Identification of key factors shaping integrated levels of ACE2 and TMPRSS2 expression in head and neck squamous cell carcinoma.

Objectives: To quantify the integrated levels of ACE2 and TMPRSS2, the two well-recognized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry-related genes, and to further identify key factors contributing to SARS-CoV-2 susceptibility in head and neck squamous cell carcinoma (HNSC). Methods: We developed a metric of the potential for tissue infected with SARS-CoV-2 ("TPSI") based on ACE2 and TMPRSS2 transcript levels and compared TPSI levels between tumor and matched normal tissues across 11 tumor types. For further analysis of HNSC, weighted gene co-expression network analysis (WGCNA), functional analysis, and single sample gene set enrichment analysis (ssGSEA) were conducted to investigate TPSI-relevant biological processes and their relationship with the immune landscape. TPSI-related factors were identified from clinical and mutational domains, followed by lasso regression to determine their relative effects on TPSI levels. Results: TPSI levels in tumors were generally lower than in the normal tissues. In HNSC, the genes highly associated with TPSI were enriched in viral entry-related processes, and TPSI levels were positively correlated with both eosinophils and T helper 17 (Th17) cell infiltration. Furthermore, the site of onset, human papillomaviruses (HPV) status, and nuclear receptor binding SET domain protein 1 (NSD1) mutations were identified as the most important factors shaping TPSI levels. Conclusions: This study identified the infection risk of SARS-CoV-2 between tumor and normal tissues, and provided evidence for the risk stratification of HNSC.

Identification of glycolysis related pathways in pancreatic adenocarcinoma and liver hepatocellular carcinoma based on TCGA and GEO datasets.

BACKGROUND: Abnormal energy metabolism is one of the characteristics of tumor cells, and it is also a research hotspot in recent years. Due to the complexity of digestive system structure, the frequency of tumor is relatively high. We aim to clarify the prognostic significance of energy metabolism in digestive system tumors and the underlying mechanisms. METHODS: Gene set variance analysis (GSVA) R package was used to establish the metabolic score, and the score was used to represent the metabolic level. The relationship between the metabolism and prognosis of digestive system tumors was explored using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Volcano plots and gene ontology (GO) analyze were used to show different genes and different functions enriched between different glycolysis levels, and GSEA was used to analyze the pathway enrichment. Nomogram was constructed by R package based on gene characteristics and clinical parameters. qPCR and Western Blot were applied to analyze gene expression. All statistical analyses were conducted using SPSS, GraphPad Prism 7, and R software. All validated experiments were performed three times independently. RESULTS: High glycolysis metabolism score was significantly associated with poor prognosis in pancreatic adenocarcinoma (PAAD) and liver hepatocellular carcinoma (LIHC). The STAT3 (signal transducer and activator of transcription 3) and YAP1 (Yes1-associated transcriptional regulator) pathways were the most critical signaling pathways in glycolysis modulation in PAAD and LIHC, respectively. Interestingly, elevated glycolysis levels could also enhance STAT3 and YAP1 activity in PAAD and LIHC cells, respectively, forming a positive feedback loop. CONCLUSIONS: Our results may provide new insights into the indispensable role of glycolysis metabolism in digestive system tumors and guide the direction of future metabolism-signaling target combined therapy.

The lncRNA MEG3/miR-16-5p/VGLL4 regulatory axis is involved in etoposide-induced senescence of tumor cells.

