The mechanism of lncRNAs in the crosstalk between epithelial-mesenchymal transition and tumor microenvironment for early colon adenocarcinoma based on molecular subtyping.

A large number of colon adenocarcinoma (COAD) patients are already advanced when diagnosed. In this study, we aimed to further understand the mechanism of tumor development in early COAD by focusing on epithelial-mesenchymal transition (EMT) and long non-coding RNAs (lncRNAs). Expression profiles of early COAD patients were obtained from public databases. EMT-related lncRNAs were used as a basis for constructing molecular subtypes through unsupervised consensus clustering. Genomic features, pathways and tumor microenvironment (TME) were compared between two subtypes. LncATLAS database was applied to analyze the relation between lncRNAs and transcription factors (TFs). First order partial correlation analysis was conducted to identify key EMT-related lncRNAs.C1 and C2 subtypes with distinct prognosis were constructed. Oncogenic pathways such as EMT, KRAS signaling, JAK-STAT signaling, and TGF-ß signaling were significantly enriched in C2 subtype. Higher immune infiltration and expression of immune checkpoints were also observed in C2 subtype, suggesting the key EMT-related lncRNAs may play a critical role in the modulation of TME. In addition, JAK-STAT signaling pathway was obviously enriched in upregulated TFs in C2 subtype, which indicated a link between key lncRNAs and JAK-STAT signaling that may regulate TME. The study further expanded the research on the role of EMT-related lncRNAs in the early COAD. The six identified EMT-related lncRNAs could serve as biomarkers for early screening COAD.

Identification of an IFN-ß-associated gene signature for the prediction of overall survival among glioblastoma patients.

BACKGROUND: Brain glioblastoma multiforme (GBM) is the most common primary malignant intracranial tumor. The prognosis of this disease is extremely poor. While the introduction of ß-interferon (IFN-ß) regimen in the treatment of gliomas has significantly improved the outcome of patients; The mechanism by which IFN-ß induces increased TMZ sensitivity has not been described. Therefore, the main objective of the study was to elucidate the molecular mechanisms responsible for the beneficial effect of IFNß in GBM. METHODS: Messenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) GBM and GSE83300 dataset from the Gene Expression Omnibus. Univariate Cox regression analysis and lasso Cox regression model established a novel 4-gene IFN-ß signature (peroxiredoxin 1, Sec61 subunit beta, X-ray repair cross-complementing 5, and Bcl-2-like protein 2) for GBM prognosis prediction. Further, GBM samples (n=50) and normal brain tissues (n=50) were then used for real-time polymerase chain reaction experiments. Gene set enrichment analysis (GSEA) was performed to further understand the underlying molecular mechanisms. Pearson correlation was applied to calculate the correlation between the long non-coding RNAs (lncRNAs) and IFN-ß-associated genes. An lncRNA with a correlation coefficient |R2|>0.3 and P<0.05 was considered to be an IFN-ß-associated lncRNA. RESULTS: Patients in the high-risk group had significantly poorer survival than patients in the low-risk group. The signature was found to be an independent prognostic factor for GBM survival. Furthermore, GSEA revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust 4-gene IFN-ß signature for GBM prognosis prediction. The signature might contain potential biomarkers for metabolic therapy and treatment response prediction for GBM patients. CONCLUSIONS: In the present study, we established a novel IFN-ß-associated gene signature to predict the overall survival of GBM patients, which may help in clinical decision making for individual treatment.

High expression of PYCARD is an independent predictor of unfavorable prognosis and chemotherapy resistance in glioma.

BACKGROUND: PYD and CARD domain-containing (PYCARD) was upregulated in TMZ-resistant cell lines and glioma tissue and was correlated with poor prognosis, its role in glioma is unclear known. The aim of this study was to elucidate the relationship between PYCARD and glioma based on Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA) databases. METHODS: Glioma-resistant cells were compared with parental cells based on the GSE53014 and GSE113510 data sets. The relationship between PYCARD, tumor microenvironment, and long noncoding RNAs (lncRNAs) was assessed using logistic regression. Moreover, Kaplan-Meier and Cox regression were used to analyze the relationship between PYCARD expression and survival rate. Gene set enrichment analysis (GSEA) was also used to determine the biological function of PYCARD and lncRNAs. Cell viability and cell migration assays were used to evaluate the ability of cells to migrate and proliferate. Finally, we analyzed the expression patterns of PYCARD genes in a wide range of cancers. RESULTS: Elevated expression of PYCARD promoted glioma cell proliferation and migration. PYCARD expression was significantly positively associated with gamma delta T cells but negatively correlated with M2 macrophages in glioblastoma multiforme (GBM). Likewise, PYCARD expression was significantly positively associated with monocytes but negatively associated with activated mast cells in low grade glioma (LGG). We also found that 3 PYCARD-related lncRNAs in GBM and 4 PYCARD-related lncRNAs in LGG had a predictive value for glioma patients. The pan-cancer analysis showed that PYCARD expression was higher in most cancer groups. CONCLUSIONS: High expression of PYCARD is an independent predictor of unfavorable prognosis and chemotherapy resistance in glioma.