Identification of lipid metabolism-related gene signature in the bone marrow microenvironment of multiple myelomas through deep analysis of transcriptomic data.

Dysregulated lipid metabolism in the bone marrow microenvironment (BMM) plays a vital role in multiple myeloma (MM) development, progression, and drug resistance. However, the exact mechanism by which lipid metabolism impacts the BMM, promotes tumorigenesis, and triggers drug resistance remains to be fully elucidated.By analyzing the bulk sequencing and single-cell sequencing data of MM patients, we identified lipid metabolism-related genes differential expression significantly associated with MM prognosis, referred to as LMRPgenes. Using a cohort of ten machine learning algorithms and 117 combinations, LMRPgenes predictive models were constructed. Further exploration of the effects of the model risk score (RS) on the survival status, immune status of patients with BMM, and response to immunotherapy was conducted. The study also facilitated the identification of personalized therapeutic strategies targeting specified risk categories within patient cohorts.Analysis of the scRNA-seq data revealed increased lipid metabolism-related gene enrichment scores (LMESs) in erythroblasts and progenitor, malignant, and Tprolif cells but decreased LMESs in lymphocytes. LMESs were also strongly correlated with most of the 50 hallmark pathways within these cell populations. An elevated malignant cell ratio and reduced lymphocytes were observed in the high LMES group. Moreover, the LMRPgenes predictive model, consisting of 14 genes, showed great predictive power. The risk score emerged as an independent indicator of poor outcomes. Inverse relationships between the RS and immune status were noted, and a high RS was associated with impaired immunotherapy responses. Drug sensitivity assays indicated the effectiveness of bortezomib, buparlisib, dinaciclib, staurosporine, rapamycin, and MST-312 in the high-RS group, suggesting their potential for treating patients with high-RS values and poor response to immunotherapy. Ultimately, upon verification via qRT-PCR, we observed a significant upregulation of ACBD6 in NDMM group compared to the control group.Our research enhances the knowledge base regarding the association between lipid metabolism-related genes (LMRGs) and the BMM in MM patients, offering substantive insights into the mechanistic effects of the BMM mediated by LMRGs.

Clinical influencing factors affecting pulmonary hypertension in hemodialysis patients

Background: The fluid status and rate of blood flow through the arteriovenous fistula (AVF) are two important factors affecting hemodynamic in hemodialysis patients; however, their effects on pulmonary hypertension have rarely been studied. Hence, we aimed to evaluate the effects of these factors in hemodialysis patients with pulmonary hypertension. Methods: This single-center cross-sectional survey included 219 maintenance hemodialysis patients (139 [63.5%] male). The prevalence of pulmonary hypertension was 13.6% (30 of 219). Pulmonary artery pressure was measured by echocardiography, fluid status was measured objectively using bioimpedance spectroscopy, and blood flow rate in the AVF (Qa) was determined using Doppler ultrasound. Results: The overall mean overhydration before hemodialysis was 1.5 L (range, 0.6-2.8 L). The mean overhydration in patients with and without pulmonary hypertension was 3.6 L (range, 2.3-4.6 L) and 1.4 L (range, 0.6-2.4 L), respectively (p < 0.001). The overall mean Qa was 780 mL/min (range, 570-1,015.5 mL/min). The mean Qa of patients with and without pulmonary hypertension was 672 mL/min (range, 505.7-982.2 mL/min) and 790 mL/min (range, 591-1,026 mL/min), respectively (p = 0.27). Overhydration (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.08-1.97; p = 0.01), N-terminal prohormone of brain natriuretic peptide (NT-proBNP; OR, 1.36; 95% CI, 1.09-1.71; p = 0.007), and left atrial diameter (OR, 1.14; 95% CI, 1.01-1.28; p = 0.03) were risk factors. Conclusion: Pulmonary hypertension is strongly associated with overhydration, NT-proBNP, and left atrial diameter in hemodialysis patients.

Identification of the cell cycle characteristics of non-small cell lung cancer and its relationship with tumor immune microenvironment, cell death pathways, and metabolic reprogramming.

