Weighted gene coexpression network analysis and machine learning reveal oncogenome associated microbiome plays an important role in tumor immunity and prognosis in pan-cancer.

BACKGROUND: For many years, the role of the microbiome in tumor progression, particularly the tumor microbiome, was largely overlooked. The connection between the tumor microbiome and the tumor genome still requires further investigation. METHODS: The TCGA microbiome and genome data were obtained from Haziza et al.'s article and UCSC Xena database, respectively. Separate WGCNA networks were constructed for the tumor microbiome and genomic data after filtering the datasets. Correlation analysis between the microbial and mRNA modules was conducted to identify oncogenome associated microbiome module (OAM) modules, with three microbial modules selected for each tumor type. Reactome analysis was used to enrich biological processes. Machine learning techniques were implemented to explore the tumor type-specific enrichment and prognostic value of OAM, as well as the ability of the tumor microbiome to differentiate TP53 mutations. RESULTS: We constructed a total of 182 tumor microbiome and 570 mRNA WGCNA modules. Our results show that there is a correlation between tumor microbiome and tumor genome. Gene enrichment analysis results suggest that the genes in the mRNA module with the highest correlation with the tumor microbiome group are mainly enriched in infection, transcriptional regulation by TP53 and antigen presentation. The correlation analysis of OAM with CD8+ T cells or TAM1 cells suggests the existence of many microbiota that may be involved in tumor immune suppression or promotion, such as Williamsia in breast cancer, Biostraticola in stomach cancer, Megasphaera in cervical cancer and Lottiidibacillus in ovarian cancer. In addition, the results show that the microbiome-genome prognostic model has good predictive value for short-term prognosis. The analysis of tumor TP53 mutations shows that tumor microbiota has a certain ability to distinguish TP53 mutations, with an AUROC value of 0.755. The tumor microbiota with high importance scores are Corallococcus, Bacillus and Saezia. Finally, we identified a potential anti-cancer microbiota, Tissierella, which has been shown to be associated with improved prognosis in tumors including breast cancer, lung adenocarcinoma and gastric cancer. CONCLUSION: There is an association between the tumor microbiome and the tumor genome, and the existence of this association is not accidental and could change the landscape of tumor research.

Expression and prognostic significance of the DNA damage response pathway and autophagy markers in gastric cancer.

Gastric cancer (GC) is a leading cause of mortality and morbidity worldwide. We assessed the expression patterns of DNA damage response (DDR)-related markers, including ATM, CHK2, p-p53 (S15), Rad51, and BRCA2 and autophagy-related proteins including p62 and Beclin-1 in 153 GC specimens using immunohistochemistry staining. GC tissues showed lower levels of ATM, CHK2, p-p53, BRCA2, and higher levels of Rad51 compared to adjacent normal tissues. The autophagy-related protein p62 was upregulated, whereas Beclin-1 was downregulated in human GC groups. Additionally, different statuses of DDR pathways and autophagy characterized by protein expression were associated with overall survival. Our results indicated that the impairment of DNA damage and autophagy may be implicated in gastric cancer progression and its clinical prognosis.

DNA aptamers that target human glioblastoma multiforme cells overexpressing epidermal growth factor receptor variant III in vitro.

AIM: Aptamers are oligonucleic acid or peptide molecules that bind to a specific target molecule in cells, thus may act as effective vehicles for drug or siRNA delivery. In this study we investigated the DNA aptamers that target human glioblastoma multiforme (GBM) cells overexpressing epidermal growth factor receptor variant III (EGFRvIII), which was linked to radiation and chemotherapeutic resistance of this most aggressive brain tumor. METHODS: A 73-mer ssDNA library containing molecules with 30 nt of random sequence flanked by two primer hybridization sites was chosen as the initial library. Cell systematic evolution of ligands by exponential enrichment (Cell-SELEX) method was used to select the DNA aptamers that target EGFRvIII. The binding affinity of the aptamers was measured using a cell-based biotin-avidin ELISA. RESULTS: After 14 rounds of selection, four DNA aptamers (32, 41, 43, and 47) that specifically bound to the EGFRvIII-overexpressing human glioma U87Δ cells with Kd values of less than 100 nmol/L were discovered. These aptamers were able to distinguish the U87Δ cells from the negative control human glioma U87MG cells and HEK293 cells. Aptamer 32 specifically bound to the EGFRvIII protein with an affinity similar to the EGFR antibody (Kd values of aptamer 32 and the EGFR antibody were 0.62±0.04 and 0.32±0.01 nmol/L, respectively), and this aptamer was localized in the cell nucleus. CONCLUSION: The DNA aptamers are promising molecular probes for the diagnosis and treatment of GBM.

[Studies on glycosides from Gentiana veitchiorum].

OBJECTIVE: To study the chemical constituents of Gentiana veitchiorum. METHOD: The chemical constituents were isolated by chromatography and identified by spectral data. RESULT: Five glycosides, loganic acid (1), gentiopicroside (2), isoorientin 3'-methyl ether (3), isovitexin (4), isoorientin (5) were isolated and identified. CONCLUSION: Compounds 1-5 were isolated from this plant for the first time.