COVID-19-associated lncRNAs as predictors of survival in uterine corpus endometrial carcinoma: A prognostic model.

Background: Patients with uterine corpus endometrial carcinoma (UCEC) may be susceptible to the coronavirus disease-2019 (COVID-19). Long non-coding RNAs take on a critical significance in UCEC occurrence, development, and prognosis. Accordingly, this study aimed to develop a novel model related to COVID-19-related lncRNAs for optimizing the prognosis of endometrial carcinoma. Methods: The samples of endometrial carcinoma patients and the relevant clinical data were acquired in the Carcinoma Genome Atlas (TCGA) database. COVID-19-related lncRNAs were analyzed and obtained by coexpression. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were performed to establish a COVID-19-related lncRNA risk model. Kaplan-Meier analysis, principal component analysis (PCA), and functional enrichment annotation were used to analyze the risk model. Finally, the potential immunotherapeutic signatures and drug sensitivity prediction targeting this model were also discussed. Results: The risk model comprising 10 COVID-19-associated lncRNAs was identified as a predictive ability for overall survival (OS) in UCEC patients. PCA analysis confirmed a reliable clustering ability of the risk model. By regrouping the patients with this model, different clinic-pathological characteristics, immunotherapeutic response, and chemotherapeutics sensitivity were also observed in different groups. Conclusion: This risk model was developed based on COVID-19-associated lncRNAs which would be conducive to the precise treatment of patients with UCEC.

Systematic Analysis of Coronavirus Disease 2019 (COVID-19) Receptor ACE2 in Malignant Tumors: Pan-Cancer Analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) was first detected in patients with pneumonia in December 2019 in China and it spread rapidly to the rest of the world becoming a global pandemic. Several observational studies have reported that cancer is a risk factor for COVID-19. On the other hand, ACE2, a receptor for the SARS-CoV-2 virus, was found to be aberrantly expressed in many tumors. However, the characterization of aberrant ACE2 expression in malignant tumors has not been elucidated. Here, we conducted a systematic analysis of the ACE2 expression profile across 31 types of tumors. METHODS: Distribution of ACE2 expression was analyzed using the GTEx, CCLE, TCGA pan-cancer databases. We evaluated the effect of ACE2 on clinical prognosis using the Kaplan-Meier survival plot and COX regression analysis. Correlation between ACE2 and immune infiltration levels was investigated in various cancer types. Additionally, the correlation between ACE2 and immune neoantigen, TMB, microsatellite instability, Mismatch Repair Genes (MMRs), HLA gene members, and DNA Methyltransferase (DNMT) was investigated. The frequency of ACE2 gene mutation in various tumors was analyzed. Functional enrichment analysis was conducted in various cancer types using the GSEA method. RESULTS: In normal tissues, ACE2 was highly expressed in almost all 31 organs tested. In cancer cell lines, the expression level of ACE2 was low to medium. Although aberrant expression was observed in most cancer types, high expression of ACE2 was not linked to OS, DFS, RFS, and DFI in most tumors in TCGA pan-cancer data. We found that ACE2 expression was significantly correlated with the infiltrating levels of macrophages and dendritic cells, CD4+ T cells, CD8+ T cells, and B cells in multiple tumors. A positive correlation between ACE2 expression and immune neoantigen, TMB, and microsatellite instability was found in multiple cancers. GSEA analysis which was carried out to determine the effect of ACE2 on tumors indicated that several cancer-associated pathways and immune-related pathways were hyperactivated in the high ACE2 expression group of most tumors. CONCLUSION: These findings suggest that ACE2 is not correlated with prognosis in most cancer types. However, elevated ACE2 is significantly correlated with immune infiltrating levels, including those of CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and DCs in multiple cancers, especially in lung and breast cancer patients. These findings suggest that ACE2 may affect the tumor environment in cancer patients with COVID-19.

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.

DPP9: Comprehensive In Silico Analyses of Loss of Function Gene Variants and Associated Gene Expression Signatures in Human Hepatocellular Carcinoma.

Dipeptidyl peptidase (DPP) 9, DPP8, DPP4 and fibroblast activation protein (FAP) are the four enzymatically active members of the S9b protease family. Associations of DPP9 with human liver cancer, exonic single nucleotide polymorphisms (SNPs) in DPP9 and loss of function (LoF) variants have not been explored. Human genomic databases, including The Cancer Genome Atlas (TCGA), were interrogated to identify DPP9 LoF variants and associated cancers. Survival and gene signature analyses were performed on hepatocellular carcinoma (HCC) data. We found that DPP9 and DPP8 are intolerant to LoF variants. DPP9 exonic LoF variants were most often associated with uterine carcinoma and lung carcinoma. All four DPP4-like genes were overexpressed in liver tumors and their joint high expression was associated with poor survival in HCC. Increased DPP9 expression was associated with obesity in HCC patients. High expression of genes that positively correlated with overexpression of DPP4, DPP8, and DPP9 were associated with very poor survival in HCC. Enriched pathways analysis of these positively correlated genes featured Toll-like receptor and SUMOylation pathways. This comprehensive data mining suggests that DPP9 is important for survival and that the DPP4 protease family, particularly DPP9, is important in the pathogenesis of human HCC.

Anti-parasite drug ivermectin can suppress ovarian cancer by regulating lncRNA-EIF4A3-mRNA axes.

