Prostate Specific Antigen-Growth Curve Model to Predict High-Risk Prostate Cancer

Preliminary effects of risk-adapted PSA screening for prostate cancer after integrating PRS-specific and age-specific variation

Background

Although the risk of prostate cancer (PCa) varies across different ages and genetic risks, it's unclear about the effects of genetic-specific and age-specific prostate-specific antigen (PSA) screening for PCa.

Methods

Weighed and unweighted polygenic risk scores (PRS) were constructed to classify the participants from the PLCO trial into low- or high-PRS groups. The age-specific and PRS-specific cut-off values of PSA for PCa screening were determined with time-dependent receiver-operating-characteristic curves and area-under-curves (tdAUCs). Improved screening strategies integrating PRS-specific and age-specific cut-off values of PSA were compared to traditional PSA screening on accuracy, detection rates of high-grade PCa (Gleason score ≥7), and false positive rate.

Results

Weighted PRS with 80 SNPs significantly associated with PCa was determined as the optimal PRS, with an AUC of 0.631. After stratifying by PRS, the tdAUCs of PSA with a 10-year risk of PCa were 0.818 and 0.816 for low- and high-PRS groups, whereas the cut-off values were 1.42 and 1.62 ng/mL, respectively. After further stratifying by age, the age-specific cut-off values of PSA were relatively lower for low PRS (1.42, 1.65, 1.60, and 2.24 ng/mL for aged <60, 60-64, 65-69, and ≥70 years) than high PRS (1.48, 1.47, 1.89, and 2.72 ng/mL). Further analyses showed an obvious interaction of positive PSA and high PRS on PCa incidence and mortality. Very small difference in PCa risk were observed among subgroups with PSA (-) across different age and PRS, and PCa incidence and mortality with PSA (+) significantly increased as age and PRS, with highest risk for high-PRS/PSA (+) in participants aged ≥70 years [HRs (95%CI): 16.00 (12.62-20.29) and 19.48 (9.26-40.96)]. The recommended screening strategy reduced 12.8% of missed PCa, ensured high specificity, but not caused excessive false positives than traditional PSA screening.

Conclusion

Risk-adapted screening integrating PRS-specific and age-specific cut-off values of PSA would be more effective than traditional PSA screening.

Risk-stratified multi-round PSA screening for prostate cancer integrating the screening reference level and subgroup-specific progression indicators

BACKGROUND

Although prostate-specific antigen (PSA) is widely used in prostate cancer (PCa) screening, nearly half of PCa cases are missed and less than one-third of cases are non-lethal. Adopting diagnostic criteria in population-based screening and ignoring PSA progression are presumed leading causes.

METHODS

A total of 31,942 participants with multi-round PSA tests from the PLCO trial were included. Time-dependent receiver-operating-characteristic curves and area under curves (tdAUCs) were performed to determine the screening reference level and the optimal subgroup-specific progression indicator. Effects of risk-stratified multi-round PSA screening were evaluated with multivariable Cox regression and measured with hazard ratio [HR (95%CIs)].

RESULTS

After a median follow-up of 11.6 years, a total of 3484 PCa cases and 216 PCa deaths were documented. The tdAUC of 10-year incidence PCa with PSA was 0.816, and the cut-off value was 1.61 ng/ml. Compared to subgroup with stable negative PSA in both first-round (FR) and last-round (LR) tests [FR(-)/LR(-)], HRs (95%CI) of PCa incidence were 1.66 (1.20-2.29), 8.29 (7.25-9.48), and 14.52 (12.95-16.28) for subgroups with loss of positive PSA[FR(+)/LR(-)], gain of positive PSA[FR(-)/LR(+)], and stable positive PSA[FR(+)/LR(+)]; while HRs(95%CI) of PCa mortality were 1.47 (0.52-4.15), 5.71 (3.68-8.86), and 5.01 (3.41-7.37). After excluding regressive PSA [(namely FR(+)/LR(-)], absolute velocity was the shared optimal progression indicator for subgroups with FR(-)/LR(-), FR(-)/LR(+), and FR(+)/LR(+), with tdAUCs of 0.665, 0.681 and 0.741, and cut-off values of 0.07, 0.21, and 0.33 ng/ml/year. After reclassifying participants into groups with positive and negative progression based on subgroup-specific progression indicators, incidence HR (95%CI) were 2.41 (1.87-3.10), 2.91 (2.43-3.48), and 3.16 (2.88-3.46) for positive progression compared to negative progression within subgroups of FR(-)/LR(-), FR(-)/LR(+), and FR(+)/LR(+), while mortality HR (95%CI) were 2.22 (0.91-5.38), 2.37 (1.28-4.38), and 2.98 (1.94-4.59). To improve screening performances by excluding regressive PSA and low-risk positive progression in FR(-)/LR(-), optimized screening strategy not only significantly reduce 32.4% of missed PCa (54.0% [1881/3484] vs. 21.6% [754/3484], P < 0.001), but also detected additional 8.0% of high-grade PCa (Gleason score 7-10: 36.0% [665/1849] vs. 28.0% [206/736], P < 0.001) than traditional screening strategy.

