1.Construction of miRNA-target networks and gene GO analysis of the specific target genes in colorectal cancer with liver metastasis
Chengyu LUO ; Jun YANG ; Deming YU ; Xiaoxin JI ; Xinfei ZHAO
Chinese Journal of General Surgery 2013;(2):116-119
Objective To explore the microRNA expression changes and related characteristics and analyze the corresponding miRNA target genes and their bioinformatics in colorectal cancer with liver metastasis.Methods The fresh specimens of primary CRC were collected in 10 patients during operation,with liver metastasis or without.The miRNA expression levels were compared by miRNA microarray between two groups.Then,target genes were identified using target prediction algorithms.The liver metastasis related miRNA-target networks and gene ontology (GO) bioinformatics analysis were further performed.Results A total of six dysregulated miRNAs were identified in colorectal cancer liver metastasis comparing with no metastasis,including 3 up-regulated miRNAs (miR-224,miR-1236,miR-622) and 3 downregulated miRNAs (miR-155,miR-342-5p,miR-363).miR-224 with most significantly up-regulation played regulation role not only with corresponding target-genes but also downstream genes.Conclusions As a core of the regulation networks,miR-224 can regulate the related gene functional groups simultaneously and asynchronously.It further implements the post-transcriptional regulation and plays a vital role in liver metastasis of colorectal cancer.
2.Prognostic value of urine paraquat concentrations combined with poisoning time and creatinine clearance rate ;on prognosis in patients with acute paraquat poisoning
Haitao SHEN ; Na WU ; Jun HAN ; Hang ZHAO ; Xinfei HAN ; Min ZHAO
Chinese Critical Care Medicine 2016;28(10):881-885
Objective To evaluate the prognostic value of urine paraquat (PQ) concentrations combined with poisoning time and creatinine clearance rate (CCr) on prognosis of patients with acute paraquat poisoning (APP). Methods A retrospective case control study was conducted. Clinical data of 96 patients with APP admitted to Department of Emergency of Shengjing Hospital of China Medical University from March 2014 to May 2016 were analyzed. The gender, age, body weight, urine PQ concentrations (determined by semi-quantitative colorimetric method), poisoning time (time from oral poison to urine detection) and CCr of patients were collected, and poisoning index (poisoning index = urine PQ concentrations × poisoning time/CCr) and simplified poisoning index (simplified poisoning index = urine PQ concentrations × poisoning time) were calculated. The patients were divided into death group and survival group according to 2-month outcome after poisoned with clinical data and telephone follow-up. The urine PQ concentrations, poisoning index, and simplified poisoning index between the two groups were compared. Binary classification logistic regression was used to analyze the risk factors affecting prognosis. Receiver-operating characteristic curve (ROC) and diagnostic test were used to analyze the prognostic value of the parameters. Results Compared with survival group, the urine PQ concentrations [mg/L: 30.00 (10.00, 100.00) vs. 10.00 (3.00, 10.00)], poisoning index [mg·h-1·μmol-1: 12.72 (1.86, 33.75) vs. 0.56 (0.18, 1.12)], and simplified poisoning index [mg·h-1·L-1: 600.00 (150.00, 1 000.00) vs. 60.00 (18.00, 120.00)] in death group were significantly increased (all P < 0.01). It was shown by logistic regression analysis that both urine PQ concentrations [odds ratio (OR) = 1.046, 95% confidence interval (95%CI) = 1.006-1.087, P = 0.022] and poisoning index (OR = 1.353, 95%CI = 0.029-1.815, P = 0.031) were independent risk factors affecting the prognosis of patients with APP. It was shown by ROC curve and diagnostic test that the poisoning index had greater area under ROC curve (AUC was 0.902) for evaluating the prognosis of patients with APP. When the best cut-off value was greater than 1.23 mg·h-1·μmol-1, the sensitivity was 90.91%, and the specificity was 73.08%. The AUC of urine PQ concentrations for evaluating the prognosis was 0.759. When the best cut-off value was greater than 20.00 mg/L, the sensitivity was 63.64%, and the specificity was 76.92%. The AUC of simplified poisoning index for evaluating the prognosis was 0.846. When the best cut-off value was greater than 135.00 mg·h-1·L-1, the sensitivity was 81.82%, and the specificity was 76.92%. Conclusion The poisoning index calculated with urine PQ concentrations combined with poisoning time and CCr has prognostic value for prognosis of APP patients, and the prognostic value of poisoning index is greater than that of the urine PQ concentrations alone.