Potentially functional variants of ERAP1, PSMF1 and NCF2 in the MHC-I-related pathway predict non-small cell lung cancer survival

A signature of four ferroptosis-related genes in laryngeal squamous cell carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) prognosis has not improved significantly in the past few decades, and more effective treatments are needed to be explored. Ferroptosis is a newly discovered kind of regulated cell death in recent years, which is related to tumor immunity and can used to treat tumors. Therefore, the prognostic value of ferroptosis-related genes in laryngeal cancer needs further clarification.

Methods

In this study, the mRNA expression profile data of LSCC were downloaded from the public database. After identifying ferroptosis-related differentially expressed genes (FDGs), we explored the role of these genes through functional enrichment analysis. FDGs with prognostic significance were identified by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. By calculating the risk score, we constructed a prognostic model. Kaplan-Meier (K-M) analysis, the receiver operating characteristic (ROC) curves, and the nomogram were utilized to investigate this model. Public databases and quantitative real-time polymerase chain reaction (qRT-PCR) were performed to verify the expression of model genes.

Results

The model consisting of four FDGs was acknowledged to be a self-determining predictor of prognosis. The K-M survival curves and the ROC curves confirmed the model's predictive ability. The C index (0.805) indicates that the nomogram has a good predictive ability. In vitro studies have confirmed the differential expression of the four FDGs.

Conclusions

We identified a novel ferroptosis-related gene signature for predicting prognosis in LSCC.

Targeted serum proteome profiling reveals nicotinamide adenine dinucleotide phosphate (NADPH)-related biomarkers to discriminate linear IgA bullous disorder from dermatitis herpetiformis

Linear IgA bullous dermatosis (LABD) and dermatitis herpetiformis (DH) represent the major subtypes of IgA mediated autoimmune bullous disorders. We sought to understand the disease etiology by using serum proteomics. We assessed 92 organ damage biomarkers in LAB, DH, and healthy controls using the Olink high-throughput proteomics. The positive proteomic serum biomarkers were used to correlate with clinical features and HLA type. Targeted proteomic analysis of IgA deposition bullous disorders vs. controls showed elevated biomarkers. Further clustering and enrichment analyses identified distinct clusters between LABD and DH, highlighting the involvement of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase. Comparative analysis revealed biomarkers with distinction between LABD and DH and validated in the skin lesion. Finally, qualitative correlation analysis with DEPs suggested six biomarkers (NBN, NCF2, CAPG, FES, BID, and PXN) have better prognosis in DH patients. These findings provide potential biomarkers to differentiate the disease subtype of IgA deposition bullous disease.

Novel biomarkers related to oxidative stress and immunity in chronic kidney disease

Introduction

The incidence of chronic kidney disease (CKD) has been increasing in recent years, gradually becoming a global health crisis. Due to limited treatment options, novel molecular pathways are urgently required to advance the treatment and diagnosis of CKD.

Materials and methods

The characteristics of differentially expressed genes (DEGs) in CKD patients were analyzed using Gene Expression Omnibus (GEO) database, and genes related to oxidative stress were retrieved from the Genecard database. Subsequently, a comprehensive approach was applied, including immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis, to identify hub genes among differentially expressed immune-related oxidative stress genes (DEIOSGs). Validation of hub genes was performed using an external data set, and diagnostic potential capability was evaluated through receiver operating curve (ROC) analysis. In animal experiments, the expression of hub genes in CKD was confirmed by inducing a CKD model through a 5/6 nephrectomy procedure. Finally, the relationship between these hub genes and clinical characteristics were assessed using the Nephroseq v5 database.

Results

29 DEIOSGs were identified by comprehensive bioinformatics analysis. PPI analysis screened the hub genes NCF2, S100A9, and SELL. ROC analysis demonstrated excellent diagnostic efficacy. Further validation from other databases and animal experiments confirmed a substantial upregulation in the expression of hub genes in CKD. Additionally, clinical correlation analysis established a clear link between hub gene expression and renal function deterioration.

Conclusions

Our study confirms NCF2, S100A9, and SELL as diagnostic biomarkers associated with immune response and oxidative stress in CKD, suggesting their potential as novel targets for CKD diagnosis and treatment.

A genetic variant in the immune-related gene ERAP1 affects colorectal cancer prognosis

BACKGROUND

Findings on the association of genetic factors and colorectal cancer (CRC) survival are limited and inconsistent, and revealing the mechanism underlying their prognostic roles is of great importance. This study aimed to explore the relationship between functional genetic variations and the prognosis of CRC and further reveal the possible mechanism.