Background: The genes related to the cell cycle progression could be considered the key factors in human cancers. However, the genes involved in cell cycle regulation in non-small cell lung cancer (NSCLC) have not yet been reported. Therefore, it is necessary to evaluate the genes related to the cell cycle in all types of cancers, especially NSCLC. Methods: This study constituted the first pan-cancer landscape of cell cycle signaling. Cluster analysis based on cell cycle signaling was conducted to identify the potential molecular heterogeneity of NSCLC. Further, the discrepancies in the tumor immune microenvironment, metabolic remodeling, and cell death among the three clusters were investigated. Immunohistochemistry was performed to validate the protein levels of the ZWINT gene and examine its relationship with the clinical characteristics. Bioinformatics analyses and experimental validation of the ZWINT gene were also conducted. Results: First, pan-cancer analysis provided an overview of cell cycle signaling and highlighted its crucial role in cancer. A majority of cell cycle regulators play risk roles in lung adenocarcinoma (LUAD); however, some cell cycle genes play protective roles in lung squamous cell carcinoma (LUSC). Cluster analysis revealed three potential subtypes for patients with NSCLC. LUAD patients with high cell cycle activities were associated with worse prognosis; while, LUSC patients with high cell cycle activities were associated with a longer survival time. Moreover, the above three subtypes of NSCLC exhibited distinct immune microenvironments, metabolic remodeling, and cell death pathways. ZWINT, a member of the cell signaling pathway, was observed to be significantly associated with the prognosis of LUAD patients. A series of experiments verified the higher expression levels of ZWINT in NSCLC compared to those in paracancerous tissues. The activation of epithelial-mesenchymal transition (EMT) induced by ZWINT might be responsible for tumor progression. Conclusion: This study revealed the regulatory function of the cell cycle genes in NSCLC, and the molecular classification based on cell cycle-associated genes could evaluate the different prognoses of patients with NSCLC. ZWINT expression was found to be significantly upregulated in NSCLC tissues, which might promote tumor progression via activation of the EMT pathway.

lncRNA MALAT1/miR­26a/26b/ST8SIA4 axis mediates cell invasion and migration in breast cancer cell lines.

Metastasis­associated lung adenocarcinoma transcript 1 (MALAT1) is a long non­coding RNA that is overexpressed in various human cancers, including breast cancer. Evidence has associated the function of the α­2,8­sialyltransferase (ST8SIA) family with breast cancer. The present study aimed to investigate the potential roles of MALAT1 in breast cancer development and progression using analyses of both breast cancer tissues and cell lines. The mRNA levels of MALAT1, microRNA (miR)­26a/26b and ST8SIA4 were detected by reverse transcription­quantitative PCR (RT­qPCR) and the protein level of ST8SIA4 was assessed by western blot analysis. Cell proliferation, invasion and migration were detected by CCK­8, wound healing and Transwell assays, respectively. Interactions between MALAT1 and miR­26a/26b were assessed using fluorescence in situ hybridization, RNA immunoprecipitation and luciferase reporter assays. Herein, different levels of MALAT1 were primarily observed in human breast cancer samples and cells. Upregulated MALAT1 was a crucial predictor of poor breast cancer prognosis. Altered MALAT1 modulated cell progression in breast cancer. Moreover, miR­26a/26b was confirmed as a direct regulator of MALAT1, and ST8SIA4 was predicted as a target of miR­26a/26b. Functional analysis in human breast cancer cell lines demonstrated that MALAT1 modulated breast cancer cell tumorigenicity by acting as a competing endogenous lncRNA (ceRNA) to regulate ST8SIA4 levels by sponging miR­26a/26b. The identification of the MALAT1/miR­26a/26b/ST8SIA4 axis which contributes to breast cancer progression may constitute a potential new therapeutic target.

Risk factors, outcomes and genotypes of carbapenem-nonsusceptible Klebsiella pneumoniae bloodstream infection: a three-year retrospective study in a large tertiary hospital in Northern China.

OBJECTIVE: To investigate the independent risk factors, outcomes and genotypes associated with carbapenem-non-susceptible K. pneumoniae bloodstream infections (BSIs) in northern China from 2014 to 2016. METHODS: Over a three-year period, a total of 289 K. pneumoniae BSI patients were identified. Medical records were extracted to obtain the clinical information. Polymerase chain reactions (PCRs) were performed to analyse the multilocus sequence typing (MLST) types, Klebsiella pneumoniae carbapenemase (KPC) and metallo-ß-lactamases (MBL) genes, for replicon typing of the 10 randomly selected carbapenem-non-susceptible K. pneumoniae. RESULTS: A total of 59 carbapenem-non-susceptible K. pneumoniae strains were identified. Resistance rates to imipenem, meropenem, ertapenem and amikacin were low. Multivariate analyses showed that a central venous catheter odds ratio (OR) of 4.021 (CI 1.002-16.134); mechanical ventilation of 7.587 (2.856-20.156); Pitt bacteraemia score of 1.481 (CI 1.218-1.800); hospitalization prior to culture of 1.026 (CI 1.001-1.053); and some antibiotic use 30 days prior to K. pneumoniae bacteremia, including carbapenem of 9.123 (CI 2.995-27.791), aminoglycoside of 34.079 (2.091-555.396), and tigecycline of 5.065 (CI 1.261-20.339) were associated with carbapenem-non-susceptible K. pneumoniae bacteremia. Sequence type 11 (ST11) was the most predominant MLST type, which accounted for 50% of the isolates. Eighty per cent of the isolates harbored the KPC-2 gene. The overall 28-day mortality rates of carbapenem-non-susceptible and carbapenem-susceptible K. pneumoniae were 54.24% and 19.56%, respectively. CONCLUSION: Central venous catheter, mechanical ventilation, high Pitt bacteraemia score, hospitalization prior to culture, and prior antibiotic use (carbapenem, aminoglycoside and tigecycline) were identified as independent risk factors for carbapenem-non-susceptible K. pneumoniae BSI, which was mostly caused by KPC-2 in northern China.