P4HA1, a Prognostic Biomarker that Correlates With Immune Infiltrates in Lung Adenocarcinoma and Pan-Cancer

Comprehensive investigation in oncogenic functions and immunological roles of NCBP2 and its validation in prostate cancer

BACKGROUND

Nuclear cap-binding protein 2 (NCBP2), as the component of the cap-binding complex, participates in a number of biological processes, including pre-mRNA splicing, transcript export, translation regulation and other gene expression steps. However, the role of NCBP2 on the tumor cells and immune microenvironment remains unclear. To systematically analyze and validate functions of NCBP2, we performed a pan-cancer analysis using multiple approaches.

METHODS

The data in this study were derived from sequencing, mutation, and methylation data in the TCGA cohort, normal sample sequencing data in the GTEx project, and cell line expression profile data in the CCLE database.

RESULTS

Survival analyses including the Cox proportional-hazards model and log-rank test revealed the poor prognostic role of NCBP2 in multiple tumors. We further validated the oncogenic ability of NCBP2 in prostate cancer cell lines, organoids and tumor-bearing mice. A negative correlation was observed between NCBP2 expression and immune score by the ESTIMATE algorithm. Simultaneously, the NCBP2-induced immunosuppressive microenvironment might be related to the decline in CD8+T cells and the increase in regulatory T cells and neutrophils, examined by flow cytometry experiments for NCBP2 overexpressed tumor-bearing mice.

CONCLUSION

This research offered strong proof supporting NCBP2 as the prognostic marker and the therapeutic target in the future.

Integrated single cell-RNA sequencing and Mendelian randomization for ischemic stroke and metabolic syndrome

Although more and more evidence has supported that metabolic syndrome (MS) is linked to ischemic stroke (IS), the molecular mechanism and genetic association between them has not been investigated. Here, we combined the existing single-cell RNA sequencing (scRNA-seq) data and mendelian randomization (MR) for stroke to understand the role of dysregulated metabolism in stroke. The shared hub genes were identified with machine learning and WGCNA. A total of six upregulated DEGs and five downregulated genes were selected for subsequent analyses. Nine genes were finally identified with random forest, Lasso regression, and XGBoost method as a potential diagnostic model. scRNA-seq also show the abnormal glycolysis level in most cell clusters in stroke and associated with the expression level of hub genes. The genetic relationship between IS and MS was verified with MR analysis. Our study reveals the common molecular profile and genetic association between ischemic stroke and metabolic syndrome.

P4HA1 expression and function in esophageal squamous cell carcinoma

This study aimed to explore the effect of P4HA1 (prolyl 4-hydroxylase subunit α1) and its ratio on the prognosis of esophageal squamous cell carcinoma. The expression data of P4HA1 in esophageal cancer in The Cancer Genome Atlas and Genotype-Tissue Expression were collected using the public database gene expression profiling interactive analysis. The expression levels of P4HA1 were examined by immunohistochemistry. The relationship between P4HA1 expression and clinicopathological parameters was analyzed the χ2 test. Survival analysis was performed to investigate the effect of P4HA1 and its ratio on prognosis. Compared with normal esophageal mucosal epithelium, there was higher P4HA1 gene mRNA in esophageal cancer tissue. Regarding the expression level, no significant difference was observed in patients with stage I-IV esophageal cancer. Immunohistochemistry showed that P4HA1 was highly expressed in esophageal squamous cell carcinoma (68.7%), while it was negatively expressed in paracancerous tissues. There was a significant difference in expression between cancer and adjacent tissues. The expression of P4HA1 associated with the degree of tumor differentiation, site, lymph node metastasis, and tumor node metastasis stage. The prognostic factors that affected the OS (overall survival) of esophageal cancer patients were the degree of differentiation, lymph node metastasis, and P4HA1 expression. Multivariate analysis of the OS results of patients showed that lymph node metastases and P4HA1 expression were independent prognostic factors that affected the OS of esophageal cancer patients. The prognostic factors affecting the PFS (progression-free survival) of esophageal cancer patients in the univariate survival analysis were as follows: degree of differentiation, lymph node metastasis, and P4HA1 expression. In addition, multivariate analysis of the PFS results of patients showed that lymph node metastasis and P4HA1 expression were independent prognostic factors that affected the PFS of esophageal cancer patients. P4HA1 may be a novel potential biomarker for the early diagnosis, prognosis, and targeted therapy of esophageal cancer.

