Multidrug resistance of non‑small cell lung cancer (NSCLC) is a common clinical problem, which is one of the main reasons leading to the failure of chemotherapy. Therefore, how to overcome or prevent drug resistance has become a hot and difficult issue in clinical research. The present study was designed to investigate the expression patterns, functions and underlying mechanisms of MUC1 in regulating paclitaxel‑resistant cell line A549/PR in NSCLC. RT‑qPCR and western blot was performed to determine the mRNA and protein level, respectively. CCK‑8 was conducted to determine the cell viability of A549/PR cells. Moreover, flow cytometry assay was applied to examine the apoptosis rate of A549/PR. Herein, the MUC1 was over‑expressed in clinic NSCLC tissues and A549/PR cells. Silence of MUC1 could obviously suppress the proliferation and promote apoptosis of A549/PR cells in treatment of paclitaxel through up‑regulating the expression of Bax and Caspase‑3, and down‑regulating the expression of Bcl‑2, suggesting that chemotherapy combined with the modulation of MUC1 might be characterized as a promising therapeutic approach to overcome paclitaxel‑resistance in NSCLC in the future.
Lung squamous cell carcinoma (LUSC), one of the most common subtypes of lung cancer, is a leading cause of cancer-caused deaths in the world. It has been well demonstrated that a deep understanding of the tumor environment in cancer would be helpful to predict the prognosis of patients. This study aimed to evaluate the tumor environment in LUSC, and to construct an efficient prognosis model involved in specific subtypes. Four expression files were downloaded from the Gene Expression Omnibus (GEO) database. Three datasets (GSE19188, GSE2088, GSE6044) were considered as the testing group and the other dataset (GSE11969) was used as the validation group. By performing LUSC immune subtype consensus clustering (CC), LUSC patients were separated into two immune subtypes comprising subtype 1 (S1) and subtype 2 (S2). Weighted gene co-expression network (WGCNA) and least absolute shrinkage and selection operator (LASSO) were performed to identify and narrow down the key genes among subtype 1 related genes that were closely related to the overall survival (OS) of LUSC patients. Using immune subtype related genes, a prognostic model was also constructed to predict the OS of LUSC patients. It showed that LUSC patients in the S1 immune subtype exhibited a better OS than in the S2 immune subtype. WGCNA and LASSO analyses screened out important immune subtype related genes in specific modules that were closely associated with LUSC prognosis, followed by construction of the prognostic model. Both the testing datasets and validation dataset confirmed that the prognostic model could be efficiently used to predict the OS of LUSC patients in subtype 1. We explored the tumor environment in LUSC and established a risk prognostic model that might have the potential to be applied in clinical practice.
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-β-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.
Lung squamous cell carcinoma (LUSC), one of the most common subtypes of lung cancer, is a leading cause of cancer-caused deaths in the world. It has been well demonstrated that a deep understanding of the tumor environment in cancer would be helpful to predict the prognosis of patients. This study aimed to evaluate the tumor environment in LUSC, and to construct an efficient prognosis model involved in specific subtypes.Four expression files were downloaded from the Gene Expression Omnibus (GEO) database. Three datasets (GSE19188, GSE2088, GSE6044) were considered as the testing group and the other dataset (GSE11969) was used as the validation group. By performing LUSC immune subtype consensus clustering (CC), LUSC patients were separated into two immune subtypes comprising subtype 1 (S1) and subtype 2 (S2). Weighted gene co-expression network (WGCNA) and least absolute shrinkage and selection operator (LASSO) were performed to identify and narrow down the key genes among subtype 1 related genes that were closely related to the overall survival (OS) of LUSC patients. Using immune subtype related genes, a prognostic model was also constructed to predict the OS of LUSC patients.It showed that LUSC patients in the S1 immune subtype exhibited a better OS than in the S2 immune subtype. WGCNA and LASSO analyses screened out important immune subtype related genes in specific modules that were closely associated with LUSC prognosis, followed by construction of the prognostic model. Both the testing datasets and validation dataset confirmed that the prognostic model could be efficiently used to predict the OS of LUSC patients in subtype 1.We explored the tumor environment in LUSC and established a risk prognostic model that might have the potential to be applied in clinical practice.