METHODS

We first systematically performed expression quantitative trait locus (eQTL) analysis using The Cancer Genome Atlas (TCGA) dataset. Then, the Kaplan-Meier analysis was used to filter out the survival-related eQTL target genes of CRC patients in two public datasets (TCGA and GSE39582 dataset from the Gene Expression Omnibus database). The seven most potentially functional eQTL single nucleotide polymorphisms (SNPs) associated with six survival-related eQTL target genes were genotyped in 907 Chinese CRC patients with clinical prognosis data. The regulatory mechanism of the survival-related SNP was further confirmed by functional experiments.

RESULTS

The rs71630754 regulating the expression of endoplasmic reticulum aminopeptidase 1 ( ERAP1 ) was significantly associated with the prognosis of CRC (additive model, hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.08-1.88, P = 0.012). The results of dual-luciferase reporter assay and electrophoretic mobility shift assay showed that the A allele of the rs71630754 could increase the binding of transcription factor 3 (TCF3) and subsequently reduce the expression of ERAP1 . The results of bioinformatic analysis showed that lower expression of ERAP1 could affect the tumor immune microenvironment and was significantly associated with severe survival outcomes.

CONCLUSION

The rs71630754 could influence the prognosis of CRC patients by regulating the expression of the immune-related gene ERAP1 .

TRIAL REGISTRATION

No. NCT00454519 ( https://clinicaltrials.gov/ ).

Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes

OBJECTIVES

The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD).

MATERIALS AND METHODS

With The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we used Cox regression analysis to construct a prognostic model, and verified independence of riskscore. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves. Immune analysis was performed by using ssGSEA. Additionally, immune checkpoint blockade therapy was assessed by using immunophenoscore, Tumor Immune Dysfunction and Exclusion score. Based on the cMAP database, effective small molecule compounds were predicted.

RESULTS

A prognostic model was established based on 8 MHC-I-related genes, and the predictive capacity of the model was accurate. Immune analysis results revealed that patients classified as high-risk had lower levels of immune cell infiltration and impaired immune function. The low-risk group possessed a better response to immune checkpoint blockade therapy. Theobromine and pravastatin were identified as having great potential in improving the prognosis of LUAD.

CONCLUSION

Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response.

Down-regulation of ERAP1 mRNA expression in non-small cell lung cancer

BACKGROUND

ERAP1 is a major aminopeptidase that serves as an editor of the peptide repertoire by trimming N-terminal residues of antigenic peptides, creating a pool of peptides with the optimal length for MHC-I binding. As an important component of the antigen processing and presenting machinery - APM, ERAP1 is frequently down-regulated in many cancers. Since ERAP1 expression has not yet been thoroughly investigated in non-small cell lung cancer (NSCLC), we decided to analyze ERAP1 mRNA levels in tissues collected from NSCLC patients.

METHODS

Using real-time qPCR, we evaluated ERAP1 mRNA expression in samples of tumor and adjacent non-tumor tissue (serving as control tissue) from 61 NSCLC patients.

RESULTS

We observed a significantly lower level of ERAP1 mRNA expression in tumor tissue (Med_Tumor = 0.75) in comparison to non-tumor tissue (Med_Non-tumor = 1.1), p = 0.008. One of the five tested polymorphisms, namely rs26653, turned out to be significantly associated with ERAP1 expression in non-tumor tissue (difference [d] = 0.59 CI95% (0.14;1.05), p = 0.0086), but not in tumor tissue. The levels of ERAP1 mRNA expression did not affect the overall survival of NSCLC patients, either in the case of the tumor (p = 0.788) or in non-tumor (p = 0.298) tissue. We did not detect any association between mRNA ERAP1 expression level in normal tissue and: (i) age at diagnosis (p = 0.8386), (ii) patient's sex (p = 0.3616), (iii) histological type of cancer (p = 0.7580) and (iv) clinical stage of NSCLC (p = 0.7549). Furthermore, in the case of tumor tissue none of the abovementioned clinical parameters were associated with ERAP1 expression (p = 0.76).

CONCLUSION

Down-regulation of ERAP1 mRNA observed in NSCLC tissue may be related to tumor immune evasion strategy. The rs26653 polymorphism can be considered an expression quantitative trait locus (eQTL) associated with ERAP1 expression in normal lung tissue.

Role of NCF2 as a potential prognostic factor and immune infiltration indicator in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the major causes of cancer-related deaths globally. The tumor microenvironment (TME) plays a crucial role in the prognosis and treatment of HCC. Hence, it is important to exploit new biomarkers for survival surveillance and TME estimation of HCC.

