Helicobacter pylori immunoproteomics in gastric cancer and gastritis of the carcinoma phenotype

Development and validation of a risk prognostic model based on the H. pylori infection phenotype for stomach adenocarcinoma

Background

Stomach adenocarcinoma (STAD) is one of the most common malignancies. Infection of helicobacter pylori (H. pylori) is a major risk factor that leads to the development of STAD. This study constructed a risk model based on the H. pylori-related macrophages for predicting STAD prognosis.

Methods

The single-cell RNA sequencing (scRNA-seq) dataset and the clinic information and RNA-seq datasets of STAD patients were collected for establishing a prognostic model and for validation. The "Seurat" and "harmony" packages were used to process the scRNA-seq data. Key gene modules were sectioned using the "limma" package and the "WGCNA" package. Kaplan-Meier (KM) and Receiver Operating Characteristic Curve (ROC) analyses were performed with "survminer" package. The "GSVA" package was employed for single sample gene set enrichment analysis (ssGSEA). Cell migration and invasion were measured by carrying out wound healing and trans-well assays.

Results

A total of 17397 were screened and classified into 8 cell type clusters, among which the macrophage cluster was closely associated with the H. pylori infection. Macrophages were further categorized into four subtypes (including C1, C2, C3, and C4), and highly variable genes of macrophage subtype C4 could serve as an indicator of the prognosis of STAD. Subsequently, we developed a RiskScore model based on six H. pylori -associated genes (TNFRSF1B, CTLA4, ABCA1, IKBIP, AKAP5, and NPC2) and observed that the high-risk patients exhibited poor prognosis, higher suppressive immune infiltration, and were closely associated with cancer activation-related pathways. Furthermore, a nomogram combining the RiskScore was developed to accurately predict the survival of STAD patients. AB CA 1 in the RiskScore model significantly affected the migration and invasion of tumor cells.

Conclusion

The gene expression profile served as an indicator of the survival for patients with STAD and addressed the clinical significance of using H. pylori-associated genes to treat STAD. The current findings provided novel understandings for the clinical evaluation and management of STAD.

Application of proteomics to the study of Helicobacter pylori and implications for the clinic

INTRODUCTION

Helicobacter pylori (H. pylori) is a gram-negative bacterium that colonizes the gastric epithelium and mucous layer of more than half the world's population. H. pylori is a primary human pathogen, responsible for the development of chronic gastritis, peptic ulceration and gastric cancer. Proteomics is impacting several aspects of medical research: understanding the molecular basis of infection and disease manifestation, identification of therapeutic targets and discovery of clinically relevant biomarkers. Areas covered: The main aim of the present review is to provide a comprehensive overview of the contribution of proteomics to the study of H. pylori infection pathophysiology. In particular, we focused on the role of the bacterium and its most important virulence factor, CagA, in the progression of gastric cells transformation and cancer progression. We also discussed the proteomic approaches aimed at the investigation of the host response to bacterial infection. Expert commentary: In the field of proteomics of H. pylori, comprehensive analysis of clinically relevant proteins (functional proteomics) rather than entire proteomes will result in important medical outcomes. Finally, we provided an outlook on the potential development of proteomics in H. pylori research.

Helicobacter pylori Infection Increases Frequency of PDCA-1(+) (CD317(+)) B-cell Subsets

BACKGROUND AND AIMS

As a newly discovered B-cell subset, PDCA-1(+) B cells have been shown to participate in the immune clearance of invading pathogens. The prominence of PDCA-1(+) B cell immunity in the pathogenesis of Helicobacter pylori infection prompted us to explore the potential role of this subset in gastric H. pylori infection.

METHODS

H. pylori infection was determined by (14)C-urea breath test and Western blot. The frequency of the different sub-compartments of PDCA-1(+) B cells and their relation to serum cytokines was determined in 33 H. pylori-infected and 14 uninfected patients and in 12 healthy controls (HC).

RESULTS

In comparison to uninfected individuals, there was a significantly increased frequency of PDCA-1(+) B cells, PDCA-1(+)IgM(+) B cells, CD93(+)PDCA-1(+) B cells, CD93(+)PDCA-1(+)IgM(+) B cells, CD137(+)PDCA-1(+) B cells and CD137(+)PDCA-1(+)IgM(+) B cells were detected in patients with H. pylori infection, corresponding to increased levels of serum IFN-α and IgM in this group. Compared with H. pylori-positive (HP(+)) chronic non-atrophic gastritis patients, a larger proportion of PDCA-1(+) B cells, CD93(+)PDCA-1(+) B cells and CD137(+)PDCA-1(+) B cells were observed in HP(+) patients suffering from atrophic gastritis or HP(+) peptic ulcers.