CONCLUSIONS

Risk-stratified multi-round PSA screening strategy integrating the screening reference level and the optimal subgroup-specific progression indicator of PSA could be recommended as a fundamental strategy to reduce missed diagnosis and improve the detection of high-grade PCa cases.

Potent carotenoid astaxanthin expands the anti-cancer activity of cisplatin in human prostate cancer cells

Prostate cancer (PCa) is the second most common type of cancer and the sixth cause of death in men worldwide. Radiotherapy and immunotherapy are commonly used in treating PCa, but understanding the crosstalk mechanisms of carcinogenesis and new therapeutic approaches is essential for supporting poor diagnosis and existing therapies. Astaxanthin (ASX) is a member of the xanthophyll family that is an oxygenated derivative of carotenoids whose synthesis is in plant extracts from lycopene. ASX has protective effects on various diseases, such as Parkinson's disease and cancer by showing potent antioxidant and anti-inflammatory properties. However, there is an ongoing need for a detailed investigation of the molecular mechanism of action to expand its therapeutic use. In the present study, we showed the new regulatory role of ASX in PCa cells by affecting the unfolded protein response (UPR) signaling, autophagic activity, epithelial-mesenchymal transition (EMT) and regulating the expression level of angiogenesis-related protein vascular endothelial growth factor A (VEGF-A), proto-oncogene c-Myc and prostate-specific antigen (PSA). Additionally, we determined that it exhibited synergistic action with cisplatin and significantly enhanced apoptotic cell death in PCa cells. Present findings suggest that ASX may be a potent adjuvant therapeutic option in PCa treatment when used alone or combined with chemotherapeutics. Schematic illustration of the biochemical activity of astaxanthin and its combination with cisplatin.

Predicting High-Risk Prostate Cancer Using Machine Learning Methods

Prostate cancer can be low- or high-risk to the patient’s health. Current screening on the basis of prostate-specific antigen (PSA) levels has a tendency towards both false positives and false negatives, both of which have negative consequences. We obtained a dataset of 35,875 patients from the screening arm of the National Cancer Institute’s Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. We segmented the data into instances without prostate cancer, instances with low-risk prostate cancer, and instances with high-risk prostate cancer. We developed a pipeline to deal with imbalanced data and proposed algorithms to perform preprocessing on such datasets. We evaluated the accuracy of various machine learning algorithms in predicting high-risk prostate cancer. An accuracy of 91.5% can be achieved by the proposed pipeline, using standard scaling, SVMSMOTE sampling method, and AdaBoost for machine learning. We then evaluated the contribution of rate of change of PSA, age, BMI, and filtration by race to this model’s accuracy. We identified that including the rate of change of PSA and age in our model increased the area under the curve (AUC) of the model by 6.8%, whereas BMI and race had a minimal effect.

Diet-related inflammation and risk of prostate cancer in the California Men's Health Study

PURPOSE

The purpose of the study was to examine the relationship between proinflammatory diet and prostate cancer risk.

METHODS

Energy-adjusted Dietary Inflammatory Index (E-DII) scores were computed among 40,161 participants in the California Men's Health Study. Over 9.7 ± 3.8 years of follow-up, 2707 incident prostate cancer cases were diagnosed and categorized as low-, intermediate-, or high-risk, based on disease grade and stage. Accelerated failure-time models assessed time to diagnosis of prostate cancer. Cox proportional hazard models estimated hazard ratios (HR) and 95% confidence intervals (95% CI). Nonlinear effects of E-DII were modeled as third-order polynomials.

