Identification and validation of necroptosis-related prognostic gene signature and tumor immune microenvironment infiltration characterization in esophageal carcinoma.

BACKGROUND: Esophageal carcinoma (ESCA) is a common malignancy with a poor prognosis. Previous research has suggested that necroptosis is involved in anti-tumor immunity and promotes oncogenesis and cancer metastasis, which in turn affects tumor prognosis. However, the role of necroptosis in ESCA is unclear. This study aimed to investigate the relationships between necroptosis-related genes (NRGs) and ESCA. METHODS AND RESULTS: The clinical data and gene expression profiles of ESCA patients were extracted from The Cancer Genome Atlas (TCGA), and 159 NRGs were screened from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We then identified 52 differentially expressed NRGs associated with ESCA and used them for further analysis. Gene ontology (GO) and KEGG functional enrichment analyses showed that these NRGs were mostly associated with the regulation of necroptosis, Influenza A, apoptosis, NOD-like receptor, and NF-Kappa B signaling pathway. Next, univariate and multivariate Cox regression and LASSO analysis were used to identify the correlation between NRGs and the prognosis of ESCA. We constructed a prognostic model to predict the prognosis of ESCA based on SLC25A5, PPIA, and TNFRSF10B; the model classified patients into high- and low-risk subgroups based on the patient's risk score. Furthermore, the receiver operating characteristic (ROC) curve was plotted, and the model was affirmed to perform moderately well for prognostic predictions. In addition, Gene Expression Omnibus (GEO) datasets were selected to validate the applicability and prognostic value of our predictive model. Based on different clinical variables, we compared the risk scores between the subgroups of different clinical features. We also analyzed the predictive value of this model for drug sensitivity. Moreover, Immunohistochemical (IHC) validation experiments explored that these three NRGs were expressed significantly higher in ESCA tissues than in adjacent non-tumor tissues. In addition, a significant correlation was observed between the three NRGs and immune-cell infiltration and immune checkpoints in ESCA. CONCLUSIONS: In summary, we successfully constructed and validated a novel necroptosis-related signature containing three genes (SLC25A5, PPIA, and TNFRSF10B) for predicting prognosis in patients with ESCA; these three genes might also play a crucial role in the progression and immune microenvironment of ESCA.

LPAR2 correlated with different prognosis and immune cell infiltration in head and neck squamous cell carcinoma and kidney renal clear cell carcinoma.

BACKGROUND: Lysophosphatidic acid (LPA) and its receptors play a key role in regulating cancer progression. Upregulation of LPA receptor 2 (LPAR2) plays a role in carcinogenesis; however, the exact role of LPAR2 in tumors remains elusive. This study aims to explore the correlation between LPAR2 expression with tumor prognosis and immune infiltration in pan-cancers. MATERIALS AND METHODS: The expression of LPAR2 in pan-cancers was analyzed using the Online Cancer Microarray Database (Oncomine), Tumor Immune Estimation Resource (TIMER), and UALCAN databases. The effects of LPAR2 on the clinical prognosis in pan-cancer were examined using the Kaplan-Meier plotter (KM plotter) as well as Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Human Protein Atlas (HPA) databases. Moreover, the R software program was applied for validation of expression and prognostic value of LPAR2 in tumor patients in the Cancer Genome Atlas (TCGA) dataset and the Gene Expression Omnibus (GEO) database. The relationship between the expression level of LPAR2 and the clinical and molecular criteria of head and neck squamous cell carcinoma (HNSC) and kidney renal clear cell carcinoma (KIRC) was analyzed using UALCAN, whereas the relationship between LPAR2 expression and prognosis in patients with HNSC and KIRC with different clinical characteristics was examined using the KM plotter. Furthermore, the correlation between LPAR2 expression and tumor immune infiltration was examined using TIMER. The correlation between LPAR2 expression and gene markers of tumor immune infiltrates was analyzed using TIMER and GEPIA. In addition, the cBioPortal for Cancer Genomics was used to calculate the mutations, methylations, and altered neighbor genes of LPAR2. RESULTS: The expression of LPAR2 was significantly correlated with the outcome of multiple types of cancer, especially HNSC and KIRC. Furthermore, high expression of LPAR2 was significantly associated with various immune markers in the immune cell subsets of HNSC and KIRC. CONCLUSIONS: High expression of LPAR2 plays significantly different prognostic roles in HNSC and KIRC possibly owing to its association with different immune markers. LPAR2 is correlated with tumor immune cell infiltration and is a valuable prognostic biomarker for HNSC and KIRC. However, further experiments are required to validate these findings.