RELEVANCE: Ivermectin, as an old anti-parasite drug, can suppress almost completely the growth of various human cancers, including ovarian cancer (OC). However, its anticancer mechanism remained to be further studied at the molecular levels. Ivermectin-related molecule-panel changes will serve a useful tool for its personalized drug therapy and prognostic assessment in OCs. PURPOSE: To explore the functional significance of ivermectin-mediated lncRNA-EIF4A3-mRNA axes in OCs and ivermectin-related molecule-panel for its personalized drug therapy monitoring. METHODS: Based on our previous study, a total of 16 lncRNA expression patterns were analyzed using qRT-PCR before and after ivermectin-treated different OC cell lines (TOV-21G and A2780). Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to analyze the protein expressions of EIF4A3 and EIF4A3-binding mRNAs in ovarian cancer cells treated with and without ivermectin. A total of 411 OC patients from the Cancer Genome Atlas (TCGA) database with the selected lncRNA expressions and the corresponding clinical data were included. Lasso regression was constructed to examine the relationship between lncRNA signature and OC survival risk. The overall survival analysis between high-risk and low-risk groups used the Kaplan-Meier method. Heatmap showed the correlation between risk groups and clinical characteristics. The univariate and multivariate models were established with Cox regression. RESULTS: SILAC-based quantitative proteomics found the protein expression levels of EIF4A3 and 116 EIF4A3-binding mRNAs were inhibited by ivermectin in OC cells. Among the analyzed 16 lncRNAs (HCG15, KIF9-AS1, PDCD4-AS1, ZNF674-AS1, ZNRF3-AS1, SOS1-IT1, LINC00565, SNHG3, PLCH1-AS1, WWTR1-AS1, LINC00517, AL109767.1, STARD13-IT1, LBX2-AS1, LEMD1-AS1, and HOXC-AS3), only 7 lncRNAs (HCG15, KIF9-AS1, PDCD4-AS1, ZNF674-AS1, ZNRF3-AS1, SOS1-IT1, and LINC00565) were obtained for further lasso regression when combined with the results of drug testing and overall survival analysis. Lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565). The high-risk and low-risk groups based on the prognostic model were significantly related to overall survival and clinicopathologic characteristics (survival status, lymphatic invasion, cancer status, and clinical stage) in OC patients and remained independent risk factors according to multivariate COX analysis (p < 0.05). CONCLUSION: Those findings provided the potential targeted lncRNA-EIF4A3-mRNA pathways of ivermectin in OC, and constructed the effective prognostic model, which benefits discovery of novel mechanism of ivermectin to suppress ovarian cancer cells, and the ivermectin-related molecule-panel changes benefit for its personalized drug therapy and prognostic assessment towards its predictive, preventive, and personalized medicine (PPPM) in OCs.

Analysis of 2019-nCoV receptor ACE2 expression in different tissues and its significance study.

BACKGROUND: On March 11, 2020, the World Health Organization (WHO) officially announced that the coronavirus disease 2019 (COVID-19) had reached global pandemic status. Current studies have found that angiotensin-converting enzyme 2 (ACE2) is a cell surface receptor of the novel coronavirus that plays a vital role in the pathogenesis of COVID-19. It is of immense importance for the prevention of virus transmission and treatment to clarify the distribution and expression of ACE2 in various tissues and organs of the body. METHODS: RNAseq transcriptome data and sex data were obtained from the genotype-tissue expression (GTEx) and the Cancer Genome Atlas (TCGA) databases. We separately analyzed the distribution of ACE2 expression in different tissues in the GTEx and TCGA database, and explored the correlation between sex and ACE2 expression levels. Next, the expression levels of ACE2 in different tissues and organs and its correlation with sex were analyzed once again after combing all samples from the two databases. RESULTS: ACE2 expression data were collected from the GTEx database for 6738 normal tissues. Six hundred eighteen tumor tissue data were collected from the TCGA database. The results of the analysis are consistent from different databases. The results indicated that the expression of ACE2 was the highest in the small intestines, higher in tissues such as salivary glands in the testicular, kidney, heart, thyroid and adipose tissues, while the expression of ACE2 was lower in tissues such as the spleen, brain, muscle, pituitary, and skin. There were no significant differences in the expression of ACE2 in the different organs when it came to the individual's sex. CONCLUSIONS: Our study deeply explored the distribution and expression of ACE2 in various tissues of the human body. The tissues and organs with high ACE2 expression were consistent with the current clinical and basic research results of the novel coronavirus. Our study is conducive to the discovery of potential target organs for viral infection, to provide a reference for the development of clinical progress of patients with novel coronavirus infection.

The SARS-CoV-2 host cell receptor ACE2 correlates positively with immunotherapy response and is a potential protective factor for cancer progression.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 29 million people and has caused more than 900,000 deaths worldwide as of September 14, 2020. The SARS-CoV-2 human cell receptor ACE2 has recently received extensive attention for its role in SARS-CoV-2 infection. Many studies have also explored the association between ACE2 and cancer. However, a systemic investigation into associations between ACE2 and oncogenic pathways, tumor progression, and clinical outcomes in pan-cancer remains lacking. Using cancer genomics datasets from the Cancer Genome Atlas (TCGA) program, we performed computational analyses of associations between ACE2 expression and antitumor immunity, immunotherapy response, oncogenic pathways, tumor progression phenotypes, and clinical outcomes in 13 cancer cohorts. We found that ACE2 upregulation was associated with increased antitumor immune signatures and PD-L1 expression, and favorable anti-PD-1/PD-L1/CTLA-4 immunotherapy response. ACE2 expression levels inversely correlated with the activity of cell cycle, mismatch repair, TGF-ß, Wnt, VEGF, and Notch signaling pathways. Moreover, ACE2 expression levels had significant inverse correlations with tumor proliferation, stemness, and epithelial-mesenchymal transition. ACE2 upregulation was associated with favorable survival in pan-cancer and in multiple individual cancer types. These results suggest that ACE2 is a potential protective factor for cancer progression. Our data may provide potential clinical implications for treating cancer patients infected with SARS-CoV-2.