Acute leukemia (AL) is a group of highly heterogeneous hematological malignancies. Circular RNAs (circRNAs) are covalently closed circRNA molecules implicated in the development of many diseases. However, the role of circRNAs in AL remains largely unknown. Therefore, this study aimed to identify new classification diagnostic biomarkers for subgroups of AL. The circRNA expression signatures discriminating acute lymphoblastic leukemia (ALL) from acute myeloid leukemia (AML) were identified by microarray, followed by reverse transcription quantitative polymerase chain reaction (RT-qPCR) validation. Receiver operating characteristic curve analysis was used to evaluate the diagnostic efficiencies of hsa_circ_0001857 and hsa_circ_0012152, and hsa_circ_0012152 was selected for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. The results showed that the circRNA expression profiles, hsa_circ_0001857, and hsa_circ_0012152 could clearly discriminate ALL from AML. The target genes of hsa_circ_0012152 might be involved in biological processes, such as myeloid cell differentiation, covalent chromatin modification, histone modification, and rat sarcoma (Ras) protein signal transduction, and participate in pathways such as mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3′-kinase (PI3K)-Akt signaling pathway. Hsa_circ_0012152 might be involved in the initiation and development of AML through miR-491-5p/epidermal growth factor receptor (EGFR)/MAPK1 or miR-512-3p/EGFR/MAPK1 axis. Our results showed that circRNA expression profiles and specifically expressed circRNAs were promising classification biomarkers to designate AL into ALL or AML.

Background: It is well known that the prognosis of Gastric cancer (GC) patient is affected by many factors. However, the latent impact of anoikis on the prognosis of GC patients is insufficient understood.Methods: According to the Cancer Genome Atlas (TCGA) database, we elected discrepantly expressed anoikis-related genes (ARGs). Univariate cox and the least absolute shrinkage and selection operator (lasso) analysis were applied to build the ARGs signature. The prognostic effect of the ARGs signature was also evaluated. A series of algorithms were performed to evaluate the discrepancies in the immune microenvironment. Moreover, the correlation between drug sensitivity and ARGs signature was analyzed. We also performed Real-Time Polymerase Chain Reaction (RT-PCR) to probe the signature.Results: The ARGs signature of 9 genes was constructed, which was apparently interrelated with the prognosis. The nomogram was established by combining the ARGs signature with clinicopathological characteristics. We found that the predictive power was noteworthily superior to other individual predictors. The immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, StromalScores, tumor immune dysfunction and exclusion (TIDE) score were lower in the low-risk group, while immunophenoscore (IPS) was on the contrary. The infiltrated immune cells and immune checkpoint (ICP) expression levels were significantly different between the two groups. Furthermore, nine drugs were positively associated with the ARGs signature score. The results of RT-PCR analysis were consistent with our previous differential expression analysis.Conclusion: The developed ARGs signature could act as the biomarker and provide a momentous reference for Individual therapy of GC patients.

Co-stimulatory molecules have been shown to enhance antitumor immune responses, but their role in Diffuse Large B-cell Lymphoma (DLBCL) remains unexplored. This study aimed to explore the molecular typing of DLBCL with co-stimulatory molecule genes and to construct a prognostic profile to improve treatment decisions and clinical outcomes. We conducted the first comprehensive analysis of co-stimulatory molecules in DLBCL patients and identified five co-stimulatory molecule genes with prognostic and diagnostic values. Consensus cluster analysis based on these five co-stimulatory molecule genes revealed that the two identified clusters had different distribution patterns and prognostic differences. Co-stimulatory molecular correlation signatures were then constructed based on these five co-stimulatory molecular genes and validated in an external dataset, showing good performance in predicting patient prognosis. The signature is an independent risk factor for DLBCL patients and significantly correlates with clinical factors in patients and can be used as a complement to clinical factors. Furthermore, the signature was associated with the tumor immune microenvironment. Patients identified as being at high risk according to our signature exhibit high levels of immune cell infiltration microenvironment. In conclusion, our signature can provide clinicians with prognostic predictions and help guide the treatment of patients with DLBCL.

Introduction: Although the effects of U2 small nuclear RNA auxiliary factor 1 gene ( U2AF1) mutations on the outcomes of patients with myelodysplastic syndromes (MDS) have previously been investigated, their prognostic significance remains controversial. We performed a meta-analysis to investigate the impact of U2AF1 mutations on MDS progression. Methods: Two reviewers independently extracted information such as hazard ratios (HRs) and 95% confidential intervals (CIs) for overall survival (OS) and leukemia-free survival (LFS) as well as the number of surviving patients each year after diagnosis from the included studies. Results: Thirteen studies with a total of 3038 patients were included. The summary odds ratio (OR) for U2AF1 mutations with an OS of 5 years was 0.37, the summary HR for U2AF1 mutations in OS was 1.60, and the summary OR for an OS of 5 years in patients with U2AF1^S34 and U2AF1^Q157 was 3.68. There were no significant differences in leukemia-free survival or hypomethylating therapy response between patients with and without U2AF1 mutations. Conclusion: U2AF1 mutations were associated with poor survival in MDS patients, and patients with U2AF1^Q157 had a worse OS than those with U2AF1^S34. Our findings suggest that MDS patients with U2AF1 mutations could benefit more from hypomethylation therapy.

Background: Graft-versus-host disease (GVHD) is one of the most complex complications after allogeneic stem cell transplantation. Current standard of grading system is based on clinical symptoms in skin, liver and intestinal. However, it’s difficult to differ GVHD and its extent just by clinical manifestation. Here we retrospectively analyzed cell immune function in patients implemented allogeneic stem cell transplantation in Ningbo first Hospital from Jan 2013 to Jan 2018. Results: the data are collected from 51 patients (mean age was 42; 45.1% women). The average NK cell percentage was 39.31% in severe GVHD (Grade III-IV), was 16.98% in mild GVHD (GradeI-II), while was 21.15% in No GVHD group. The statistical analysis showed difference among each grade. Further analysis was performed in Antithymocyte globulin (ATG) treated group and control group. We showed NK Cell percentage was sharply different in ATG treated group: 47.34% in severe GVHD, 11.98% in mild GVHD group, while 18.3% in no GVHD group. However, in control group, the average percentage of NK cells was 23.27% in severe GVHD, was 23.22%in mild GVHD group, while was 21.13% in no GVHD group. Conclusion: The data supports that ATG can prevent GVHD by increasing NK cell percentage. The percentage of NK cell seemed to be a useful probe to evaluate the severity of GVHD in allogeneic stem cell transplantation patients using ATG in pretreatment.