Proteomic response of A549 lung cancer cell line to protein-polysaccharide complex Venetin-1 isolated from earthworm coelomic fluid

Earthworms' celomic fluid has long attracted scientists' interest due to their toxic properties. It has been shown that the elimination of coelomic fluid cytotoxicity to normal human cells was crucial for the generation of the non-toxic Venetin-1 protein-polysaccharide complex, which exhibits selective activity against Candida albicans cells as well as A549 non-small cell lung cancer cells. To find the molecular mechanisms behind the anti-cancer properties of the preparation, this research investigated the proteome response of A549 cells to the presence of Venetin-1. The sequential window acquisition of all theoretical mass spectra (SWATH-MS) methodology was used for the analysis, which allows for a relative quantitative analysis to be carried out without radiolabelling. The results showed that the formulation did not induce significant proteome responses in normal BEAS-2B cells. In the case of the tumour line, 31 proteins were up regulated, and 18 proteins down regulated. Proteins with increased expression in neoplastic cells are mainly associated with the mitochondrion, membrane transport and the endoplasmic reticulum. In the case of altered proteins, Venetin-1 interferes with proteins that stabilise the structures, i.e., keratin, glycolysis/gluconeogenesis and metabolic processes.

A novel metabolic-related gene signature for predicting clinical prognosis and immune microenvironment in head and neck squamous cell carcinoma

OBJECTIVES

Metabolic reprogramming is not only an essential hallmark in the progression of head and neck squamous cell carcinoma (HNSCC), but also an important regulator of cancer cell adaptation to tumor microenvironment (TME). However, the potential mechanism of metabolic reprogramming in TME of HNSCC is still unknown.

METHODS

The head and neck squamous cell carcinoma with survival information were obtained the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The metabolic-related genes were identified by differential analysis and survival analysis. Univariate and multivariate Cox regression analyses were applied to determine an overall estimate of metabolic-related risk signature and related clinical parameters. The sensitivity and specificity of the risk signature were evaluated by time-dependent receiver operation characteristic (ROC) curves. TME immune cell infiltration mediated by metabolic-related genes was explored by gene set enrichment analysis (GSEA) and correlation analysis.

RESULTS

Seven metabolic-related genes (SMS, MTHFD2, HPRT1, DNMT1, PYGL, ADA, and P4HA1) were identified to develop a metabolic-related risk signature. The low-risk group had a better overall survival compared to that of the high-risk group in the TCGA and GSE65858 cohorts. The AUCs for 1-, 3-, and 5-year overall survival were 0.646 vs. 0.673, 0.694 vs. 0.639, and 0.673 vs. 0.573, respectively. The AUC vale of risk score was 0.727 vs. 0.673. The low-risk group was associated with immune cell infiltration in the TME.

CONCLUSIONS

The metabolic-related risk signature were constructed and validated, which could involve in regulating the immune cell infiltration in the TME and act as an independent biomarker that predicted the prognosis of HNSCC.

A tumor microenvironment-based prognostic index for osteosarcoma

BACKGROUND

The tumor microenvironment (TME) has a central role in the oncogenesis of osteosarcomas. The composition of the TME is essential for the interaction between tumor and immune cells. The aim of this study was to establish a prognostic index (TMEindex) for osteosarcoma based on the TME, from which estimates about patient survival and individual response to immune checkpoint inhibitor (ICI) therapy can be deduced.

METHODS

Based on osteosarcoma samples from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, the ESTIMATE algorithm was used to estimate ImmuneScore and StromalScore. Combined differentially expressed gene analysis, weighted gene co-expression network analyses, the Least Absolute Shrinkage and Selection Operator regression and stepwise regression to construct the TMEindex. The prognostic role of TMEindex was validated in three independent datasets. The molecular and immune characteristics of TMEindex and the impact on immunotherapy were then comprehensively investigated. The expression of TMEindex genes in different cell types and its effects on osteosarcoma cells were explored by scRNA-Seq analysis and molecular biology experiments.