BACKGROUND: The senescence of tumor cells is an important tumor suppressor mechanism. The present study aimed to investigate the role of long non-coding RNA (lncRNA) MEG3 (maternally expressed gene 3) in the senescence process of tumor cells and its potential molecular mechanism by competitively binding with microRNA miR-16-5p to regulate the expression of VGLL4 (encoding vestigial like family member 4). METHODS: We used etoposide to construct senescence models of tumor cells. The degree of cellular senescence was detected by senescence-associated ß-galactosidase, cell cycle and senescence-associated secretory phenotype. The expression of lncRNA MEG3, miR-16-5p and VGLL4 in senescent or non-senescent cells was evaluated using a quantitative real-time reverse transcriptase-PCR (qRT-PCR) or western blotting. Dual luciferase reporter assays were used to detect the binding of miR-16-5p to lncRNA MEG3 and VGLL4. The mRNA and protein expression levels of senescence-related markers (p53, p21 and p16) were detected using qRT-PCR or western blotting. RESULTS: Compared to the control group, the expression of lncRNA MEG3 and VGLL4 was significantly up-regulated in senescent cells. Knockdown of lncRNA MEG3 and VGLL4 reduced the degree of senescence and the expression of p21 and p16. lncRNA MEG3 interfered with the expression of miR-16-5p in senescent A549 and MCF-7 cells. The expression of VGLL4 was regulated by miR-16-5p in senescent A549 and MCF-7 cells. lncRNA MEG3 participated in the senescent progress of tumor cells induced by etoposide via the miR-16-5p/VGLL4 axis. CONCLUSIONS: The present study has confirmed the regulatory role of the lncRNA MEG3/miR-16-5p/VGLL4 axis in the low-dose etoposide-induced tumor cell senescence model, which has potential clinical application with respect to treating malignant tumors.

Prognostic Inflammasome-Related Signature Construction in Kidney Renal Clear Cell Carcinoma Based on a Pan-Cancer Landscape.

OBJECTIVE: To investigate the expression patterns and prognostic characteristics of inflammasome-related genes (IRGs) across cancer types and develop a robust biomarker for the prognosis of KIRC. METHODS: The differentially expressed IRGs and prognostic genes among 10 cancers were analyzed based on The Cancer Genome Atlas (TCGA) dataset. Subsequently, an IRGs risk signature was developed in KIRC. Its prognostic accuracy was evaluated by receiver operating characteristic (ROC) analysis. The independent predictive capacity was identified by stratification survival and multivariate Cox analyses. The gene ontology (GO) analysis and principal component analysis (PCA) were performed to explore biological functions of the IRGs signature in KIRC. RESULTS: The expression patterns and prognostic association of IRGs varied from different cancers, while KIRC showed the most abundant survival-related dysregulated IRGs. The IRG signature for KIRC was able to independently predict survival, and the signature genes were mainly involved inimmune-related processes. CONCLUSIONS: The pan-cancer analysis provided a comprehensive landscape of IRGs across cancer types and identified a strong association between IRGs and the prognosis of KIRC. Further IRGs signature represented a reliable prognostic predictor for KIRC and verified the prognostic value of inflammasomes in KIRC, contributing to our understanding of therapies targeting inflammasomes for human cancers.

Development of an autophagy-related signature in pancreatic adenocarcinoma.

In recent years, autophagy has become a research hotspot in the field of pancreatic adenocarcinoma (PAAD) due to its ambiguous roles in pancreatic tumor progression. Hence, it is necessary to assess its clinical significance in a larger cohort of patients with PAAD. Here, we identified autophagy-related genes with prognostic value in PAAD and constructed a risk model based on these genes. We found that patients in high-risk group were significantly associated with poor prognosis. Genome mutation analysis suggested that KRAS and TP53 mutations were significantly higher in high-risk groups. In addition, functional enrichment analysis showed that high-risk groups were associated with immune cell infiltration and tumor-associated signaling pathways. We further performed CIBERSORT analysis and observed increased macrophage infiltration in high-risk group, but decreased B and T cell counts compared to that in low-risk group. Gene set enrichment analysis indicated that the Hippo pathway was enriched in the high-risk group. Further, using weighted gene co-expression network analysis, Yes-associated protein 1 (YAP1) was identified as a critical hub gene. Interestingly, we found that the autophagy status and YAP1 expression status could influence each other, thus creating a positive feedback loop. In conclusion, in this study, we highlighted the clinical significance of autophagy in pancreatic cancer, constructed an autophagy-related prognostic predictive system, and identified a promising target for autophagy regulation in pancreatic cancer.