A b s t r a c tBackground and aim: Dyslipidaemia is the main risk factor for coronary heart disease (CHD). Plasma lipid levels are conventionally used to predict coronary risk globally, but further studies are required to investigate whether the lipoprotein ratios are superior to conventional lipid parameters as predictors for CHD. Methods:A hospital-based case-control study consisting of 738 CHD patients and 157 control subjects was conducted in a Chinese Han population. Demographic characteristics and plasma lipid or apolipoprotein data were collected. Univariate and multivariate logistic regression analyses were carried out to examine the relationship between the lipoprotein ratios and CHD risk. Results:The CHD group had significantly higher age, non-high-density lipoprotein cholesterol (non-HDL-C), lipoprotein (a) [Lp(a)], triglyceride (TG)/HDL-C, total cholesterol (TC)/HDL-C, low-density lipoprotein cholesterol (LDL-C)/HDL-C, non-HDL-C/HDL-C, very low-density lipoprotein cholesterol (VLDL-C)/HDL-C, and apolipoprotein B100/apolipoprotein AI (apoB100/apoAI) than the control group (p < 0.05 for all). Moreover, the prevalence of male sex, smoking, and hypertension in the CHD group was significantly higher than in the control group. The results from univariate logistic regression analysis showed that the ratios of TC/HDL-C (OR 1.135, 95% CI 1.019-1.265), LDL-C/HDL-C (OR 1.216, 95% CI 1.033-1.431), non-HDL-C/HDL-C (OR 1.135, 95% CI 1.019-1.265), and apoB100/apoAI (OR 1.966, 95% CI 1.013-3.817) significantly increased the risk for CHD. By multivariate logistic regression analysis, the results were not materially altered and each of the four ratios was independently associated with CHD after adjustment for non-lipid coronary risk factors. ApoB100/apoAI showed the strongest association with CHD in both the univariate and multivariate logistic regression analyses. Conclusions:Our data indicate that the lipoprotein ratios are superior to conventional lipid parameters as predictors for CHD. Of the ratios, apoB100/apoAI is the best to predict CHD risk.

Background/Aims: Circular RNAs (circRNAs) are a family of novel non-coding RNAs associated with various diseases, especially cancer. Recent studies have demonstrated that circRNAs participate in pathogenesis mainly by acting as microRNA (miRNA) sponges. The expression profile of circRNAs in acute myeloid leukemia (AML) has rarely been reported. Methods: Profiles of circRNAs were analyzed using an Arraystar human circRNA microarray with 5 bone marrow samples from patients with newly diagnosed AML and 5 from patients with iron-deficiency anemia. Quantitative reverse transcription PCR was used to validate the expression pattern of circRNAs. Furthermore, circRNA–miRNA network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied. Results: CircRNA microarray analysis revealed that 698 circRNAs were differentially expressed in AML patients, with 282 circRNAs found to be upregulated and 416 to be downregulated. Quantitative reverse transcription PCR showed that circ-ANAPC7 was significantly upregulated in AML. Bioinformatics analysis predicted that circ-ANAPC7 acts as a sponge for the miR-181 family, KEGG analysis revealed that it is associated with cancer-related pathways, and GO analysis indicated that most of its target genes are involved in biological processes. Conclusions: These findings show that circ-ANAPC7 is a promising biomarker for AML, and that it might participate in AML pathogenesis by acting as a sponge for the miR-181 family.

These results reveal the feasible functions of lncRNAs in pathogenesis of MM. Further studies are required to explore whether these lncRNAs could serve as candidate therapeutic targets and new molecular biomarkers for MM.

Long non‐coding RNAs (lncRNAs) are transcripts longer than 200 nt that are involved in tumorigenesis and play a key role in cancer progression. To determine whether lncRNAs are involved in acute myeloid leukemia (AML), we analyzed the expression profile of lncRNAs and mRNAs in AML. Five pairs of AML patients and iron deficiency anemia (IDA) controls were screened by microarray. Through coexpression analysis, differently expressed transcripts were divided into modules, and lncRNAs were functionally annotated. We further analyzed the clinical significance of crucial lncRNAs from modules in public data. Finally, the expression of three lncRNAs, RP11‐222K16.2, AC092580.4, and RP11‐305O.6, were validated in newly diagnosed AML, AML relapse, and IDA patient groups by quantitative RT‐PCR, which may be associated with AML patients’ overall survival. Further analysis showed that RP11‐222K16.2 might affect the differentiation of natural killer cells, and promote the immunized evasion of AML by regulating Eomesodermin expression. Analysis of this study revealed that dysregulated lncRNAs and mRNAs in AML vs IDA controls could affect the immune system and hematopoietic cell differentiation. The biological functions of those lncRNAs need to be further validated.