METHODS

HCC samples data was collected from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database, and clinical samples were collected from our center. The TME of HCC were explored with ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data), ssGSEA (single sample Gene Sets Enrichment Analysis) and CIBERSORT algorithm. Differentially expressed genes were analyzed with functional enrichment analysis. Immunohistochemistry was implemented to validate the results.

RESULTS

Based on TCGA database, we found that Neutrophil Cytosolic Factor 2 (NCF2) was significantly associated with the prognosis of HCC patients, involved in immune-related biological processes of HCC and closely associated with some types of immunocompetent cells. The survival analysis based on NCF2 expression assessed by immunohistochemistry also confirmed that NCF2-positive group had a shorter relapse free survival (RFS) and overall survival (OS) than NCF2-negative group. Multivariate Cox regression revealed NCF2 expression level and lymphovascular space invasion (LVSI) were independent risk factors for HCC patients. Receiver operating characteristic curves showed that the combination of NCF2 and LVSI had higher predictive efficacy on the 1-year RFS rate and 5-year OS rate than each of them alone. Besides, the expression level of NCF2 was positively associated with M0 and M2 macrophages infiltration. Furthermore, NCF2 expression was positively correlated with CSF1, IL4, IL10, CD206, CD163, CSF1R and TGFβ1.

CONCLUSION

We proposed that higher NCF2 expression predicted an adverse prognosis and more M2 macrophages infiltration in HCC patients.

A trans-omics assessment of gene-gene interaction in early-stage NSCLC

Epigenome-wide gene-gene (G × G) interactions associated with non-small-cell lung cancer (NSCLC) survival may provide insights into molecular mechanisms and therapeutic targets. Hence, we proposed a three-step analytic strategy to identify significant and robust G × G interactions that are relevant to NSCLC survival. In the first step, among 49 billion pairs of DNA methylation probes, we identified 175 775 G × G interactions with P_Bonferroni  ≤ 0.05 in the discovery phase of epigenomic analysis; among them, 15 534 were confirmed with P ≤ 0.05 in the validation phase. In the second step, we further performed a functional validation for these G × G interactions at the gene expression level by way of a two-phase (discovery and validation) transcriptomic analysis, and confirmed 25 significant G × G interactions enriched in the 6p21.33 and 6p22.1 regions. In the third step, we identified two G × G interactions using the trans-omics analysis, which had significant (P ≤ 0.05) epigenetic cis-regulation of transcription and robust G × G interactions at both the epigenetic and transcriptional levels. These interactions were cg14391855 × cg23937960 (β_interaction  = 0.018, P = 1.87 × 10^-12 ), which mapped to RELA × HLA-G (β_interaction  = 0.218, P = 8.82 × 10^-11 ) and cg08872738 × cg27077312 (β_interaction  = -0.010, P = 1.16 × 10^-11 ), which mapped to TUBA1B × TOMM40 (β_interaction =-0.250, P = 3.83 × 10^-10 ). A trans-omics mediation analysis revealed that 20.3% of epigenetic effects on NSCLC survival were significantly (P = 0.034) mediated through transcriptional expression. These statistically significant trans-omics G × G interactions can also discriminate patients with high risk of mortality. In summary, we identified two G × G interactions at both the epigenetic and transcriptional levels, and our findings may provide potential clues for precision treatment of NSCLC.

Prognostic Ability of Enhancer RNAs in Metastasis of Non-Small Cell Lung Cancer

(1) Background: Non-small cell lung cancer (NSCLC) is the most common lung cancer. Enhancer RNA (eRNA) has potential utility in the diagnosis, prognosis and treatment of cancer, but the role of eRNAs in NSCLC metastasis is not clear; (2) Methods: Differentially expressed transcription factors (DETFs), enhancer RNAs (DEEs), and target genes (DETGs) between primary NSCLC and metastatic NSCLC were identified. Prognostic DEEs (PDEEs) were screened by Cox regression analyses and a predicting model for metastatic NSCLC was constructed. We identified DEE interactions with DETFs, DETGs, reverse phase protein arrays (RPPA) protein chips, immunocytes, and pathways to construct a regulation network using Pearson correlation. Finally, the mechanisms and clinical significance were explained using multi-dimensional validation unambiguously; (3) Results: A total of 255 DEEs were identified, and 24 PDEEs were selected into the multivariate Cox regression model (AUC = 0.699). Additionally, the NSCLC metastasis-specific regulation network was constructed, and six key PDEEs were defined (ANXA8L1, CASTOR2, CYP4B1, GTF2H2C, PSMF1 and TNS4); (4) Conclusions: This study focused on the exploration of the prognostic value of eRNAs in the metastasis of NSCLC. Finally, six eRNAs were identified as potential markers for the prediction of metastasis of NSCLC.