RESULTS

Fundamental is the expression of MYC, P4HA1, RAMP1 and TAC4. Patients with high TMEindex had worse overall survival, recurrence-free survival, and metastasis-free survival. TMEindex is an independent prognostic factor in osteosarcoma. TMEindex genes were mainly expressed in malignant cells. The knockdown of MYC and P4HA1 significantly inhibited the proliferation, invasion and migration of osteosarcoma cells. A high TME index is related to the MYC, mTOR, and DNA replication-related pathways. In contrast, a low TME index is related to immune-related signaling pathways such as the inflammatory response. The TMEindex was negatively correlated with ImmuneScore, StromalScore, immune cell infiltration, and various immune-related signature scores. Patients with a higher TMEindex had an immune-cold TME and higher invasiveness. Patients with a low TME index were more likely to respond to ICI therapy and achieve clinical benefit. In addition, the TME index correlated with response to 29 oncologic drugs.

CONCLUSIONS

The TMEindex is a promising biomarker to predict the prognosis of patients with osteosarcoma and their response to ICI therapy, and to distinguish the molecular and immune characteristics.

Identification and verification of FN1, P4HA1 and CREBBP as potential biomarkers in human atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is a common arrhythmia that can lead to cardiac complications. The mechanisms involved in AF remain elusive. We aimed to explore the potential biomarkers and mechanisms underpinning AF.

METHODS

An independent dataset, GSE2240, was obtained from the Gene Expression Omnibus database. The R package, "limma", was used to screen for differentially expressed genes (DEGs) in individuals with AF and normal sinus rhythm (SR). Weighted gene co-expression network analysis (WGCNA) was applied to cluster DEGs into different modules based on functional disparities. Enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed, and hub genes were identified using cytoHubba. Quantitative reverse-transcription PCR was used to validate mRNA expression in individuals with AF and SR.

RESULTS

We identified 2, 589 DEGs clustered into 10 modules using WGCNA. Gene Ontology analysis showed specific clustered genes significantly enriched in pathways associated with the extracellular matrix and collagen organization. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the target genes were mainly enriched for proteoglycans in cancer, extracellular matrix-receptor interaction, focal adhesion, and the PI3K-Akt signaling pathway. Three hub genes, FN1, P4HA1 and CREBBP, were identified, which were highly correlated with AF endogenesis. mRNA expression of hub genes in patients with AF were higher than in individuals with normal SR, consistent with the results of bioinformatics analysis.

CONCLUSIONS

FN1, P4HA1, and CREBBP may play critical roles in AF. Using bioinformatics, we found that expression of these genes was significantly elevated in patients with AF than in individuals with normal SR. Furthermore, these genes were elevated at core positions in the mRNA interaction network. These genes should be further explored as novel biomarkers and target candidates for AF therapy.

P4HA1, transcriptionally activated by STAT1, promotes esophageal cancer progression

Esophageal cancer (EC) is one of the most frequent cancers with a higher mortality worldwide. Although prolyl 4-hydroxylase alpha polypeptide I (P4HA1) is involved in various human malignancies, the function of P4HA1 in EC remains unclear. The mRNA and protein expressions were assessed by quantitative real-time polymerase chain reaction, western blot and immunohistochemistry. CCK8 assay was used to detect EC cell viability. Cell proliferation was analyzed by colony formation and ethynyl-2'-deoxyuridine assays. In addition, flow cytometry and TdT-mediated dUTP nick-end labeling staining were performed to detect cell apoptosis. Masson's trichrome staining was used to assess the collagen fiber level in tumor tissues. The interaction between STAT1 and P4HA4 was analyzed using ChIP, dual-luciferase reporter gene and Y1H assays. P4HA1 was overexpressed in EC, and its knockdown suppressed EC cell proliferation and collagen synthesis and increased cell apoptosis. Meanwhile, P4HA1 knockdown could repress EC tumor growth in vivo. Our further research displayed that STAT1 promoted P4HA1 expression by interacting with P4HA1 promoter. As expected, P4HA1 overexpression abolished STAT1 knockdown's repression on EC cell malignant behaviors. Our research proved that P4HA1 was transcriptionally activated by STAT1, thereby promoting EC progression.