Esophageal cancer (EC) is a common malignant tumor of the digestive system with high mortality and morbidity. Current evidence suggests that immune cells and molecules regulate the initiation and progression of EC. Accordingly, it is necessary to identify immune-related genes (IRGs) affecting the biological behaviors and microenvironmental characteristics of EC.Bioinformatics methods, including differential expression analysis, Cox regression, and immune infiltration prediction, were conducted using R software to analyze the Gene Expression Omnibus (GEO) dataset. The Cancer Genome Atlas (TCGA) cohort was used to validate the prognostic signature. Patients were stratified into high- and low-risk groups for further analyses, including functional enrichment, immune infiltration, checkpoint relevance, clinicopathological characteristics, and therapeutic sensitivity analyses.A prognostic signature was established based on 21 IRGs (S100A7, S100A7A, LCN1, CR2, STAT4, GAST, ANGPTL5, TRAV39, F2RL2, PGLYRP3, KLRD1, TRIM36, PDGFA, SLPI, PCSK2, APLN, TICAM1, ITPR3, MAPK9, GATA4, and PLAU). Compared with high-risk patients, better overall survival rates and clinicopathological characteristics were found in low-risk patients. The areas under the curve of the two cohorts were 0.885 and 0.718, respectively. Higher proportions of resting CD4+ memory T lymphocytes, M2 macrophages, and resting dendritic cells and lower proportions of follicular helper T lymphocytes, plasma cells, and neutrophils were found in the high-risk tumors. Moreover, the high-risk group showed higher expression of CD44 and TNFSF4, lower expression of PDCD1 and CD40, and higher TIDE scores, suggesting they may respond poorly to immunotherapy. High-risk patients responded better to chemotherapeutic agents such as docetaxel, doxorubicin, and gemcitabine. Furthermore, IRGs associated with tumor progression, including PDGFA, ITPR3, SLPI, TICAM1, and GATA4, were identified.Our immune-related signature yielded reliable value in evaluating the prognosis, microenvironmental characteristics, and therapeutic sensitivity of EC and may help with the precise treatment of this patient population.
Objective
To investigate curative effect of pramipexole in combination with hyperbaric oxygen therapy in Parkinson’s disease patients with dyssomnia.
Methods
80 Parkinson’s disease patients with dyssomnia were randomly divided into three groups according to the therapy. Pramipexole group (25 cases) was treated with oral pramipexole, hyperbaric oxygen group (25 cases) was treated with hyperbaric oxygen therapy, combination group (30 cases) was treated with oral pramipexole combined with hyperbaric oxygen therapy. All patients were treated for 2 months, compared the sleep quality, the degree of anxiety and depression before and after treatment.
Results
After treatment, PQSI score and ESS score of combination group were (4.36±1.22) and (2.19±3.52), significantly lower than those of pramipexole group [(6.88±1.83), (5.62±4.33)] and hyperbaric oxygen group [(6.54±1.66), (5.16±3.96)], with statistically significant differences among three groups (P 0.05). The time in bed, total sleep time, sleep efficiency of combination group were significantly higher than those of pramipexole group and hyperbaric oxygen group (P<0.05), the sleep latency and the times of arousal were significantly lower than those of pramipexole group and hyperbaric oxygen group (P<0.05).
Conclusion
Pramipexole combined with hyperbaric oxygen therapy has significant effect in Parkinson’s disease patients with dyssomnia, which can effectively improve sleep efficiency and sleep quality, worthy of clinical promotion.
Key words:
Pramipexole; Hyperbaric oxygen; Parkinson's disease; Dyssomnia; Sleep quality
Background: Due to the severe toxicity of carboplatin and cisplatin, nedaplatin and lobaplatin are increasingly used in advanced lung adenocarcinoma (LUAD). However, there are no studies comparing lobaplatin with nedaplatin in the treatment of advanced LUAD. In this study, patients with LUAD were treated with PN or PL, and the safety and efficacy of the two regimens were evaluated. Methods: A total of 344 locally advanced or advanced LUAD patients first-line treated with nedaplatin plus pemetrexed (PN) or lobaplatin plus pemetrexed (PL) were enrolled. There were 175 patients in PN group and 169 patients in PL group. The primary endpoint was leukopenia and thrombocytopenia (grade 3 and 4). Secondary endpoints included disease control rate (DCR), objective response rate (OCR), and progression-free survival (PFS). Results: In PN group, the incidence of myelosuppression among 3/4 grade adverse events were 7.4%, and 18.3% in the group that received PL (P < 0.01). Incidences of thrombocytopenia in PN group were 2.3% and in PL group were 10.1% (P < 0.01). The overall PFS of the PN group was 5.6 months (95% CI, 3.76-7.44) and PL group was 4.9 months (95% CI, 4.04-5.76) (P = 0.035). In mutation-negative patients, the median PFS was 5.0 months (95% CI, 3.84-6.17) in the PN group and 4.8 months (95% CI, 4.03-5.57) in the PL group (P = 0.05). There was no significant difference in DCR and ORR between the two groups (P > 0.05). Conclusions: The PL group is associated with a higher risk of hematologic toxicity than PN group. The PFS of PN group was better than that of PL group.
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