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Background: Most endometrial carcinoma patients are diagnosed at an early stage with a good prognosis. However, a relatively low fraction with lethal disease constitutes a substantial number of patients due to the high incidence rate. Preoperative identification of patients with high risk and low risk for poor outcome is necessary to tailor treatment. Nucleotyping refers to characterization of cell nuclei by image cytometry, including the assessment of chromatin structure by nuclear texture analysis. This method is a strong prognostic marker in many cancers but has not been evaluated in preoperative curettage specimens from endometrial carcinoma., Methods: The prognostic impact of changes in chromatin structure quantified with Nucleotyping was evaluated in preoperative curettage specimens from 791 endometrial carcinoma patients prospectively included in the MoMaTEC multicenter trial., Results: Nucleotyping was an independent prognostic marker of disease-specific survival in preoperative curettage specimens among patients with Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage I-II disease (HR=2.9; 95% CI, 1.2-6.5; P = 0.013) and significantly associated with age, FIGO stage, histologic type, histologic grade, myometrial infiltration, lymph node status, curettage histology type, and DNA ploidy., Conclusions: Nucleotyping in preoperative curettage specimens is an independent prognostic marker for disease-specific survival, with potential to supplement existing parameters for risk stratification to tailor treatment., Impact: This is the first study to evaluate the prognostic impact of Nucleotyping in curettage specimens from endometrial carcinoma and shows that this may be a clinically useful prognostic marker in endometrial cancer. External validation is warranted. Cancer Epidemiol Biomarkers Prev; 26(1); 61-67. ©2016 AACR., (©2016 American Association for Cancer Research.)

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. What's new? The stroma that surrounds tumor cells can have significant effects on tumor growth and behavior. Another hallmark of cancer is aneuploidy caused by genomic instability, which offers an important prognostic marker in several cancer types. In this study, the authors found that combining these two markers—stromal fraction and DNA ploidy—provided a significant predictor of biochemical recurrence in prostate cancer. The low cost, high throughput, and accuracy of digital analysis using this combined method thus promise to provide improved prognostic biomarkers in prostate cancer. [ABSTRACT FROM AUTHOR]

Abstract: DNA ploidy analysis is useful for prognostication in cancer patients, but the genomic details underlying ploidy changes are not fully understood. To improve this understanding, we compared DNA ploidy status with karyotypic and comparative genomic hybridization data on 51 endometrial adenocarcinomas. Out of 34 DNA diploid tumors evaluated by CGH, 16 (47%) showed imbalances, though only two had more than four copy number changes. Ten (29%) had aberrations involving chromosome 1, seven (21%) involving chromosome 10, while one tumor had a chromosome 8 aberration. Four of the seven DNA tetraploid tumors (57%) had imbalances detected by CGH with two (29%) having more than four. Six out of eight DNA aneuploid tumors showed imbalances by CGH, with five (63%) having more than four. The aberrations were observed on chromosomes 1 and 8 in five/eight (63%) cases while four imbalances (50%) involved chromosomes 5, 7 and X. Not surprisingly, we observed a significant correlation between increasing DNA ploidy complexity and increasing number of copy alterations. Gains of material from chromosomes 8 and 7 might be specifically correlated to DNA aneuploidy in endometrial adenocarcinomas since 63% and 50% of the aneuploid compared to 3% of the diploid tumors showed imbalances involving these chromosomes. [Copyright &y& Elsevier]

Background: Nuclear texture analysis is a useful method to obtain quantitative information for use in prognosis of cancer. The first-order gray level statistics of a digitized light microscopic nuclear image may be influenced by variations in the image input conditions. Therefore, we have previously standardized the nuclear gray level mean value and standard deviation. However, there is a clear relation between nuclear DNA content, area, first-order statistics, and texture. For nuclei with approximately the same DNA content, the mean gray level increases with an increasing nuclear area. The aims of the present methodical work were to study: (1) whether the prognostic value of adaptive textural features varies with nuclear area, and (2) the effect of standardizing nuclear first-order statistics. Methods: Nuclei from 134 cases of ovarian cancer were grouped into intervals according to nuclear area. Adaptive features were extracted from two different image sets, i.e., standardized and non-standardized nuclear images. Results: The prognostic value of adaptive textural features varied strongly with nuclear area. A standardization of the first-order statistics significantly reduced this prognostic information. Several single features discriminated the two classes of cancer with a correct classification rate of 70%. Conclusion: Nuclei having an area between 2000–4999 pixels contained most of the class distance information between the good and poor prognosis classes of cancer. By considering the relation between nuclear area and texture, we avoided a loss of information caused by standardizing the first-order statistics and mixing data from cells having different nuclear area. [ABSTRACT FROM AUTHOR]

