No significant difference in intermediate key outcomes in men with low- and intermediate-risk prostate cancer managed by active surveillance.

Active surveillance (AS) is standard of care for patients with low-risk prostate cancer (PCa), but its feasibility in intermediate-risk patients is controversial. We compared outcomes of low- and intermediate-risk patients managed with multiparametric magnetic resonance imaging (mpMRI)-supported AS in a community hospital. Of the 433 patients enrolled in AS between 2009 and 2016, 358 complied with AS inclusion criteria (Cancer of the Prostate Risk Assessment (CAPRA) score ≤ 5, Gleason grade group (GGG) ≤ 2, clinical stage ≤ cT2 and prostate-specific antigen (PSA) ≤ 20 ng/ml) and discontinuation criteria (histological-, PSA-, clinical- or radiological disease reclassification). Of the 358 patients, 177 (49%) were low-risk and 181 (51%) were intermediate-risk. Median follow-up was 4.2 years. The estimated 5-year treatment-free survival (TFS) was 56% (95% confidence interval [CI] 51-62%). Intermediate-risk patients had significantly shorter TFS compared with low-risk patients (hazard ratio 2.01, 95% CI 1.47-2.76, p < 0.001). There were no statistically significant differences in the rate of adverse pathology, biochemical recurrence-free survival and overall survival between low- and intermediate-risk patients. Two patients developed metastatic disease and three died of PCa. These results suggest that selected patients with intermediate-risk PCa may be safely managed by mpMRI-supported AS, but longer follow-up is necessary.

PTEN and DNA Ploidy Status by Machine Learning in Prostate Cancer.

Machine learning (ML) is expected to improve biomarker assessment. Using convolution neural networks, we developed a fully-automated method for assessing PTEN protein status in immunohistochemically-stained slides using a radical prostatectomy (RP) cohort (n = 253). It was validated according to a predefined protocol in an independent RP cohort (n = 259), alone and by measuring its prognostic value in combination with DNA ploidy status determined by ML-based image cytometry. In the primary analysis, automatically assessed dichotomized PTEN status was associated with time to biochemical recurrence (TTBCR) (hazard ratio (HR) = 3.32, 95% CI 2.05 to 5.38). Patients with both non-diploid tumors and PTEN-low had an HR of 4.63 (95% CI 2.50 to 8.57), while patients with one of these characteristics had an HR of 1.94 (95% CI 1.15 to 3.30), compared to patients with diploid tumors and PTEN-high, in univariable analysis of TTBCR in the validation cohort. Automatic PTEN scoring was strongly predictive of the PTEN status assessed by human experts (area under the curve 0.987 (95% CI 0.968 to 0.994)). This suggests that PTEN status can be accurately assessed using ML, and that the combined marker of automatically assessed PTEN and DNA ploidy status may provide an objective supplement to the existing risk stratification factors in prostate cancer.

Prognostic value of mitotic checkpoint protein BUB3, cyclin B1, and pituitary tumor-transforming 1 expression in prostate cancer.

The mitotic checkpoint protein BUB3, cyclin B1 (CCNB1) and pituitary tumor-transforming 1 (PTTG1) regulates cell division, and are sparsely studied in prostate cancer. Deregulation of these genes can lead to genomic instability, a characteristic of more aggressive tumors. We aimed to determine the expression levels of BUB3, CCNB1, and PTTG1 as potential prognostic markers of recurrence after radical prostatectomy. Protein levels were determined by immunohistochemistry on three formalin-fixed paraffin-embedded tissue sections from each of the 253 patients treated with radical prostatectomy. Immunohistochemistry scores were obtained by automated image analysis for CCNB1 and PTTG1. Recurrence, defined as locoregional recurrence, distant metastasis or death from prostate cancer, was used as endpoint for survival analysis. Tumors having both positive and negative tumor areas for cytoplasmic BUB3 (30%), CCNB1 (28%), or PTTG1 (35%) were considered heterogeneous. Patients with ≥1 positive tumor area had significantly increased risk of disease recurrence in univariable analysis compared with patients where all tumor areas were negative for cytoplasmic BUB3 (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.41-3.36), CCNB1 (HR = 2.98, 95% CI 1.93-4.61) and PTTG1 (HR = 1.91, 95% CI 1.23-2.97). Combining the scores of cytoplasmic BUB3 and CCNB1 improved risk stratification when integrated with the Cancer of the Prostate Risk Assessment post-Surgical (CAPRA-S) score (difference in concordance index = 0.024, 95% CI 0.001-0.05). In analysis of multiple tumor areas, prognostic value was observed for cytoplasmic BUB3, CCNB1, and PTTG1.

