Screening of biomarkers associated with diagnosis and prognosis of colorectal cancer.

We aimed to explore biomarkers associated with diagnosis and prognosis of colorectal cancer. Differentially expressed protein (DEP) genes were obtained and validated. Moreover, co-expressed genes were screened and their prognostic value was evaluated. In addition, miRNAs that were negatively correlated with DEP genes were identified and used to construct a competitive endogenous RNA network. Furthermore, a support vector machine model was built using DEP genes, and a receiver operating characteristic curve was implemented to confirm its prediction performance. The results showed that only one DEP gene, CCL26, was obtained. Moreover, 43 genes co-expressed with CCL26 were identified, among which six (AP3M2, DAPK1, ISYNA1, PPM1K, PRR4 and RNF122) were linked with the prognosis of colorectal cancer. Besides, the axis RP11-47122.2/RP11-527N22.1-hsa-miR-3192-5p-CCL26 was identified as an lncRNA-miRNA-target gene network. Support vector machine model analysis showed that the area under the curve of CCL26 reached 0.878 based on GEO data and 0.743 based on our protein data. In conclusion, AP3M2, DAPK1, ISYNA1, PPM1K, PRR4, RNF122, CCL26 and hsa-miR-3192-5p appear to be related to the progression of colorectal cancer.

IL-8, MSPa, MIF, FGF-9, ANG-2 and AgRP collection were identified for the diagnosis of colorectal cancer based on the support vector machine model.

Colorectal cancer (CRC) is one of the most common cancer, and the early detection of CRC is essential to improve the survival rate of patients. To identify diagnostic markers for colorectal cancer (CRC) by screening differentially expressed proteins (DEPs) in CRC. The DEPs were initially obtained from 12 CRC samples and 12 healthy control samples, and verification analysis was performed in another 34 CRC samples and 34 normal controls. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment with DEPs was analyzed by the R package clusterProfiler (Version 3.2.11), and the DEP-associated protein-protein interaction (PPI) network was created from the STRING database. Additionally, Support Vector Machine (SVM) model prediction and survival analyses were conducted on the key DEPs. Preliminary screening and functional analysis showed that the DEPs mainly overrepresented in pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, Rap1, Ras, and MAPK signaling pathways. The key DEPs, including AgRP, ANG-2, Dtk, EOT3, FGF-4, FGF-9, HCC-4, IL-16, IL-8, MIF, MSPa, TECK, TPO, TRAIL R3, and VEGF-D, were used to construct a custom chip. The drug-gene interaction network suggested that TPO was a key drug target. ROC curve showed the SVM diagnostic model with the DEPs IL-8, MSPa, MIF, FGF-9, ANG-2, and AgRP had better diagnostic performance with an AUC of 0.933. Survival analysis showed the expression of FGF9, TPO, TRAIL R3, Dtk, TECK and FGF4 were associated with prognosis. This study revealed the important serum proteins in the pathogenesis of CRC, which might serve as useful and noninvasive predictors for the diagnosis of CRC.

Identification of an MiRNA-mRNA Regulatory Network in Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) is the fourth most prevalent cancer in the world. However, the molecular mechanism underlying CRC is largely unknown. OBJECTIVE: To explore the pathogenic mechanism of CRC and to facilitate better diagnosis and treatment of this disease. METHODS: Differentially expressed miRNAs (DEMs) and genes (DEGs) in CRC vs. Control samples from the miRNA expression data in GSE115513 and the miRNA and mRNA expression data in the TCGA-COAD dataset were screened, followed by the construction of the miRNAmRNA regulatory network. Functional and pathway enrichment analysis, protein-protein interaction (PPI) analysis, and survival analysis were then performed for these DEGs and DEMs. RESULTS: We identified 64 DEMs from the GSE115513 dataset and 265 DEMs and 2218 DEGs from the TCGA-COAD dataset. miR-27a-3p was a hub DEM with the highest degree in the miRNA-mRNA network, while GRIN2B and PCDH10 were hub DEGs targeted by multiple miRNAs, including miR-27a-3p. SNAP25 and GRIN2B were also hub DEGs with the highest degree of interactions in the PPI network. These DEMs and DEGs were significantly enriched in multiple KEGG pathways, including proteoglycans expression and cAMP signaling pathway in cancer. Finally, seven DEGs, including FJX1 Dsc2, and hsa-miR-375, were revealed to be correlated with CRC prognosis. CONCLUSION: Aberrant expressions of genes and miRNAs were involved in the pathogenesis of CRC, probably by regulating proteoglycans expression and cAMP signaling. miR-27a-3p, PCDH10, GRIN2B, FJX1, Dsc2, and hsa-miR-375 were identified as potential targets for understanding the pathogenic mechanism of CRC. In addition, FJX1, Dsc2 and hsa-miR-375 were identified as potential predictive markers for CRC prognosis.

Pregnancy-Related ICU Admissions From 2008 to 2016 in China: A First Multicenter Report.

OBJECTIVES: To identify the key points for improving severe maternal morbidity by analyzing pregnancy-related ICU admissions in Beijing. DESIGN: This was a retrospective, multicenter cohort study. SETTING: Three ICUs in tertiary hospitals in Beijing. PATIENTS: A total of 491 severe maternal cases in any trimester of pregnancy or within 42 days of delivery were reviewed between January 1, 2008, and December 31, 2016. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among 491 obstetric ICU admissions (median Sequential Organ Failure Assessment score, 2) out of 87,850 hospital deliveries (a frequency of 5.6 admissions per 1,000 deliveries), the leading diagnoses were postpartum hemorrhage (170; 34.62%), hypertensive disorders of pregnancy (156; 31.77%), and cardio-cerebrovascular diseases (78; 15.9%). Comparing 2008-2011 to 2012-2016, the rates of maternal mortality (2.5% vs 1.9%; p = 0.991) and fetal loss (8.5% vs 8.6%; p = 0.977) did not decrease significantly, whereas the rates of ICU admission (3.05% vs 7.85%; p trends < 0.001) and postpartum hemorrhage (23% vs 38.5%; p = 0.002) increased. Hypertensive disorder (150/156; 96.2% transferred to the ICU postpartum, 24/28 women with fetal loss transferred from lower-level hospitals) was an independent maternal factor associated with fetal loss, and infections were the leading cause of maternal death (6/10) in the ICU. CONCLUSIONS: Our study highlights the increasing rate of intensive care admissions for postpartum hemorrhage. Improving prenatal care quality for pregnancy-induced hypertension and sepsis at lower-level hospitals may improve maternal and fetal outcomes. Specifically, providing more effective regional cooperation before transfer and shifting patients who require continuous surveillance but not necessarily intensive care to a transitional ward in a tertiary hospital would provide more ICU beds for more prenatal intensive care for the most complex medical conditions.