No abstract

Eccrine spiradenoma (ES) is a rare, benign adnexal neoplasm that may easily be mistaken for glomus lesions or angioleiomyoma due to its painfulness and florid vascularization. A 44-year-old male with a blue-colored, nodular tumor on the left knee, present for 10 years, was submitted for diagnosis. Dermatological examination was undertaken, followed by surgical excision of the subcutaneous lesion and histopathological examination of the tissue. Subjective symptoms included tenderness upon palpation and routine investigations were within normal limits. Immunohistochemical analysis of the tumor cells demonstrated positive staining for CK5/CK6, CK8/CK18, S100, as well as small vacuole-like positive for EMA, and was therefore diagnosed as ES. The results of the present study suggest that immunohistochemical assays may be helpful to clarify the diagnosis and differentiate ES from other painful subcutaneous tumors exhibiting similar clinical and histological presentations.

Proteasome inhibitor bortezomib is one of the most effective drugs currently available for the treatment of multiple myeloma (MM). However, the intrinsic and acquired resistance to bortezomib can limit its effectiveness. The activation of heat shock response has been characterized as a potential resistance mechanism protecting MM cells from bortezomib-induced cell death. In this study, in response to bortezomib therapy, we discovered that HSP70 is one of the most substantially upregulated heat shock proteins. In order to further explore approaches to sensitizing bortezomib-based treatment for MM, we investigated whether targeting HSP70 using a specific inhibitor VER-155008 combined with bortezomib could overcome the acquired resistance in MM. We found that HSP70 inhibitor VER-155008 alone significantly decreased MM cell viability. Moreover, the combination of VER-155008 and bortezomib synergistically induced MM cell apoptosis markedly in vitro. Notably, the combined treatment was found to increase the cleavage of PARP, an early marker of chemotherapy-induced apoptosis. Importantly, the reduction of anti-apoptotic Bcl-2 family member Bcl-2, Bcl-xL, and Mcl-1 and the induction of pro-apoptotic Bcl-2 family member BH3-only protein NOXA and Bim were confirmed to be tightly associated with the synergism. Finally, the ER stress marker CHOP (CCAAT-enhancer binding protein homologous protein), which can cause transcriptional activation of genes involved in cell apoptosis, was markedly induced by both VER-155008 and bortezomib. Taken together, our finding of a strong synergistic interaction between VER-155008 and bortezomib may support for combination therapy in MM patients in the future.

Background: Multiple Myeloma (MM) is a hematologic malignant disease whose underlying molecular mechanism has not yet fully understood. Generally, cell adhesion plays an important role in MM progression. In our work, we intended to identify key genes involved in cell adhesion in MM. Methods: First, we identified differentially expressed genes (DEGs) from the mRNA expression profiles of GSE6477 dataset using GEO2R with cutoff criterion of p < 0.05 and [logFC] ≥ 1. Then, GO and KEGG analysis were performed to explore the main function of DEGs. Moreover, we screened hub genes from the protein-protein interaction (PPI) network analysis and evaluated their prognostic and diagnostic values by the PrognoScan database and ROC curves. Additionally, a comprehensive analysis including clinical correlation analysis, GSEA and transcription factor (TF) prediction, pan-cancer analysis of candidate genes was performed using both clinical data and mRNA expression data. Results: First of all, 1383 DEGs were identified. Functional and pathway enrichment analysis suggested that many DEGs were enriched in cell adhesion. 180 overlapped genes were screened out between the DEGs and genes in GO terms of cell adhesion. Furthermore, 12 genes were identified as hub genes based on a PPI network analysis. ROC curve analysis demonstrated that ITGAM, ITGB2, ITGA5, ITGB5, CDH1, IL4, ITGA9, and LAMB1 were valuable biomarkers for the diagnosis of MM. Further study demonstrated that ITGA9 and LAMB1 revealed prognostic values and clinical correlation in MM patients. GSEA and transcription factor (TF) prediction suggested that MYC may bind to ITGA9 and repress its expression and HIF-1 may bind to LAMB1 to promote its expression in MM. Additionally, pan-cancer analysis showed abnormal expression and clinical outcome associations of LAMB1 and ITGA9 in multiple cancers. Conclusion: In conclusion, ITGA9 and LAMB1 were identified as potent biomarkers associated with cell adhesion in MM.