Prognostic value of DNA ploidy and automated assessment of stroma fraction in prostate cancer.

The combination of DNA ploidy and automatically estimated stroma fraction has been shown to correlate with recurrence and cancer death in colorectal cancer. We aimed to extend this observation and evaluate the prognostic importance of this combined marker in prostate cancer. DNA ploidy status was determined by image cytometry and the stroma fraction was estimated automatically on hematoxylin and eosin stained sections in three tumor samples from each patient to account for tumor heterogeneity. The optimal threshold for low (≤56%) and high (>56%) stroma fraction was identified in a discovery cohort (n = 253). The combined marker was validated in an independent patient cohort (n = 259) with biochemical recurrence as endpoint. The combined marker predicted biochemical recurrence independently in the validation cohort. Multivariable analysis showed that the highest risk of recurrence was observed for patients with samples that had both non-diploid ploidy status and a high stroma fraction (hazard ratio: 2.51, 95% confidence interval: 1.18-5.34). In conclusion, we suggest the combination of DNA ploidy and automatically estimated stroma fraction as a prognostic marker for the risk stratification of prostate cancer patients. It may also be a potential generic marker as concurrent results have been described in colorectal cancer.

[Properties of cancer cell DNA affects the prognosis]. / Egenskaper ved kreftcellenes DNA påvirker prognosen.

BACKGROUND: When diagnosing cancer, it is often difficult to predict the further growth and spread of the tumour. One of the features of cancer is an abnormality in the amount of DNA in cancer cell nuclei, so-called DNA aneuploidy. Extensive abnormalities are often due to an unstable genome, which leads to an accumulation of mutations, dysregulation of genes and loss of cell cycle control. This article aims to provide an overview of the prognostic value of DNA ploidy analyses in ovarian, endometrial, prostate and colorectal carcinoma. MATERIAL AND METHOD: This review article is based on literature searches in PubMed for the period 2000­2016. RESULTS: The search resulted in 308 articles. Thirty-three of these, representing an analysis of more than 18 000 tumours, fulfilled the inclusion criteria. In 30 of the 33 articles, a significant correlation was found between DNA ploidy and disease outcome for patients with ovarian, endometrial, prostate and colorectal carcinoma. Patients with aneuploid tumours had a poorer prognosis than those with diploid tumours. INTERPRETATION: DNA ploidy analysis is a prognostic method for patients with ovarian and endometrial carcinoma, and is used as a guide to options for supplemental treatment and fertility-sparing surgery. A review of publications in recent years of DNA ploidy analyses for prostate and colorectal carcinoma reveals that these patient groups may also benefit from these measurements. In general terms, DNA ploidy analyses may help to increase knowledge of who needs supplemental treatment and who does not ­ which may be advantageous in avoiding overtreatment.

Tumour heterogeneity poses a significant challenge to cancer biomarker research.

BACKGROUND: The high degree of genomic diversity in cancer represents a challenge for identifying objective prognostic markers. We aimed to examine the extent of tumour heterogeneity and its effect on the evaluation of a selected prognostic marker using prostate cancer as a model. METHODS: We assessed Gleason Score (GS), DNA ploidy status and phosphatase and tensin homologue (PTEN) expression in radical prostatectomy specimens (RP) from 304 patients followed for a median of 10 years (interquartile range 6-12). GS was assessed for every tumour-containing block and DNA ploidy for a median of four samples for each RP. In a subgroup of 40 patients we assessed DNA ploidy and PTEN status in every tumour-containing block. In 102 patients assigned to active surveillance (AS), GS and DNA ploidy were studied in needle biopsies. RESULTS: Extensive heterogeneity was observed for GS (89% of the patients) and DNA ploidy (40% of the patients) in the cohort, and DNA ploidy (60% of the patients) and PTEN expression (75% of the patients) in the subgroup. DNA ploidy was a significant prognostic marker when heterogeneity was taken into consideration. In the AS cohort we found heterogeneity in GS (24%) and in DNA ploidy (25%) specimens. CONCLUSIONS: Multi-sample analysis should be performed to support clinical treatment decisions.