PTPN2, A Key Predictor of Prognosis for Pancreatic Adenocarcinoma, Significantly Regulates Cell Cycles, Apoptosis, and Metastasis.

This study conducted a comprehensive analysis of the members of the PTPN family and emphasized the key role of PTPN2 as a potential therapeutic target and diagnostic biomarker in improving the survival rate of PAAD. Oncomine was used to analyze the pan-cancer expression of the PTPN gene family. The Cancer Genome Atlas (TCGA) data as well as Genotype-Tissue Expression (GTEx) data were downloaded to analyze the expression and prognosis of PTPNs. The diagnosis of PTPNs was evaluated by the experimental ROC curve. The protein-protein interaction (PPI) network was constructed by combining STRING and Cytoscape. The genes of 50 proteins most closely related to PTPN2 were screened and analyzed by GO and KEGG enrichment. The differentially expressed genes of PTPN2 were found by RNA sequencing, and GSEA enrichment analysis was carried out to find the downstream pathways and targets, which were verified by online tools and experiments. Finally, the relationship between PTPN2 and immune cell infiltration in PAAD, and the relationship with immune score and immune checkpoint were studied. The expression patterns and the prognostic value of multiple PTPNs in PAAD have been reported through bioinformatic analyzes. Among these members, PTPN2 is the most important prognostic signature that regulates the progression of PAAD by activating JAK-STAT signaling pathway. Comparison of two PAAD cell lines with normal pancreatic epithelial cell lines revealed that PTPN2 expression was up-regulated as a key regulator of PAAD, which was associated with poor prognosis. Knockdown of PTPN2 caused a profound decrease in PAAD cell growth, migration, invasion, and induced PAAD cell cycle and apoptosis. In addition, we conducted a series of enrichment analyses to investigate the PTPN2-binding proteins and the PTPN2 expression-correlated genes. We suggest that STAT1 and EGFR are the key factors to regulate PTPN2, which are involved in the progression of PAAD. Meanwhile, the silencing of PTPN2 induced the repression of STAT1 and EGFR expression. These findings provide a comprehensive analysis of the PTPN family members, and for PAAD, they also demonstrate that PTPN2 is a diagnostic biomarker and a therapeutic target.

Kuang W ，Wang X ，Ding J ，Li J ，Ji M ，Chen W ，Wang L ，Yang P ... -  《Frontiers in Immunology》

Development and Validation of an Inflammatory Response-Related Gene Signature for Predicting the Prognosis of Pancreatic Adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is a highly dangerous malignant tumor of the digestive tract, and difficult to diagnose, treat, and predict the prognosis. As we all know, tumor and inflammation can affect each other, and thus the inflammatory response in the microenvironment can be used to affect the prognosis. So far, the prognostic value of inflammatory response-related genes in PAAD is still unclear. Therefore, this study aimed to explore the inflammatory response-related genes for predicting the prognosis of PAAD. In this study, the mRNA expression profiles of PAAD patients and the corresponding clinical characteristics data of PAAD patients were downloaded from the public database. The least absolute shrinkage and selection operator (LASSO) Cox analysis model was used to identify and construct the prognostic gene signature in The Cancer Genome Atlas (TCGA) cohort. The PAAD patients used for verification are from the International Cancer Genome Consortium (ICGC) cohort. The Kaplan-Meier method was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were performed to identify the independent predictors of OS. Gene set enrichment analysis (GSEA) was performed to obtain gene ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and the correlation between gene expression and immune infiltrates was investigated via single sample gene set enrichment analysis (ssGSEA). The GEPIA database was performed to examine prognostic genes in PAAD. LASSO Cox regression analysis was used to construct a model of inflammatory response-related gene signature. Compared with the low-risk group, patients in the high-risk group had significantly lower OS. The receiver operating characteristic curve (ROC) analysis confirmed the signature's predictive capacity. Multivariate Cox analysis showed that risk score is an independent predictor of OS. Functional analysis shows that the immune status between the two risk groups is significantly different, and the cancer-related pathways were abundant in the high-risk group. Moreover, the risk score is significantly related to tumor grade, stage, and immune infiltration types. It was also obtained that the expression level of prognostic genes was significantly correlated with the sensitivity of cancer cells to anti-tumor drugs. In addition, there are significant differences in the expression of PAAD tissues and adjacent non-tumor tissues. The novel signature constructed from five inflammatory response-related genes can be used to predict prognosis and affect the immune status of PAAD. In addition, suppressing these genes may be a treatment option.

Deng ZL ，Zhou DZ ，Cao SJ ，Li Q ，Zhang JF ，Xie H ... -  《-》

Screening and validating the core biomarkers in patients with pancreatic ductal adenocarcinoma.

Li Y ，Zhu YY ，Dai GP ，Wu DJ ，Gao ZZ ，Zhang L ，Fan YH ... -  《-》

Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma.

Meng Z ，Ren D ，Zhang K ，Zhao J ，Jin X ，Wu H ... -  《Aging-US》

Comprehensive exploration of immune checkpoint-related genes in the prognosis and tumor immune microenvironment of pancreatic adenocarcinoma.

To comprehensively analyze the clinical significance of Immune Checkpoint-Related Genes (ICRGs) in Pancreatic Adenocarcinoma (PAAD). PAAD tissues and normal pancreatic tissues were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, and 283 ICRGs were integrated by the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome datasets. Unsupervised clustering was used to obtain potential ICRGs-based PAAD subtypes. Wilcoxon test was performed to screen Differentially Expressed ICRGs (DEICRGs), while cox regression analyses were utilized to identify prognosis-related ICRGs and clinicopathological factors, and construct the corresponding models. The Tumor Immune Microenvironment (TIME) was evaluated. Moreover, the authors performed enrichment analysis, Gene Set Enrichment Analysis (GSEA), and transcription factor regulatory networks to realize underlying mechanisms. Three ICRGs-based PAAD subtypes were identified, and they were associated with three ESTIMATE scores, a Tumor Microenvironment (TMB) score, 14 therapeutic immune checkpoints, and infiltration levels of seven immune cells. On top of that, the authors constructed two signatures based on DEICRGs to predict the Overall Survival (OS) (Area Under the ROC Curve [AUC: 0.741∼0.778]) and Progression-Free Survival (PFS) (AUC: 0.746∼0.831) of patients. Two nomograms were established by combining clinical variables and signatures. In addition, the authors found higher infiltration of naïve B cells and CD8+ T-cells in low-risk PAAD patients, and higher infiltration of suppressive immune cells and cancer-related signaling pathways in high-risk PAAD patients. The present study suggested that ICRGs were associated with TIME formation and prognosis of PAAD patients, which may serve as novel clinical biomarkers and therapeutic targets.

Chen X ，Zhang H 《-》