Recent studies have reported that preadmission metformin users had lower mortality than non-metformin users in patients with sepsis and diabetes mellitus; however, these results are still controversial. Therefore, we conducted a systematic review and meta-analysis of published observational cohort data to determine the association between preadmission metformin use and mortality in septic adult patients with diabetes mellitus. The MEDLINE, EMBASE, and Cochrane CENTRAL databases were searched from their inception to September 30, 2018. Cohort studies that evaluated the use of metformin in septic adult patients with diabetes mellitus were included. The quality of outcomes was evaluated using the Newcastle-Ottawa Scale (NOS). The inverse variance method with random effects modelling was used to calculate the pooled odds ratios (ORs) and 95% CIs. Five observational cohort studies (1282 patients) that were all judged as having a low risk of bias were included. In this meta-analysis, metformin use was associated with a significantly lower mortality rate (OR, 0.59; 95% CI, 0.43–0.79, P = 0.001). This meta-analysis indicated an association between metformin use prior to admission and lower mortality in septic adult patients with diabetes mellitus. This finding suggested that the possible effect of metformin should be evaluated in future clinical trials.

Lung adenocarcinoma (LUAD), largely remains a primary cause of cancer-related death worldwide. The molecular mechanisms in LUAD metastasis have not been completely uncovered. In this study, we identified differentially expressed genes (DEGs), miRNAs (DEMs) and lncRNAs (DELs) underlying metastasis of LUAD from The Cancer Genome Atlas database. Intersection mRNAs were used to perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and co-expression network analysis. In addition, survival analyses of intersection mRNAs were conducted. Finally, intersection mRNAs, miRNAs and lncRNAs were subjected to construct miRNA-mRNA-lncRNA network. A total of 1015 DEGs, 54 DEMs and 22 DELs were identified in LUAD metastasis and non-metastasis samples. GO and KEGG pathway analysis had proven that the functions of intersection mRNAs were closely related with many important processes in cancer pathogenesis. Among the co-expression interactions network, 22 genes in the co-expression network were over the degree 20. These genes imply that they have connections with many other gene nodes. In addition, 14 target genes (ARHGAP11A, ASPM, HELLS, PRC1, TMPO, ARHGAP30, CD52, IL16, IRF8, P2RY13, PRKCB, PTPRC, SASH3 and TRAF3IP3) were found to be associated with survival in patients with LUAD significantly (log-rank P < 0.05). Two lncRNAs (LOC96610 and ADAM6) acting as ceRNAs were identified based on the miRNA-mRNA-lncRNA network. Taken together, the results may provide a novel perspective to develop a multiple gene diagnostic tool for LUAD prognosis, which might also provide potential biomarkers or therapeutic targets for LUAD.

In recent years, immunotherapy has become a hot spot in the treatment of tumors. As an emerging treatment, it solves many problems in traditional cancer treatment and has now become the main method for cancer treatment. Although immunotherapy is promising, most patients do not respond to treatment or develop resistance. Therefore, in order to achieve a better therapeutic effect, combination therapy has emerged. The combination of immune checkpoint inhibition and epigenetic therapy is one such strategy. In this review, we summarize the current understanding of the key mechanisms of how epigenetic mechanisms affect cancer immune responses and reveal the key role of epigenetic processes in regulating immune cell function and mediating anti-tumor immunity. In addition, we highlight the outlook of combined epigenetic and immune regimens, particularly the combination of immune checkpoint blockade with epigenetic agents, to address the limitations of immunotherapy alone.

The incidence and mortality of colorectal cancer (CRC) are increasing year by year. The accurate classification of CRC can realize the purpose of personalized and precise treatment for patients. The tumor microenvironment (TME) plays an important role in the malignant progression and immunotherapy of CRC. An in-depth understanding of the clusters based on the TME is of great significance for the discovery of new therapeutic targets for CRC. We extracted data on CRC, including gene expression profile, DNA methylation array, somatic mutations, clinicopathological information, and copy number variation (CNV), from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) (four datasets—GSE14333, GSE17538, GSE38832, and GSE39582), cBioPortal, and FireBrowse. The MCPcounter was utilized to quantify the abundance of 10 TME cells for CRC samples. Cluster repetitive analysis was based on the Hcluster function of the Pheatmap package in R. The ESTIMATE package was applied to compute immune and stromal scores for CRC patients. PCA analysis was used to remove batch effects among different datasets and transform genome-wide DNA methylation profiling into methylation of tumor-infiltrating lymphocyte (MeTIL). We evaluated the mutation differences of the clusters using MOVICS, DeconstructSigs, and GISTIC packages. As for therapy, TIDE and SubMap analyses were carried out to forecast the immunotherapy response of the clusters, and chemotherapeutic sensibility was estimated based on the pRRophetic package. All results were verified in the TCGA and GEO data. Four immune clusters (ImmClust-CS1, ImmClust-CS2, ImmClust-CS3, and ImmClust-CS4) were identified for CRC. The four ImmClusts exhibited distinct TME compositions, cancer-associated fibroblasts (CAFs), functional orientation, and immune checkpoints. The highest immune, stromal, and MeTIL scores were observed in CS2, in contrast to the lowest scores in CS4. CS1 may respond to immunotherapy, while CS2 may respond to immunotherapy after anti-CAFs. Among the four ImmClusts, the top 15 markers with the highest mutation frequency were acquired, and CS1 had significantly lower CNA on the focal level than other subtypes. In addition, CS1 and CS2 patients had more stable chromosomes than CS3 and CS4. The most sensitive chemotherapeutic agents in these four ImmClusts were also found. IHC results revealed that CD29 stained significantly darker in the cancer samples, indicating that their CD29 was highly expressed in colon cancer. This work revealed the novel clusters based on TME for CRC, which would guide in predicting the prognosis, biological features, and appropriate treatment for patients with CRC.

Since December 2019, patients with unexplained pneumonia have been found in Wuhan City, Hubei Province, China. The pathogen in these cases is a new type of coronavirus. The World Health Organization confirmed this diagnosis and named the pathogen SARSCoV‐2. The disease caused by SARSCoV‐2 is called Corona Virus Disease (COVID‐2019). The virus is highly infectious and pathogenic, causing human‐to‐human transmission. At present, SARSCoV‐2 is still rampant in the world. Zhengzhou City in Henan Province serves as an example, 102 people have been confirmed to be infected with SARSCoV‐2 (at 24:00 on February 5th, 2020), including three children, the youngest is 4 years old. From the perspective of clinical pediatricians as the first line fighting the epidemic, this paper will discuss the clinical characteristics, prevention and control measures, outcomes, diagnosis, and treatment of pediatric cases.

Background: Tumor-associated macrophages (TAMs), the most abundant non-tumor cell population in the glioma microenvironment, play a crucial role in immune evasion and immunotherapy resistance of glioblastoma (GBM). However, the regulatory mechanism of the immunosuppressive TME of GBM remains unclear.