The aim of this study was to examine any relation between DNA ploidy and previously detected TP53 (p53) or p21[sup WAF1/CIP1] expression in 94 patients with muscle-invasive transitional cell carcinoma of the urinary bladder and to associate these factors with survival. DNA ploidy was determined by image cytometry. In a subgroup of patients, the mutational status of the TP53 gene was assessed by temporal temperature gradient electrophoresis (TTGE) or perpendicular denaturant gradient gel electrophoresis (DGGE) and subsequent sequencing. Significantly more aneuploid than euploid tumours showed TP53 accumulation (p = 0.003). Patients with aneuploid tumours lived longer than patients with euploid tumours (p = 0.003). In the euploid, but not in the aneuploid group, TP53 and p21[sup WAF1/CIP1] were associated with cancer-specific survival (p = 0.002 and 0.02, respectively). Patients with > 50% TP53 expression had the longest survival time. Mutation analyses showed acceptable concordance with TP53 expression. We conclude that DNA aneuploidy may confer increased radiosensitivity in bladder cancer patients and that TP53 accumulation may confer increased radiosensitivity, but its effect is detectable only in euploid tumours. [ABSTRACT FROM AUTHOR]

Simple Summary: Molecular tissue-based prognostic biomarkers are anticipated to complement the current risk stratification systems in prostate cancer, but their manual assessment is subjective and time-consuming. Objective assessment of such biomarkers by machine learning-based methods could advance their adoption in a clinical workflow. PTEN and DNA ploidy status are well-studied biomarkers, which can provide clinically relevant information in prostate cancer at a low cost. Using a cohort of 253 patients who received radical prostatectomy, we developed a novel, fully-automated PTEN scoring in immunohistochemically-stained tissue slides, which could be used to assess PTEN status in a reliable and reproducible manner. In an independent validation cohort of 259 patients, automatically assessed PTEN status was significantly associated with time to biochemical recurrence after radical prostatectomy, and the combination of PTEN and DNA ploidy status further improved risk stratification. These results demonstrate the utility of machine learning in biomarker assessment. 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. [ABSTRACT FROM AUTHOR]

Simple Summary: Chromatin organisation affects gene expression and contributes to carcinogenesis. Automatic quantification of chromatin heterogeneity can be applied to identify patients with increased risk of cancer recurrence and death in several cancer types. We aimed to investigate the prognostic role of diversity of chromatin compartments in relation to chromatin heterogeneity and as a potential supplement to pathological risk classifications in gynaecological carcinomas. To this end, we computed the entropy of both chromatin compartment sizes and optical densities within compartments. In analysis of two cohorts consisting of 1037 patients with gynaecological carcinoma, we observed a moderately strong correlation between the prognostic value of the entropies and chromatin heterogeneity. The entropies provided an objective marker, which, integrated with pathological risk classifications, might possibly contribute to the selection of high-risk stage I ovarian carcinoma patients for adjuvant chemotherapy and to preoperative identification of low-risk endometrial carcinoma patients who are candidates for less extensive surgery. Statistical texture analysis of cancer cell nuclei stained for DNA has recently been used to develop a pan-cancer prognostic marker of chromatin heterogeneity. In this study, we instead analysed chromatin organisation by automatically quantifying the diversity of chromatin compartments in cancer cell nuclei. The aim was to investigate the prognostic value of such an assessment in relation to chromatin heterogeneity and as a potential supplement to pathological risk classifications in gynaecological carcinomas. The diversity was quantified by calculating the entropy of both chromatin compartment sizes and optical densities within compartments. We analysed a median of 281 nuclei (interquartile range (IQR), 273 to 289) from 246 ovarian carcinoma patients and a median of 997 nuclei (IQR, 502 to 1452) from 791 endometrial carcinoma patients. The prognostic value of the entropies and chromatin heterogeneity was moderately strongly correlated (r ranged from 0.68 to 0.73), but the novel marker was observed to provide additional prognostic information. In multivariable analysis with clinical and pathological markers, the hazard ratio associated with the novel marker was 2.1 (95% CI, 1.3 to 3.5) in ovarian carcinoma and 2.4 (95% CI, 1.5 to 3.9) in endometrial carcinoma. Integration with pathological risk classifications gave three risk groups with distinctly different prognoses. This suggests that the novel marker of diversity of chromatin compartments might possibly contribute to the selection of high-risk stage I ovarian carcinoma patients for adjuvant chemotherapy and low-risk endometrial carcinoma patients for less extensive surgery. [ABSTRACT FROM AUTHOR]