The expression of Programmed cell Death Ligand 1 (PD-L1) is observed in many malignant tumors and is associated with poor prognosis including Gastric Cancer (GC). The relationship between PD-L1 expression and prognosis, however, is controversial in GC. This paper purports to use a meta-analysis to investigate the relationship between PD-L1 expression and prognosis in GC. For this study, the following databases were searched for articles published from June 2003 until February 2017: PubMed, EBSCO, Web of Science and Cochrane Library. The baseline information extracted were: authors, year of publication, country where the study was performed, study design, sample size, follow-up time, baseline characteristics of the study population, pathologic data, overall survival (OS). A total of 15 eligible studies covering 3291 patients were selected for a meta-analysis based on specified inclusion and exclusion criteria. The analysis showed that the expression level of PD-L1 was associated with the overall survival in GC (Hazard Ratio, HR = 1.46, 95%CI = 1.08–1.98, P = 0.01, random-effect). In addition to the above, subgroup analysis showed that GC patients with deeper tumor infiltration, positive lymph-node metastasis, positive venous invasion, Epstein-Barr virus infection positive (EBV+), Microsatellite Instability (MSI) are more likely to expression PD-L1. The results of this meta-analysis suggest that GC patients, specifically EBV+ and MSI, may be prime candidates for PD-1 directed therapy. These findings support anti-PD-L1/PD-1 antibodies as a kind of immunotherapy which is promising for GC.

Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer, and assessing its histopathological grade requires visual inspection by an experienced pathologist. In this study, the histopathological H&E images from the Genomic Data Commons Databases were used to train a neural network (inception V3) for automatic classification. According to the evaluation of our model by the Matthews correlation coefficient, the performance level was close to the ability of a 5-year experience pathologist, with 96.0% accuracy for benign and malignant classification, and 89.6% accuracy for well, moderate, and poor tumor differentiation. Furthermore, the model was trained to predict the ten most common and prognostic mutated genes in HCC. We found that four of them, including CTNNB1, FMN2, TP53, and ZFX4, could be predicted from histopathology images, with external AUCs from 0.71 to 0.89. The findings demonstrated that convolutional neural networks could be used to assist pathologists in the classification and detection of gene mutation in liver cancer.

Background The future of combined immunotherapy (a PD-1/PD-L1 plus a CTLA-4 antagonist) is very bright. However, besides improving efficacy, combined therapy increases treatment-related adverse events (TRAEs). Also, the clinical application is limited in some solid tumors. Methods This paper purports to investigate the TRAEs for the combined immunotherapy aiming for a more appropriate utilization of immune checkpoint inhibitors (ICIs) in clinical practice through a meta-analysis. Results A total of 17 eligible studies covering 2626 patients were selected for a meta-analysis based on specified inclusion and exclusion criteria. The incidence rates of any grade and grade 3 or higher TRAEs were 88% (95%CI, 84–92%) and 41% (95%CI, 35–47%), respectively. The overall incidence of any grade TRAEs leading to discontinuation of treatment was 20% (95%CI, 16–24%). The incidence rate of treatment related deaths was 4.3‰ (95%CI, 1.4‰-8.4‰). Analysis showed that NIVO1 + IPI3 cohort had higher incidences of grade 3 or higher TRAEs (RR = 1.77, 95%CI, 1.34–2.34, p < 0.0001) and any grade TRAEs leading to discontinuation of treatment (RR = 1.81, 95%CI, 1.08–3.04, P = 0.02), compared with NIVO3 + IPI1 regimen. Conclusions The combined therapy had high TRAEs. The TRAEs, especially grade 3 or higher, led to discontinuation of the treatment. Furthermore, the incidence of treatment-related deaths was rare. Moreover, the NIVO3 + IPI1 regimen, regardless of efficacy, is more recommended because of better tolerance and lower adverse events. Electronic supplementary material The online version of this article (10.1186/s12885-019-5785-z) contains supplementary material, which is available to authorized users.