RESULTS

Time to prostate cancer diagnosis did not differ by E-DII quartile. The HR for high-risk prostate cancer increased in the third E-DII quartile (HRQ3 vs. Q1 = 1.36; 95% CI: 1.04-1.76), but not in the fourth (HRQ4 vs. Q1 = 0.99; 95% CI: 0.74-1.32, Ptrend = .74), suggesting a nonlinear dose-response. HR curves for prostate cancer increased exponentially above an E-DII threshold of ≈+3.0. HR curves for high-risk prostate cancer had a much steeper incline above an E-DII threshold of ≈+2.5. Curves were higher among Blacks and Whites relative to other races and among overweight or obese men. No relationship was observed between E-DII scores and intermediate- or low-risk disease.

CONCLUSIONS

Relationships between proinflammatory diet and prostate cancer risk may be nonlinear, with an increased risk above an E-DII threshold of ≈+2.5.

Circulating Levels of Omentin, Leptin, VEGF, and HGF and Their Clinical Relevance with PSA Marker in Prostate Cancer

Background

Prostate cancer (PCa) is the first in terms of occurrence in Europe and second in Poland. The PCa risk factors include: genetic load, obesity, diet rich in fat, hypertriglyceridemia, and exposure to androgens. The prostate-specific antigen (PSA) level may be elevated in prostate cancer or other prostate disorders. Fat tissue secretes adipocytokines, which increase the risk of cancer development and metastasis.

Objectives

The aims of the study were to investigate the relationship between circulating levels of PSA, adipocytokines: omentin, leptin, hepatocyte growth factor (HGF), and vascular endothelial growth factor (VEGF) in serum obtained from patients with benign prostate hyperplasia (BPH) and prostate cancer (PCa).

Methods

Forty patients diagnosed with BPH and forty diagnosed with PCa were assessed for the purpose of the study. The concentrations of omentin, leptin, HGF, and VEGF were determined using enzyme-linked immunosorbent assays (EIA).

Results

PSA level was significantly higher in the PCa group than in BPH (18.2 versus 9 ng/mL, p < 0.01), while volume of prostate gland was significantly higher in the BPH group than in PCa (39.1 versus 31.1 cm³, p = 0.02). HGF, VEGF, omentin, and leptin concentrations were significantly higher in PCa group than in BPH (359.5 versus 294.9 pg/mL, p = 0.04; 179.3 versus 127.3 pg/mL, p < 0.01; 478.8 versus 408.3 ng/mL, p = 0.01; 15.7 versus 11.2 ng/mL, p = 0.02, resp.). The multiple logistic regression analysis demonstrated that only omentin and PSA levels were independent predictors of PCa in studied subjects.

Conclusions

PSA level as well as the level of omentin may be valuable markers of PCa with clinical significance, when compared to PSA.

Prostate Cancer Screening

During the prostate-specific antigen-based prostate cancer (PCa) screening era there has been a 53% decrease in the US PCa mortality rate. Concerns about overdiagnosis and overtreatment combined with misinterpretation of clinical trial data led to a recommendation against PCa screening, resulting in a subsequent reversion to more high-risk disease at diagnosis. Re-evaluation of trial data and increasing acceptance of active surveillance led to a new draft recommendation for shared decision making for men aged 55 to 69 years old. Further consideration is needed for more intensive screening in men with high-risk factors. PCa screening significantly reduces PCa morbidity and mortality.

Clinical multi-omics strategies for the effective cancer management

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis.

BIOLOGICAL SIGNIFICANCE

In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer.

Commentary: Building an Evidence Base for Promoting Informed Prostate Cancer Screening Decisions: An Overview of a Cancer Prevention and Control Program

African American (AA) men have significantly higher mortality rates from prostate cancer (PrCA) than other racial groups. Therefore, there is a critical need to identify strategies for promoting informed PrCA screening decisions among this population. This article details the community-driven, social and behavioral research being implemented by a Statewide Cancer Prevention and Control Program (CPCP) to support the development of person-to-person and technological interventions to improve the dissemination of PrCA information to AA men and their families. This article concludes with four recommendations to advance future research and practice related to the use of interventions for promoting informed PrCA decision-making among AAs. These recommendations include: 1) informing men about controversial screening recommendations; 2) including families in educational interventions about PrCA; 3) using technology as a modality for disseminating PrCA information when appropriate; and 4) aiming to create interventions that can be translated into community and clinical settings.