CFP is a prognostic biomarker and correlated with immune infiltrates in Gastric Cancer and Lung Cancer

Codonopsis pilosula-derived glycopeptide dCP1 promotes the polarization of tumor-associated macrophage from M2-like to M1 phenotype

The majority of the immune cell population in the tumor microenvironment (TME) consists of tumor-associated macrophages (TAM), which are the main players in coordinating tumor-associated inflammation. TAM has a high plasticity and is divided into two main phenotypes, pro-inflammatory M1 type and anti-inflammatory M2 type, with tumor-suppressive and tumor-promoting functions, respectively. Considering the beneficial effects of M1 macrophages for anti-tumor and the high plasticity of macrophages, the conversion of M2 TAM to M1 TAM is feasible and positive for tumor treatment. This study sought to evaluate whether the glycopeptide derived from simulated digested Codonopsis pilosula extracts could regulate the polarization of M2-like TAM toward the M1 phenotype and the potential regulatory mechanisms. The results showed that after glycopeptide dCP1 treatment, the mRNA relative expression levels of some M2 phenotype marker genes in M2-like TAM in simulated TME were reduced, and the relative expression levels of M1 phenotype marker genes and inflammatory factor genes were increased. Analysis of RNA-Seq of M2-like TAM after glycopeptide dCP1 intervention showed that the gene sets such as glycolysis, which is associated with macrophage polarization in the M1 phenotype, were significantly up-regulated, whereas those of gene sets such as IL-6-JAK-STAT3 pathway, which is associated with polarization in the M2 phenotype, were significantly down-regulated. Moreover, PCA analysis and Pearson's correlation also indicated that M2-like TAM polarized toward the M1 phenotype at the transcriptional level after treatment with the glycopeptide dCP1. Lipid metabolomics was used to further explore the efficacy of the glycopeptide dCP1 in regulating the polarization of M2-like TAM to the M1 phenotype. It was found that the lipid metabolite profiles in dCP1-treated M2-like TAM showed M1 phenotype macrophage lipid metabolism profiles compared with blank M2-like TAM. Analysis of the key differential lipid metabolites revealed that the interconversion between phosphatidylcholine (PC) and diacylglycerol (DG) metabolites may be the central reaction of the glycopeptide dCP1 in regulating the conversion of M2-like TAM to the M1 phenotype. The above results suggest that the glycopeptide dCP1 has the efficacy to regulate the polarization of M2-like TAM to M1 phenotype in simulated TME.

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

Epidemiological and transcriptome data identify shared gene signatures and immune cell infiltration in type 2 diabetes and non-small cell lung cancer

BACKGROUND

Numerous previous studies have reported an association between type 2 diabetes mellitus (T2DM) and lung cancer risk, but the underlying mechanism of the interaction remains unclear. This study aimed to investigate the shared genetic features and immune infiltration processes between lung cancer and T2DM.

METHODS

Epidemiological data from the National Health and Nutrition Examination Survey (NHANES) 2000-2018 was used to explore the relationship between lung cancer and diabetes systematically. In addition, we also used bioinformatics methods to analyze the transcriptome data from the Gene Expression Omnibus (GEO) to explore the potential functional mechanisms from the perspective of genes and immune infiltration.

RESULTS

Logistic regression analysis showed that prediabetes (OR = 3.289,95%CI 1.231, 8.788, p = 0.01760, model 3)and type 2 diabetes (OR = 3.032 95%CI,1.015, 9.054, p = 0.04689) were significantly associated with an increased risk of lung cancer after adjusting for multiple covariates. Data from NHANES showed an inverted U-shaped relationship between fasting blood glucose and glycosylated haemoglobin and the risk of lung cancer (P for non-linear < 0.001). Transcriptome data showed that we screened 57 co-DEGs, of which 25 were up-regulated co-DEGs and 32 were down-regulated. Ten core DEGs were identified by bioinformatics analysis, which were SMC6, CDC27, CDC7, RACGAP1, SMC4, NCF4, NCF1, NCF2, SELPLG and CFP. Correlation analysis showed that some core DEGs were significantly associated with simultaneous dysregulation of immune cells.

CONCLUSION

The identified core genes of NSCLC and T2DM are associated with dysregulated immune cells, which provides a potential research avenue for diagnosing and treating lung cancer combined with diabetes.

