Down regulation of Cathepsin W is associated with poor prognosis in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan-Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein-protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9, and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.

Identification of prognostic immune-related genes in the tumor microenvironment of endometrial cancer.

Endometrial cancer (EC) is one of the most common gynecologic malignancies. To identify potential prognostic biomarkers for EC, we analyzed the relationship between the EC tumor microenvironment and gene expression profiles. Using the ESTIMATE R tool, we found that immune and stromal scores correlated with clinical data and the prognosis of EC patients. Based on the immune and stromal scores, 387 intersection differentially expressed genes were identified. Eight immune-related genes were then identified using two machine learning algorithms. Functional enrichment analysis revealed that these genes were mainly associated with T cell activation and response. Kaplan-Meier survival analysis showed that expression of TMEM150B, CACNA2D2, TRPM5, NOL4, CTSW, and SIGLEC1 significantly correlated with overall survival times of EC patients. In addition, using the TIMER algorithm, we found that expression of TMEM150B, SIGLEC1, and CTSW correlated positively with the tumor infiltration levels of B cells, CD8+ T cells, CD4+ T cells, macrophages, and dendritic cells. These findings indicate that the composition of the tumor microenvironment affects the clinical outcomes of EC patients, and suggests that it may provide a basis for development of novel prognostic biomarkers and immunotherapies for EC patients.

The anti-phytoalexin gene Bx-cathepsin W supports the survival of Bursaphelenchus xylophilus under Pinus massoniana phytoalexin stress.

BACKGROUND: Pine trees challenged by Bursaphelenchus xylophilus invasion produce phytoalexins to combat this nematode. Nevertheless, the phytoalexins of Asian pine trees are ineffective against B. xylophilus. The anti-phytoalexin genes of B. xylophilus disable almost all Asian pine phytoalexins, which has allowed B. xylophilus to devastate pine forests in eastern Asia over the last four decades. However, to date, the factors that stimulate anti-phytoalexin gene expression and the mechanisms by which these genes act are not well understood. RESULTS: Here, we described anti-phytoalexin genes in B. xylophilus using transcriptomic and bioinformatics analyses. The genes that were induced by both Pinus massoniana and carvone and had similarly elevated expression trends were considered anti-phytoalexin genes. Altogether, 187 anti-phytoalexin genes were identified, including 4 cathepsin genes. KEGG pathway enrichment indicated that those cathepsins were related to the Lysosome pathway. Since cathepsins help to maintain metabolic homeostasis by participating in the degradation of heterophagic and autophagic material, the lysosomal cathepsin gene Bx-cathepsin W was cloned and characterized. The results of the RNAi assessment indicated that the knockdown of Bx-cathepsin W reduced the survival rates of B. xylophilus under carvone or P. massoniana stress. The correlation between Bx-cathepsin W and the susceptibility of pines showed that Bx-cathepsin W might help improve the anti-phytotoxin ability of B. xylophilus. CONCLUSIONS: The results indicated that the anti-phytoalexin gene Bx-cathepsin W supported the survival of B. xylophilus under P. massoniana phytoalexin stress. The cDNA library sequencing, differentially expressed gene identification, and WGCNA algorithm analysis provided insight at a systemic level into the gene regulation of B. xylophilus in response to the immune reaction of P. massoniana. These results will lead to a better understanding of the function of nematode defenses in host innate immunity.

Identification of a six-gene signature with prognostic value for patients with endometrial carcinoma.

Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCEC gene expression profiles were first downloaded from the The Cancer Genome Atlas (TCGA) database. After data processing and forward screening, 11 390 key genes were selected. The UCEC samples were randomly divided into training and testing sets. In total, 996 genes with prognostic value were then examined by univariate Cox survival analysis with a P-value <0.01 in the training set. Next, using robust likelihood-based survival modeling, we developed a six-gene signature (CTSW, PCSK4, LRRC8D, TNFRSF18, IHH, and CDKN2A) with a prognostic function in UCEC. A prognostic risk score system was developed by multivariate Cox proportional hazard regression based on this six-gene signature. According to the Kaplan-Meier curve, patients in the high-risk group had significantly poorer overall survival (OS) outcomes than those in the low-risk group (log-rank test P-value <0.0001). This signature was further validated in the testing dataset and the entire TCGA dataset. In conclusion, we conducted an integrated study to develop a six-gene signature for the prognostic prediction of patients with UCEC. Our findings may provide novel biomarkers for prognosis and have significant implications in the understanding of therapeutic targets for UCEC.

Expression pattern of cathepsin W isoforms in peripheral blood and gastroesophageal mucosa of patients with gastroesophageal reflux disease.

Cathepsin W is exclusively expressed in immune cells, and a novel isoform was identified previously. To characterize the expression pattern of the wildtype and isoform Ins10, specific polymerase chain reaction assays were generated and used to study respective transcript levels in peripheral blood cells and gastric biopsies in healthy subjects. The wildtype-encoding transcript levels were 3- and 9-fold higher in mucosal samples and peripheral immune cells, respectively (p<0.05). The predominant expression of wildtype form by infiltrating immune cells was confirmed in 116 patients with gastroesophageal reflux disease and 27 reflux-negative individuals demonstrating that cathepsin W expression is not altered in this disease.