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Background: Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed. Methods: Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared. Results: Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for ‘copy-number’ status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined ‘high-risk’ group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves. Conclusions: Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

Background: Upper digestive endoscopy with biopsy and histopathological evaluation of the biopsy material is the standard method for diagnosing gastric cancer (GC). However, this procedure may not be widely available for screening in the developing world, whereas in developed countries endoscopy is frequently used without major clinical gain. There is a high demand for a simple and non-invasive test for selecting the individuals at increased risk that should undergo the endoscopic examination. Here, we studied the feasibility of a nanomaterial-based breath test for identifying GC among patients with gastric complaints. Methods: Alveolar exhaled breath samples from 130 patients with gastric complaints (37 GC/32 ulcers / 61 less severe conditions) that underwent endoscopy/biopsy were analyzed using nanomaterial-based sensors. Predictive models were built employing discriminant factor analysis (DFA) pattern recognition, and their stability against possible confounding factors (alcohol/tobacco consumption; Helicobacter pylori ) was tested. Classification success was determined (i) using leave-one-out cross-validation and (ii) by randomly blinding 25% of the samples as a validation set. Complementary chemical analysis of the breath samples was performed using gas chromatography coupled with mass spectrometry. Results: Three DFA models were developed that achieved excellent discrimination between the subpopulations: (i) GC vs benign gastric conditions, among all the patients (89% sensitivity; 90% specificity); (ii) early stage GC (I and II) vs late stage (III and IV), among GC patients (89% sensitivity; 94% specificity); and (iii) ulcer vs less severe, among benign conditions (84% sensitivity; 87% specificity). The models were insensitive against the tested confounding factors. Chemical analysis found that five volatile organic compounds (2-propenenitrile, 2-butoxy-ethanol, furfural, 6-methyl-5-hepten-2-one and isoprene) were significantly elevated in patients with GC and/or peptic ulcer, as compared with less severe gastric conditions. The concentrations both in the room air and in the breath samples were in the single p.p.b. v range, except in the case of isoprene. Conclusion: The preliminary results of this pilot study could open a new and promising avenue to diagnose GC and distinguish it from other gastric diseases. It should be noted that the applied methods are complementary and the potential marker compounds identified by gas-chromatography/mass spectrometry are not necessarily responsible for the differences in the sensor responses. Although this pilot study does not allow drawing far-reaching conclusions, the encouraging preliminary results presented here have initiated a large multicentre clinical trial to confirm the observed patterns for GC and benign gastric conditions.

Background: Functional microRNAs (miRNAs) in exosomes have been recognised as potential stable biomarkers in cancers. The aim of this study is to identify specific miRNAs in exosome as serum biomarkers for the early detection of recurrence in human colorectal cancer (CRC). Methods: Serum samples were sequentially obtained from six patients with and without recurrent CRC. The miRNAs were purified from exosomes, and miRNA microarray analysis was performed. The miRNA expression profiles and copy number aberrations were explored using microarray and array CGH analyses in 124 CRC tissues. Then, we validated exosomal miRNAs in 2 serum sample sets (90 and 209 CRC patients) by quantitative real-time RT–PCR. Results: Exosomal miR-17-92a cluster expression level in serum was correlated with the recurrence of CRC. Exosomal miR-19a expression levels in serum were significantly increased in patients with CRC as compared with healthy individuals with gene amplification. The CRC patients with high exosomal miR-19a expression showed poorer prognoses than the low expression group ( P <0.001). Conclusions: Abundant expression of exosomal miR-19a in serum was identified as a prognostic biomarker for recurrence in CRC patients.

Background:Tumour budding has been reported as a promising prognostic marker in many cancers. This meta-analysis assessed the prognostic value of tumour budding in oral squamous cell carcinoma (OSCC).Methods:We searched OvidMedline, PubMed, Scopus and Web of Science for articles that studied tumour budding in OSCC. We used reporting recommendations for tumour marker (REMARK) criteria to evaluate the quality of studies eligible for meta-analysis.Results:A total of 16 studies evaluated the prognostic value of tumour budding in OSCC. The meta-analysis showed that tumour budding was significantly associated with lymph node metastasis (odds ratio=7.08, 95% CI=1.75-28.73), disease-free survival (hazard ratio=1.83, 95% CI=1.34-2.50) and overall survival (hazard ratio=1.88, 95% CI=1.25-2.82).Conclusions:Tumour budding is a simple and reliable prognostic marker for OSCC. Evaluation of tumour budding could facilitate personalised management of OSCC.

Abstract Objectives To develop a stochastic model relating measurement uncertainty, including reproducibility, to clinical accuracy, as demonstrated by the receiver operating characteristic curve. Methods A model is developed based on the symmetric case of the well-known binormal distribution. The overall distribution is partitioned further into analytical and biological components based on assumptions derived from the Cotlove criterion. Explicit mathematical solutions are derived and further verified by Monte Carlo analyses. Results The model demonstrates that tests with analytical error that conforms to the classic Cotlove criterion can achieve receiver operating characteristic curves with areas under the curve of 0.68 to 0.76 and Youden indices of 0.26 to 0.38 but have overall agreement for duplicate measurements of only 80% to 82%. Furthermore, the analytically accurate agreement is only 75% to 78%, and the clinically accurate agreement is only 50% to 60%. Conclusions The model suggests that assays may have reasonable clinical accuracy despite having reproducibility of less than 85%. Imperfect assays can substantially improve medical decision-making. The findings must be interpreted with caution given the binormal assumptions, but such assumptions are often useful as a first approximation. Practicing pathologists should feel comfortable performing semiquantitative assays shown to have a strong biological association with clinical outcome.

Background: PD-L1 (programmed cell death 1 ligand 1) on tumour cells suppresses host immunity through binding to its receptor PD-1 on lymphocytes, and promotes peritoneal dissemination in mouse models of ovarian cancer. However, how PD-L1 expression is regulated in ovarian cancer microenvironment remains unclear. Methods: The number of CD8-positive lymphocytes and PD-L1 expression in tumour cells was assessed in ovarian cancer clinical samples. PD-L1 expression and tumour progression in mouse models under conditions of altering IFN- γ signals was assessed. Results: The number of CD8-positive cells in cancer stroma was very high in peritoneally disseminated tumours, and was strongly correlated to PD-L1 expression on the tumour cells ( P <0.001). In mouse models, depleting IFNGR1 (interferon- γ receptor 1) resulted in lower level of PD-L1 expression in tumour cells, increased the number of tumour-infiltrating CD8-positive lymphocytes, inhibition of peritoneal disseminated tumour growth and longer survival ( P =0.02). The injection of IFN- γ into subcutaneous tumours induced PD-L1 expression and promoted tumour growth, and PD-L1 depletion completely abrogated tumour growth caused by IFN- γ injection ( P =0.01). Conclusions: Interferon- γ secreted by CD8-positive lymphocytes upregulates PD-L1 on ovarian cancer cells and promotes tumour growth. The lymphocyte infiltration and the IFN- γ status may be the key to effective anti-PD-1 or anti-PD-L1 therapy in ovarian cancer.