A novel machine learning-derived four-gene signature predicts STEMI and post-STEMI heart failure

High mortality and morbidity rates associated with ST-elevation myocardial infarction (STEMI) and post-STEMI heart failure (HF) necessitate proper risk stratification for coronary artery disease (CAD). A prediction model that combines specificity and convenience is highly required. This study aimed to design a monocyte-based gene assay for predicting STEMI and post-STEMI HF. A total of 1,956 monocyte expression profiles and corresponding clinical data were integrated from multiple sources. Meta-results were obtained through the weighted gene co-expression network analysis (WGCNA) and differential analysis to identify characteristic genes for STEMI. Machine learning models based on the decision tree (DT), support vector machine (SVM), and random forest (RF) algorithms were trained and validated. Five genes overlapped and were subjected to the model proposal. The discriminative performance of the DT model outperformed the other two methods. The established four-gene panel (HLA-J, CFP, STX11, and NFYC) could discriminate STEMI and HF with an area under the curve (AUC) of 0.86 or above. In the gene set enrichment analysis (GSEA), several cardiac pathogenesis pathways and cardiovascular disorder signatures showed statistically significant, concordant differences between subjects with high and low expression levels of the four-gene panel, affirming the validity of the established model. In conclusion, we have developed and validated a model that offers the hope for accurately predicting the risk of STEMI and HF, leading to optimal risk stratification and personalized management of CAD, thereby improving individual outcomes.

Aggrephagy-related LncRNAs index: A predictor for HCC prognosis, immunotherapy efficacy, and chemosensitivity

BACKGROUND

Due to the complexity and heterogeneity of hepatocellular carcinoma, the existing clinical staging criterias are insufficient to accurately reflect the tumor microenvironment and predict the prognosis of HCC patients. Aggrephagy, as a type of selective autophagy, is associated with various phenotypes of malignant tumors.

OBJECTIVE

This study aimed to identify and validate a prognostic model based on aggrephagy-related LncRNAs to assess the prognosis and immunotherapeutic response of HCC patients.

METHODS

Based on the TCGA-LIHC cohort, aggrephagy-related LncRNAs were identified. Univariate Cox regression analysis and lasso and multivariate Cox regression were used to construct a risk-scoring system based on eight ARLs. CIBERSORT, ssGSEA, and other algorithms were used to evaluate and present the immune landscape of tumor microenvironment.

RESULTS

The high-risk group had a worse overall survival (OS) than the low-risk group. Patients in the high-risk group are more likely to benefit from immunotherapy because of their high infiltration level and high immune checkpoint expression.

CONCLUSION

The ARLs signature is a powerful predictor of prognosis for HCC patients, and the nomogram based on this model can help clinicians accurately determine the prognosis of HCC patients and screen for specific subgroups of patients who are more sensitive to immunotherapy and chemotherapy.

The genetic and epigenetic regulation of CD55 and its pathway analysis in colon cancer

Background

CD55 plays an important role in the development of colon cancer. This study aims to evaluate the expression of CD55 in colon cancer and discover how it is regulated by transcriptional factors and miRNA.

Methods

The expression of CD55 was explored by TIMER2.0, UALCAN, and Human Protein Atlas (HPA) databases. TRANSFAC and Contra v3 were used to predict the potential binding sites of transcription factors in the CD55 promoter. TargetScan and starBase v2.0 were used to predict the potential binding ability of miRNAs to the 3' untranslated region (3'UTR) of CD55. SurvivalMeth was used to explore the differentially methylated sites in the CD55 promoter. Western blotting was used to detect the expression of TFCP2 and CD55. Dual-luciferase reporter assay and chromatin immunoprecipitation (ChIP) assay were performed to determine the targeting relationship of TFCP2, NF-κB, or miR-27a-3p with CD55. CD55-related genes were explored by constructing a protein-protein interaction (PPI) network and performing pathway analysis by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG).

Results

CD55 was highly expressed in colon cancer tissues. The mRNA and protein expression levels of TFCP2 were reduced by si-TFCP2. NF-κB mRNA was obviously reduced by NF-κB inhibitor and increased by NF-κB activator. CD55 protein was also inhibited by miR-27a-3p. Dual-luciferase reporter assays showed that after knocking down TFCP2 or inhibiting NF-κB, the promoter activity of CD55 was decreased by 21% and 70%, respectively; after activating NF-κB, the promoter activity of CD55 increased by 2.3 times. As TFCP2 or NF-κB binding site was mutated, the transcriptional activity of CD55 was significantly decreased. ChIP assay showed that TFCP2 and NF-κB combined to the promoter of CD55. The luciferase activity of CD55 3'UTR decreased after being co-transfected with miR-27a-3p mimics and increased by miR-27a-3p antagomir. As the miR-27a-3p binding site was mutated, we did not find any significant effect of miR-27a-3p on reporter activity. PPI network assay revealed a set of CD55-related genes, which included CFP, CFB, C4A, and C4B. GO and KEGG analyses revealed that the target genes occur more frequently in immune-related pathways.