CONCLUSIONS

The frequency of the PDCA-1(+) B cell compartment is increased during H. pylori infection. Our data support the potential role of this B-cell subset in the pathogenesis of H. pylori-dependent gastritis.

Serum antibody against Helicobacter pylori FlaA and risk of gastric cancer

BACKGROUND

Helicobacter pylori (H. pylori) infection is a major risk factor for gastric cancer (GC); however, only a minority of infected individuals develops GC. We aim to assess the association between serostatus of antibody against H. pylori flagellin A (FlaA) and risk of GC and to evaluate the value of serum FlaA antibody as a novel screening biomarker for GC risk.

METHODS

A hospital-based case-control study including 232 cases and 264 controls was conducted. Logistic regression was adopted to analyze the association between the serostatus of FlaA antibody and risk of GC. Serum FlaA antibody was measured by an enzyme-linked immunosorbent assay (ELISA). Receiver operating characteristic (ROC) curve was used to evaluate the screening efficacy and to identify a cutoff point of serum FlaA antibody level.

RESULTS

Helicobacter pylori infection was associated with an increased risk of GC (p = .007). A positive association between serum FlaA antibody and GC risk was observed in overall subjects and H. pylori-positive subjects (OR [95% CI]: 6.8 [4.3-10.7] and 6.9 [3.6-13.4], respectively; p < .001). The seropositivity of FlaA antibody was strongly related to GC risk in a dose-dependent manner (p for trend < .001). The optimal cutoff value (OD) was 0.1403, providing a sensitivity of 74.1% and a specificity of 64.4%. The area under the ROC curve (AUC) was 0.74 in overall subjects and 0.73 in H. pylori-positive subjects, respectively.

CONCLUSIONS

FlaA was an independent risk factor for H. pylori-related GC. Serum FlaA antibody may serve as a novel noninvasive biomarker for early detection of GC.

Exoproteomics: exploring the world around biological systems

The term 'exoproteome' describes the protein content that can be found in the extracellular proximity of a given biological system. These proteins arise from cellular secretion, other protein export mechanisms or cell lysis, but only the most stable proteins in this environment will remain in abundance. It has been shown that these proteins reflect the physiological state of the cells in a given condition and are indicators of how living systems interact with their environments. High-throughput proteomic approaches based on a shotgun strategy, and high-resolution mass spectrometers, have modified the authors' view of exoproteomes. In the present review, the authors describe how these new approaches should be exploited to obtain the maximum useful information from a sample, whatever its origin. The methodologies used for studying secretion from model cell lines derived from eukaryotic, multicellular organisms, virulence determinants of pathogens and environmental bacteria and their relationships with their habitats are illustrated with several examples. The implication of such data, in terms of proteogenomics and the discovery of novel protein functions, is discussed.

Identification of new protein coding sequences and signal peptidase cleavage sites of Helicobacter pylori strain 26695 by proteogenomics

Correct annotation of protein coding genes is the basis of conventional data analysis in proteomic studies. Nevertheless, most protein sequence databases almost exclusively rely on gene finding software and inevitably also miss protein annotations or possess errors. Proteogenomics tries to overcome these issues by matching MS data directly against a genome sequence database. Here we report an in-depth proteogenomics study of Helicobacter pylori strain 26695. MS data was searched against a combined database of the NCBI annotations and a six-frame translation of the genome. Database searches with Mascot and X! Tandem revealed 1115 proteins identified by at least two peptides with a peptide false discovery rate below 1%. This represents 71% of the predicted proteome. So far this is the most extensive proteome study of Helicobacter pylori. Our proteogenomic approach unambiguously identified four previously missed annotations and furthermore allowed us to correct sequences of six annotated proteins. Since secreted proteins are often involved in pathogenic processes we further investigated signal peptidase cleavage sites. By applying a database search that accommodates the identification of semi-specific cleaved peptides, 63 previously unknown signal peptides were detected. The motif LXA showed to be the predominant recognition sequence for signal peptidases.

