Background: The prognostic value of neutrophil-to-lymphocyte ratio (NLR) and monocyte-to-lymphocyte ratio (MLR) in metastatic gastric cancer (mGC) treated with systemic chemotherapy is largely unknown, especially second-line chemotherapy. We retrospectively investigated the prognostic value of baseline NLR and MLR in the progression of mGC with systemic chemotherapy.

As one of the local treatments, cryoablation plays an increasingly important role in the comprehensive treatment of malignant tumors with its advantages of less trauma, high reproducibility, and minimally invasive. Activation of anti-tumor immunity, another characteristic of cryoablation, has attracted more and more attention with the extensive application of immunotherapy. Unfortunately, the mechanism by which cryoablation enhances anti-tumor immunity is still unclear. In this study, we applied a multi-omics approach to investigate the effects of local cryoablation in the distal tumor microenvironment. The results revealed that large amounts of tumor antigens were released post-cryoablation, leading to a sterile inflammatory response in distant tumors. During this period, activated lysosome-related pathways result in over-expression of SNAP23 (Synaptosome associated protein 23) and STXBP2 (Syntaxin binding protein 2), activation of immune effector cells, suppression of the release of immunosuppressive factors, and finally enhancement of anti-tumor immunity, which shows a broad prospect in combined immunotherapy.

Aims. Gastric cancer (GC) is often diagnosed at an advanced stage; inexpensive and valid biomarkers for GC are still unavailable. We aimed to evaluate the prognosis of the combination of pretreatment red cell distribution width (RDW) and neutrophil-to-lymphocyte ratio (NLR) in patients with GC.Methods. A retrospective analysis from 103 GC patients who were diagnosed at our institution from 2012 to 2016 was performed. Both pretreatment RDW and NLR were calculated based on the recommended cutoff values of 13.4% and 2.755, respectively. Combined values of RDW and NLR (RDW + NLR) stratified patients into a score of 0 (RDW ≤ 13.4% and NLR ≤ 2.755), a score of 1 (RDW > 13.4% or NLR > 2.755), and a score of 2 (RDW > 13.4% and NLR > 2.755). Prognostic significances for overall survival (OS) and progression-free survival (PFS) were assessed.Results. Pretreatment RDW + NLR was a significantly independent prognostic factor for OS and PFS. Moreover, high RDW + NLR was strongly related to age, tumor location, TNM stage, CA125, and CA199. In a subgroup analysis for patients with advanced gastric cancer (AGC), we observed that the level of RDW + NLR was markedly associated with OS and PFS.Conclusion. Pretreatment RDW + NLR is a simple, inexpensive, and valid prognostic system to predict the survival in patients with GC, especially AGC.

Background New biomarkers are needed to identify different clinical outcomes for HER2+ breast cancer (BC). Methods Differential genes of HER2+ BC were screened based on TCGA database. We used WGCNA to identify the genes related to the survival. Genetic Algorithm was used to structure risk prediction model. The prognostic model was validated in GSE data. Results We constructed a risk prediction model of 6 genes to identify prognosis of HER2+ BC, including CLEC9A, PLD4, PIM1, PTK2B, AKNAD1 and C15orf27. Kaplan-Meier curve showed that the model effectively distinguished the survival of HER2+ BC patients. The multivariate Cox regression suggested that the risk model was an independent predictor for HER2+ BC. Analysis related to immune showed that significant differences in immune infiltration between high- and low-risk groups classified by the prognostic model. Conclusions Our study identified a risk prediction model of 6 genes that could distinguish the prognosis of HER2+ BC.

The aim of the present study was to identify genes under the effect of transforming growth factor‑β (TGF‑β1), high glucose (HG) and glucosamine (GlcN) in MES‑13 mesangial cells and elucidate the molecular mechanisms of diabetic nephropathy (DN). The gene expression datasets GSE2557 and GSE2558 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were independently screened using the GEO2R online tool. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. The protein‑protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape software. The hub genes were identified by the NetworkAnalyzer plugin. Overlapping genes were subjected to molecular docking analysis using SystemsDock. A total of 202 upregulated and 158 downregulated DEGs from the HG‑treated groups, 138 upregulated and 103 downregulated DEGs from the GlcN‑treated groups, and 81 upregulated and 44 downregulated DEGs from the TGF‑β1‑treated groups were identified. The majority of the DEGs were independently enriched in ‘nucleosome assembly’, ‘chromatin silencing’ and ‘xenobiotic glucuronidation’. In addition, KEGG pathways were significantly enriched in ‘systemic lupus erythematosus’, ‘protein processing in endoplasmic reticulum’ and ‘aldarate metabolism pathway’, and ‘TNF signaling pathway’ intersected in the TGF‑β1‑treated and HG‑treated groups. In total, eight hub genes, Jun, prostaglandin‑endoperoxide synthase 2 (Ptgs2), fibronectin 1 (Fn1), cyclin‑dependent kinase (Cdk)2, Fos, heat shock protein family A (Hsp70) member 5 (Hspa5), Hsp90b1 and homo sapiens hypoxia upregulated 1 (Hyou1), and three overlapping genes, Ras homolog gene family, member B (RHOB), complement factor H (CFH) and Krüppel‑like factor 15 (KLF15), were selected. Valsartan with RHOB, and fosinopril with CFH and KLF15 had preferential binding activity. In conclusion, Jun, Ptgs2, Fn1, Cdk2, Fos, Hspa5, Hsp90b1, Hyou1, RHOB, CFH and KLF15 may be potential therapeutic targets for mesangial cells associated with DN, which may provide insight into DN treatment strategies.

Background: There is strong evidence that apatinib is effective in the treatment of third- or later-line advanced metastatic gastric cancer (mGC). Hematology prediction index is a convenient and cheap method to predict the prognosis of disease. However, the prognosis of baseline hematological parameters of peripheral blood, such as neutrophil-to-lymphocyte ratio (NLR), carbohydrate antigen 125 (CA125) and albumin (ALB) on mGC treated with apatinib have not been identified.