Conclusion

Our results indicated that CD55 is regulated by TFCP2, NF-κB, miR-27a-3p, and several immune-related genes, which in turn affects colon cancer.

SIRGs score may be a predictor of prognosis and immunotherapy response for esophagogastric junction adenocarcinoma

Background

Esophagogastric junction adenocarcinoma (EGJA) is a special malignant tumor with unknown biological behavior. PD-1 checkpoint inhibitors have been recommended as first-line treatment for advanced EGJA patients. However, the biomarkers for predicting immunotherapy response remain controversial.

Methods

We identified stromal immune-related genes (SIRGs) by ESTIMATE from the TCGA-EGJA dataset and constructed a signature score. In addition, survival analysis was performed in both the TCGA cohort and GEO cohort. Subsequently, we explored the differences in tumor-infiltrating immune cells, immune subtypes, immune-related functions, tumor mutation burden (TMB), immune checkpoint gene expression, immunophenoscore (IPS) between the high SIRGs score and low SIRGs score groups. Finally, two validation cohorts of patients who had accepted immunotherapy was used to verify the value of SIRGs score in predicting immunotherapy response.

Results

Eight of the SIRGs were selected by LASSO regression to construct a signature score (SIRGs score). Univariate and multivariate analyses in the TCGA and GEO cohort suggested that SIRGs score was an independent risk factor for the overall survival (OS) and it could increase the accuracy of clinical prediction models for survival. However, in the high SIRGs score group, patients had more immune cell infiltration, more active immune-related functions, higher immune checkpoint gene expression and higher IPS-PD1 and IPS-PD1-CTLA4 scores, which indicate a better response to immunotherapy. The external validation illustrated that high SIRGs score was significantly associated with immunotherapy response and immune checkpoint inhibitors (ICIs) can improve OS in patients with high SIRGs score.

Conclusion

The SIRGs score may be a predictor of the prognosis and immune-therapy response for esophagogastric junction adenocarcinoma.

Membrane tension sensing molecule-FNBP1 is a prognostic biomarker related to immune infiltration in BRCA, LUAD and STAD

Background

Formin-binding protein 1/17 (FNBP1/FBP17), as a membrane-bound protein, is wildly expressed in eukaryotic cells and performs a critical role in tumor tumorigenesis and progression. However, the relationship between FNBP1 and immune infiltrating cells, prognostic value in patients still require comprehensive understanding. We purposed to explore the correlations of FNBP1 expression, prognosis and immune infiltration levels in various cancers.

Method

The expression and survival data of FNBP1 were collected from Oncomine, TIMER, GEPIA, Kaplan–Meier Plotter and PrognoScan databases. Correlations between FNBP1 and immune infiltrates were analyzed in TIMER and GEPIA databases.

Results

Compared with normal tissues, FNBP1 is significantly differentially expressed in a variety of tumor tissues. FNBP1 has significant and complex effects on the prognosis of kinds of cancers. High-expression was obviously correlated with better prognosis in breast carcinoma and lung adenocarcinoma, while worse prognosis in stomach adenocarcinoma. Besides, FNBP1 had a correlation with various immune infiltrating cells and diverse immune gene markers in breast invasive carcinoma (BRCA), lung adenocarcinoma (LUAD), and stomach adenocarcinoma (STAD). FNBP1 was also positively correlated with the adjustment of CD8+ cells, T cells, M2 macrophage, neutrophils, monocyte, Th1 cells, T regulatory cells (Treg) and Tumor-associated macrophages (TAMs). The expression level of FNBP1 is closely positively correlated with the expression level of multiple immune checkpoints in the three cancers. In addition, FNBP1 is significantly positively correlated with the expression levels of a variety of immunosuppressive molecules.

Conclusion

Our findings reveal FNBP1 can serve as a significant biomarker to influence the prognosis and the immune infiltrating levels in different cancers. The differential expression of FNBP1 might not only contribute to the judgment of metastatic and non-metastatic tumors but also in the immune escape by upregulating the expression of immune checkpoints.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12865-021-00475-z.