BIOLOGICAL SIGNIFICANCE

The results of MS-based proteomic studies highly rely on correct annotation of protein coding genes which is the basis of conventional data analysis. However, the annotation of protein coding sequences in genomic data is usually based on gene finding software. These tools are limited in their prediction accuracy such as the problematic determination of exact gene boundaries. Thus, protein databases own partly erroneous or incomplete sequences. Additionally, some protein sequences might also be missing in the databases. Proteogenomics, a combination of proteomic and genomic data analyses, is well suited to detect previously not annotated proteins and to correct erroneous sequences. For this purpose, the existing database of the investigated species is typically supplemented with a six-frame translation of the genome. Here, we studied the proteome of the major human pathogen Helicobacter pylori that is responsible for many gastric diseases such as duodenal ulcers and gastric cancer. Our in-depth proteomic study highly reliably identified 1115 proteins (FDR<0.01%) by at least two peptides (FDR<1%) which represent 71% of the predicted proteome deposited at NCBI. The proteogenomic data analysis of our data set resulted in the unambiguous identification of four previously missed annotations, the correction of six annotated proteins as well as the detection of 63 previously unknown signal peptides. We have annotated proteins of particular biological interest like the ferrous iron transport protein A, the coiled-coil-rich protein HP0058 and the lipopolysaccharide biosynthesis protein HP0619. For instance, the protein HP0619 could be a drug target for the inhibition of the LPS synthesis pathway. Furthermore it has been proven that the motif "LXA" is the predominant recognition sequence for the signal peptidase I of H. pylori. Signal peptidases are essential enzymes for the viability of bacterial cells and are involved in pathogenesis. Therefore signal peptidases could be novel targets for antibiotics. The inclusion of the corrected and new annotated proteins as well as the information of signal peptide cleavage sites will help in the study of biological pathways involved in pathogenesis or drug response of H. pylori.

Immunoproteomics: current technology and applications

The varied landscape of the adaptive immune response is determined by the peptides presented by immune cells, derived from viral or microbial pathogens or cancerous cells. The study of immune biomarkers or antigens is not new and classical methods such as agglutination, enzyme-linked immunosorbent assay, or Western blotting have been used for many years to study the immune response to vaccination or disease. However, in many of these traditional techniques, protein or peptide identification has often been the bottleneck. Recent advances in genomics and proteomics, has led to many of the rapid advances in proteomics approaches. Immunoproteomics describes a rapidly growing collection of approaches that have the common goal of identifying and measuring antigenic peptides or proteins. This includes gel based, array based, mass spectrometry, DNA based, or in silico approaches. Immunoproteomics is yielding an understanding of disease and disease progression, vaccine candidates, and biomarkers. This review gives an overview of immunoproteomics and closely related technologies that are used to define the full set of antigens targeted by the immune system during disease.

Role of Th17 and IL-17 in Helicobacter pylori-related gastric carcinogenesis

T helper 17 (Th17) cells are a newly defined subset of CD4⁺ effecter T cells characterized by the secretion of interleukin 17 (IL-17) and transcription factor RORγ. They play significant roles in the pathogenesis of various tumors and bacterial infectious diseases. Gastric carcinoma is closely related to Helicobacter pylori (H. pylori) infection and has a very high mortality. Evidence shows that both Th17 and IL-17 play critical roles in the pathogenesis of H. pylori-associated gastric carcinoma and precancerous lesions. Elucidation of the roles of Th17 and IL-17 in H. pylori-related gastric carcinogenesis will provide new clues to the early diagnosis, personalized prevention and immunotherapy, vaccination and prognostic evaluation of gastric carcinoma.

Antigenic diversity among Portuguese clinical isolates of Helicobacter pylori

BACKGROUND

 The human gastroduodenal pathogen, Helicobacter pylori, is characterized by an unusual extent of genetic heterogeneity. This dictates differences in the antigenic pattern of strains resulting in heterogeneous human humoral immune responses. Here, we examined the antigenic variability among a group of 10 strains isolated from Portuguese patients differing in age, gender, and H. pylori-associated gastric diseases.

MATERIAL AND METHODS

 Immunoassays were performed on two-dimensional electrophoresis gels obtained for the proteome of each strain, using a commercial pool of antibodies produced in rabbit, against the whole cell lysate of an Australian H. pylori strain. Relevant proteins were identified by mass spectrometry.

RESULTS

Immunoproteomes of the Portuguese strains showed no correlation between the number of antigenic proteins or the antigenic profile, and the disease to which each strain was associated. The Heat shock protein B was the unique immunoreactive protein common to all of them. Additionally, seven proteins were found to be antigenic in at least 80% of strains: enoyl-(acyl-carrier-protein) reductase (NADH); Catalase; Flagellin A; 2 isoforms of alkyl hydroperoxide reductase; succinyl-CoA transferase subunit B; and an unidentified protein. These proteins were present in the proteome of all tested strains, suggesting that differences in their antigenicity are related to antigenic variance.

CONCLUSIONS

 This study showed evidence of the variability of antigenic pattern among H. pylori strains. We believe that this fact contributes to the failure of anti-H. pylori vaccines and the low accuracy of serological tests based on a low number of proteins or antigens of only one strain.