF), initiating castration-based treatment, developing castration-resistant PCa (CRPC) and PCa-specific mortality following radical prostatectomy (RP).

METHODS

The study included a prospective cohort of 302 patients who underwent RP for PCa from 2002 to 2005. AZGP1 expression was analysed using immunohistochemistry on tissue microarray RP specimens and was scored semiquantitively as low or high expression. Risk of all endpoints was analysed using stratified cumulative incidences and cause-specific Cox regression, and validated with receiver operating curves, calibration and discrimination in competing-risk analyses. A meta-analysis was performed including previous studies investigating AZGP1 expression and risk of BF following RP.

RESULTS

Median time of follow-up was 14.0 years. The cumulative incidence of all endpoints was significantly higher in patients with low AZGP1 expression compared with patients with high AZGP1 expression (p<0.001). In a multivariate analysis, low AZGP1 expression increases the risk of BF (HR 2.7; 95% CI 1.9 to 3.8; p<0.0001), castration-based treatment (HR 2.2; 95% CI 1.2 to 4.2; p=0.01) and CRPC (HR 2.3; 95% CI 1.1 to 5.0; p=0.03). Validation showed a low risk of prediction error and a high model performance for all endpoints. In a meta-analysis, low AZGP1 was associated with BF (HR 1.7; 95% CI 1.2 to 2.5).

CONCLUSIONS

Low AZGP1 expression is associated with the risk of aggressive time-dependent outcomes in men undergoing RP for localised PCa.

Advanced impedimetric biosensor configuration and assay protocol for glycoprofiling of a prostate oncomarker using Au nanoshells with a magnetic core

In this paper several advances were implemented for glycoprofiling of prostate specific antigen (PSA), what can be applied for better prostate cancer (PCa) diagnostics in the future: 1) application of Au nanoshells with a magnetic core (MP@silica@Au); 2) use of surface plasmons of Au nanoshells with a magnetic core for spontaneous immobilization of zwitterionic molecules via diazonium salt grafting; 3) a double anti-fouling strategy with integration of zwitterionic molecules on Au surface and on MP@silica@Au particles was implemented to resist non-specific protein binding; 4) application of anti-PSA antibody modified Au nanoshells with a magnetic core for enrichment of PSA from a complex matrix of a human serum; 5) direct incubation of anti-PSA modified MP@silica@Au with affinity bound PSA to the lectin modified electrode surface. The electrochemical impedance spectroscopy (EIS) signal was enhanced 43 times integrating Au nanoshells with a magnetic core compared to the biosensor without them. This proof-of-concept study shows that the biosensor could detect PSA down to 1.2 fM and at the same time to glycoprofile such low PSA concentration using a lectin patterned biosensor device. The biosensor offers a recovery index of 108%, when serum sample was spiked with a physiological concentration of PSA (3.5 ng mL-1).

Research status and progress of the RNA or protein biomarkers for prostate cancer

Prostate cancer is a kind of male malignancy. Recently, a large number of studies have reported many potential biomarkers for the diagnosis and prognosis of prostate cancer. In this literature review, we have collected a number of potential biomarkers for prostate cancer reported in the last 5 years. Among them, some are undergoing Phase III clinical trials, and others have been approved by the US Food and Drug Administration. However, most are still in the period of basic research. The review will contribute to future research to find the biomarkers to guide clinicians to make personalized treatment decisions for each prostate cancer patient.

ZAG-a novel biomarker for cardiovascular risk in ESRD patients?

End-stage renal disease (ESRD) is associated with an exceedingly high risk of cardiovascular disease. Traditional risk factors function differently in ESRD, which has prompted a search for novel mechanisms and biomarkers. In an observational study, Bouchara et al. identified zinc-alpha2-glycoprotein (ZAG) as a prognostic marker for cardiovascular events and mortality in patients on dialysis. Although the study raises important questions, the results should be interpreted cautiously and need to be confirmed in independent studies.

An analysis of a multiple biomarker panel to better predict prostate cancer metastasis after radical prostatectomy

A plethora of individual candidate biomarkers for predicting biochemical relapse in localized prostate cancer (PCa) have been proposed. Combined biomarkers may improve prognostication, and ensuring validation against more clinically relevant endpoints are required. The Australian PCa Research Centre NSW has contributed to numerous studies of molecular biomarkers associated with biochemical relapse. In the current study, these biomarkers were re-analyzed for biochemical relapse, metastatic relapse and PCa death with extended follow-up. Biomarkers of significance were then used to develop a combined prognostic model for clinical outcomes and validated in a large independent cohort. The discovery cohort (n = 324) was based on 12 biomarkers with a median follow-up of 16 years. Seven biomarkers were significantly associated with biochemical relapse. Three biomarkers were associated with metastases: AZGP1, Ki67 and PML. Only AZGP1 was associated with PCa death. In their individual and combinational forms, AZGP1 and Ki67 as a dual BM signature was the most robust predictor of metastatic relapse (AUC 0.762). The AZPG1 and Ki67 signature was validated in an independent cohort of 347 PCa patients. The dual BM signature of AZGP1 and Ki67 predicted metastasis in the univariable (HR 7.2, 95% CI, 1.6-32; p = 0.01) and multivariable analysis (HR 5.4, 95% CI, 1.2-25; p = 0.03). The dual biomarker signature marginally improved risk prediction compared to AZGP1 alone (AUC 0.758 versus 0.738, p < 0.001). Our findings indicate that biochemical relapse is not an adequate surrogate for metastasis or PCa death. The dual biomarker signature of AZGP1 and Ki67 offers a small benefit in predicting metastasis over AZGP1 alone.