Comprehensive analysis of roles of atrial-fibrillation-related genes in lung adenocarcinoma using bioinformatic methods

Atrial fibrillation (AF) is the most common tachyarrhythmia in the world. Lung cancer is the leading cause of cancer deaths in 93 countries. Previous studies demonstrated that the prevalence of AF was higher in patients with lung cancer. However, research on the associations between AF and lung cancer is still rare. In the present study, we first identified AF-related genes using weighted gene correlation network analysis. We then analyzed the expression profiles, prognosis, immune infiltration, and methylation characteristics of these genes in LUAD patients using bioinformatics analysis. We found several AF-related genes, including CBX3, BUB1, DSC2, P4HA1, and CYP4Z1, which differently expressed between tumor and normal tissues. Survival analysis demonstrated that CYP4Z1 was positively correlated with overall survival in LUAD patients, while CBX3, BUB1, DSC2, and P4HA1 were negatively correlated. Moreover, we found that the methylation level of DSC2 in normal lung tissues was significantly higher than that in tumor tissues, and six methylation sites in the DNA sequences of DSC2 were identified negatively correlated with its expression levels. Immune infiltration analysis suggested that levels of immune cell infiltration were related to gene expression levels in varying degrees. We identified AF-related genes and found these genes were correlated with prognosis, immune infiltration, and methylation levels in lung cancer patients. We also constructed a risk signature based on these genes in LUAD patients. We hoped that the current study could provide a novel insight into roles of AF-related genes in lung cancer patients.

Construction and Validation of an Oxaliplatin-Resistant Gene Signature in Colorectal Cancer Patients Who Underwent Chemotherapy

Aberrant expression of genes contributes to the chemoresistance of colorectal cancer (CRC) treatment. This study aimed to identify genes associated with the chemoresistance of oxaliplatin-based chemotherapy in CRC patients and to construct a signature. Oxaliplatin resistance-related genes were screened by analyzing the gene profiles of cell lines and tissue samples that underwent oxaliplatin-based treatment. Oxaliplatin resistance-related genes were used to establish a signature. The association of the signature had clinical significance, so the prognostic value of the signature was analyzed. Independent cohorts and CRC cell lines were used to validate the value of the gene signature and the oxaliplatin-resistant genes. There were 64 oxaliplatin resistance-related genes identified after overlapping the genes from the dataset of oxaliplatin-treated CRC cells and the dataset of patients treated with oxaliplatin-based chemotherapy. A gene signature based on five oxaliplatin resistance-related genes was established. This gene signature effectively predicted the prognosis of CRC patients who underwent chemotherapy. No significant associations were found between the gene mutations and survival of the patients; however, two genes were associated with microsatellite instability status. Two external independent cohorts and CRC cell line experiments validated the prognostic values of the signature and expression of the genes after oxaliplatin treatment. In conclusion, the oxaliplatin resistance-related gene signature involving five genes was a novel biomarker for the prediction of the chemotherapy response and prognosis of CRC patients who underwent oxaliplatin-based chemotherapy.

A novel prognostic biomarker CD3G that correlates with the tumor microenvironment in cervical cancer

Cervical cancer (CESC) is the fourth most common and death-causing gynecological cancer, mostly induced by infection of human papillomavirus (HPV). Multiple components of the tumor microenvironment (TME), such as tumor infiltrating immune cells, could be targets of immunotherapy for HPV-related CESC. However, little is known about the TME of CESC until now. Here, we aimed to uncover the pathogenesis as well as to identify novel biomarkers to predict prognosis and immunotherapy efficacy for CESC. Combining the transcriptomic data and clinical characteristics, we identified differentially expressed genes in CESC samples from TCGA database by comparing the two groups with different ImmuneScore and StromalScore. Next, we detected ten key genes based on the PPI network and survival analyses with the univariate Cox regression model. Thereafter, we focused on CD3G, the only gene exhibiting increased RNA and protein expression in tumors by multiple analyses. Higher CD3G expression was associated with better survival; and it was also significantly associated with immune-related pathways through GSEA analysis. Furthermore, we found that CD3G expression was correlated with 16 types of TICs. Single cell RNA-sequencing data of CD3G in lymphocytes subgroup indicated its possible role in HPV defense. Hence, CD3G might be a novel biomarker in prognosis and immunotherapy for CESC patients.