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Objective: To measure the prognostic value of the lymphocyte-monocyte ratio (LMR) in patients with epithelial ovarian cancer (EOC).Methods: We retrospectively examined the LMR as a prognosticator in a cohort of 234 patients with EOC who underwent surgical resection. Patients were categorized into two different groups based on the LMR (LMR-low and LMR-high) using cut-off values determined by receiver operating characteristic (ROC) curve analysis. The objective of the study was to assess the effect of the LMR on progression-free survival (PFS) and overall survival (OS), and to validate the LMR as an independent predictor of survival.Results: Using the data collected from the whole cohort, the optimized LMR cut-off value selected on the ROC curve was 2.07 for both PFS and OS. The LMR-low and LMR-high groups included 48 (20.5%) and 186 patients (79.5%), respectively. The 5-year PFS rates in the LMR-low and LMR-high groups were 40.0 and 62.5% (P < 0.0001), respectively, and the 5-year OS rates in these two groups were 42.2 and 67.2% (P < 0.0001), respectively. On multivariate analysis, we identified age, International Federation of Gynecology and Obstetrics (FIGO) stage, and cancer antigen 125 levels to be the strongest valuable prognostic factors affecting PFS (P = 0.0421, P = 0.0012, and P = 0.0313, respectively) and age, FIGO stage, and the LMR as the most valuable prognostic factors predicting OS (P = 0.0064, P = 0.0029, and P = 0.0293, respectively).Conclusion: The LMR is an independent prognostic factor affecting the survival of patients with EOC.

The aim of this study was to examine the relationship between main air pollutants and all cancer mortality by performing a meta-analysis. We searched PubMed, EMBASE (a biomedical and pharmacological bibliographic database of published literature produced by Elsevier), and the reference lists of other reviews until April 2018. A random-effects model was employed to analyze the meta-estimates of each pollutant. A total of 30 cohort studies were included in the final analysis. Overall risk estimates of cancer mortality for 10 µg/m3 per increase of particulate matter (PM)2.5, PM10, and NO2 were 1.17 (95% confidence interval (CI): 1.11–1.24), 1.09 (95% CI: 1.04–1.14), and 1.06 (95% CI: 1.02–1.10), respectively. With respect to the type of cancer, significant hazardous influences of PM2.5 were noticed for lung cancer mortality and non-lung cancer mortality including liver cancer, colorectal cancer, bladder cancer, and kidney cancer, respectively, while PM10 had harmful effects on mortality from lung cancer, pancreas cancer, and larynx cancer. Our meta-analysis of cohort studies indicates that exposure to the main air pollutants is associated with increased mortality from all cancers.

Colposcopy is widely used to detect cervical cancers, but experienced physicians who are needed for an accurate diagnosis are lacking in developing countries. Artificial intelligence (AI) has been recently used in computer-aided diagnosis showing remarkable promise. In this study, we developed and validated deep learning models to automatically classify cervical neoplasms on colposcopic photographs. Pre-trained convolutional neural networks were fine-tuned for two grading systems: the cervical intraepithelial neoplasia (CIN) system and the lower anogenital squamous terminology (LAST) system. The multi-class classification accuracies of the networks for the CIN system in the test dataset were 48.6 ± 1.3% by Inception-Resnet-v2 and 51.7 ± 5.2% by Resnet-152. The accuracies for the LAST system were 71.8 ± 1.8% and 74.7 ± 1.8%, respectively. The area under the curve (AUC) for discriminating high-risk lesions from low-risk lesions by Resnet-152 was 0.781 ± 0.020 for the CIN system and 0.708 ± 0.024 for the LAST system. The lesions requiring biopsy were also detected efficiently (AUC, 0.947 ± 0.030 by Resnet-152), and presented meaningfully on attention maps. These results may indicate the potential of the application of AI for automated reading of colposcopic photographs. Cervical cancer is the fourth most common cancer in women worldwide, and the second most common cancer among females in developing countries 1. Screening is the principal prevention method aimed at reducing mortality rates. Screening includes certain steps, including population-based Papanicolaou (Pap) testing, colposcopydirected biopsy of suspicious lesions, and the treatment of confirmed pre-cancer lesions 2,3. In women with low-grade intraepithelial lesions (LSIL) or high-grade intraepithelial lesions (HSIL), the risk of pre-cancer is medium to high, and immediate referral for colposcopy is necessary. However, referring all women with atypical squamous cells of undetermined significance (ASC-US) is considered inefficient, as the risk of such cases being pre-cancerous is lower 4. Screening programs have been successful in the developed countries, leading to an approximately 80% decrease in the cervical cancer incidence over the past 4 decades. In contrast, the increase in cervical cancer incidence reported in developing countries 5 has been attributed to the unsuccessful implementation of screening programs. This, has been attributed to logistics in health systems, infrastructural inadequacies, and the lack of expert physicians capable of introducing screening programs and follow-up 6 .

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Cancer growth and dissemination have been extensively studied for a long time. Nevertheless, many new observations on anatomy and histopathology of cancer events are still reported such as formation of a vasculogenic-like network inside aggressive tumors. In this research, new kinds of micro-conduits, named primo-vessels, were found inside the abdominal cavity of NCI-H460 lung cancer murine xenograft models. These vascular threads were largely distributed on the surfaces of various organs and were often connected to peritoneal tumor nodules. Histological and immunofluorescent investigations showed that the primo-vessels had characteristic features that were distinctively different from those of similar-looking lymphatic vessels. They had multiple channels surrounded with loose collageneous matrices, which is in contrast to the single-channel structure of other vascular systems. The rod-shaped nuclei aligned longitudinally along the channels were assumed to be the endothelial cells of the primo-vessels, but LYVE-1, a specific marker of lymphatics, was not expressed, which indicates a clear difference from lymphatic endothelial cells. Taken together these findings on and characterization of the novel threadlike vascular structures in cancer models may have important implications for cancer prognosis and for therapy.

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