Update of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial

Screening for Lung Cancer

Lung cancer is a global health burden and is among the most common and deadliest of all malignancies worldwide. The goal of screening programs is to detect tumors in earlier, curable stages, consequently reducing disease-specific mortality. The issue of screening has great relevance to thoracic surgeons, who should play a leading role in the debate over screening and its consequences. The burden is on thoracic surgeons to work in a multidisciplinary setting to guide and treat these patients safely and responsibly, ensuring low morbidity and mortality of potential diagnostic or therapeutic interventions.

Epigenetic risk score improves prostate cancer risk assessment

BACKGROUND

Early detection of aggressive prostate cancer (PCa) remains crucial for effective treatment of patients. However, PCa screening remains controversial due to a high rate of overdiagnosis and overtreatment. To better reconcile both objectives, more effective methods for assessing disease severity at the time of diagnosis are needed.

METHODS

The relationship between DNA-methylation and high-grade PCa was examined in a cohort of 102 prospectively enrolled men who received standard 12-core prostate biopsies. EpiScore, an algorithm that quantifies the relative DNA methylation intensities of GSTP1, RASSF1, and APC in prostate biopsy tissue, was evaluated as a method to compensate for biopsy under-sampling and improve risk stratification at the time of diagnosis.

RESULTS

DNA-methylation intensities of GSTP1, RASSF1, and APC were higher in biopsy cores from men diagnosed with GS ≥ 7 cancer compared to men with diagnosed GS 6 disease. This was confirmed by EpiScore, which was significantly higher for subjects with high-grade biopsies and higher NCCN risk categories (both P < 0.001). In patients diagnosed with GS ≥ 7, increased levels of DNA-methylation were present, not only in the high-grade biopsy cores, but also in other cores with no or low-grade disease (P < 0.001). By combining EpiScore with traditional clinical risk factors into a logistic regression model, the prediction of high GS reached an AUC of 0.82 (95%CI: 0.73-0.91) with EpiScore, DRE, and atypical histological findings as most important contributors.

CONCLUSIONS

In men diagnosed with PCa, DNA-methylation profiling can detect under-sampled high-risk PCa in prostate biopsy specimens through a field effect. Predictive accuracy increased when EpiScore was combined with other clinical risk factors. These results suggest that EpiScore could aid in the detection of occult high-grade disease at the time of diagnosis, thereby improving the selection of candidates for Active Surveillance.

Prostate genetic score (PGS-33) is independently associated with risk of prostate cancer in the PLCO trial

BACKGROUND

To investigate the ability of the prostate genetic score (PGS-33), a germ-line biomarker of prostate cancer (PCa) risk, to categorize men participating in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.

METHODS

We obtained the genetic data from the Cancer Genetic Markers of Susceptibility (CGEMS), a nested case control study examining germ-line DNA in the screened arm of the PLCO trial. A PGS-33 was calculated based on their genotype at 33 PCa associated single nucleotide polymorphisms (SNPs). The primary outcome was the diagnosis of PCa and primary predictor was PGS-33.

RESULTS

We identified 2,244 subjects (no cancer, N = 1017) and cases (N = 1227). The PGS-33 (P<0.001), prostate specific antigen (PSA; P < 0.001), family history of PCa (< 0.001), abnormal digital rectal exam (DRE, P < 0.001), and history of ever smoking (P = 0.037) were associated with a PCa diagnosis. In multivariable analysis, the log (PGS-33) was associated with PCa diagnosis with an odds ratio of 1.68 (95% CI 1.36-2.08, P < 0.001), log (PSA) (OR 8.2; 95% CI 6.75-10.04, P < 0.001), and family history of PCa (OR 2.01; 95% CI 1.26-3.20, P = 0.003). PGS-33 quartiles noted an increasing rate of PCa detection in addition to PSA: 43.2% (Q1), 47.8% (Q2), 58.8% (Q3), and 69.4 (Q4) (P < 0.001) and improvement in PSA performance (P < 0.001).

CONCLUSIONS

Germ-line DNA in the form of the PGS-33 is able to risk stratify men regarding their risk of PCa. The PGS-33 may have implications regarding who may benefit most from PCa screening and possibly add to PSA performance.