Identification of a necroptosis-related prognostic gene signature associated with tumor immune microenvironment in cervical carcinoma and experimental verification.

Cervical carcinoma (CC) has been associated with high morbidity, poor prognosis, and high intratumor heterogeneity. Necroptosis is the significant cellular signal pathway in tumors which may overcome tumor cells' apoptosis resistance. To investigate the relationship between CC and necroptosis, we established a prognostic model based on necroptosis-related genes for predicting the overall survival (OS) of CC patients. The gene expression data and clinical information of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients were obtained from The Cancer Genome Atlas (TCGA). We identified 43 differentially expressed necroptosis-related genes (NRGs) in CESC by examining differential gene expression between CESC tumors and normal tissues, and 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Gene ontology (GO) and KEGG enrichment analysis illustrated that the genes identified were mainly related to cell necrosis, extrinsic apoptosis, Influenza A, I - kappaB kinase/NF - kappaB, NOD - like receptor, and other signaling pathways. Subsequently, least absolute shrinkage and selection operator (LASSO) regression and univariate and multivariate Cox regression analyses were used to screen for NRGs that were correlated with patient prognosis. A prognostic signature that includes CAMK2A, CYBB, IL1A, IL1B, SLC25A5, and TICAM2 was established. Based on the prognostic model, patients were stratified into either the high-risk or low-risk subgroups with distinct survival. Receiver operating characteristic (ROC) curve analysis was used to identify the predictive accuracy of the model. In relation to different clinical variables, stratification analyses were performed to demonstrate the associations between the expression levels of the six identified NRGs and the clinical variables in CESC. Immunohistochemical (IHC) validation experiments explored abnormal expressions of these six NRGs in CESC. We also explored the relationship between risk score of this necroptosis signature and expression levels of some driver genes in TCGA CESC database and Gene Expression Omnibus (GEO) datasets. Significant relationships between the six prognostic NRGs and immune-cell infiltration, chemokines, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoints in CESC were discovered. In conclusion, we successfully constructed and validated a novel NRG signature for predicting the prognosis of CC patients and might also play a crucial role in the progression and immune microenvironment in CC.

LINC00511/hsa-miR-573 axis-mediated high expression of Gasdermin C associates with dismal prognosis and tumor immune infiltration of breast cancer.

Breast cancer (BC) is considered the second commonest human carcinoma and the most incident and mortal in the female population. Despite promising treatments for breast cancer, mortality rates of metastatic disease remain high. Gasdermin C (GSDMC) is an affiliate of the gasdermin (GSDM) family, which is involved in the process of pyroptosis. Pyroptosis is implicated in tumorigenesis, but the role of GSDMC in cancer cells is yet to be fully elucidated. In this study, we investigated the role and mechanism of GSDMC in breast cancer. We conducted a pan-cancer analysis of the expression and prognosis of GSDMC utilizing multidimensional data from The Cancer Genome Atlas (TCGA). We investigated GSDMC expression levels in 15 BC tissues and matched adjacent normal tissues by immunohistochemistry (IHC). Further verification was performed in the Gene Expression Omnibus (GEO) database. We discovered that elevated GSDMC expression was considerably linked to a worse prognosis in breast invasive carcinoma (BRCA). Next, we identified noncoding RNAs (ncRNAs) which contributing to higher expression of GSDMC by a series of expression, survival, and correlation analysis. We finally identified LINC00511/hsa-miR-573 axis to be the most promising ncRNA-associated pathways that account for GSDMC in BRCA. Furthermore, we demonstrated the significant correlations between GSDMC expression and immune infiltrates, immune checkpoints, and immune markers in BRCA. This study illustrated that ncRNAs-mediated upregulation of GSDMC linked to dismal prognosis and also exhibited a correlation with tumor immune cell infiltration in BRCA. It is anticipated to offer novel ideas for the link between pyroptosis and tumor immunotherapy.