Recent advances in mass spectrometry-based proteomics of gastric cancer

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessment of their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs, protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, and urine diagnostic and prognostic protein biomarker panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing multiple reaction monitoring (MRM) assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on proteins differentially regulated in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessment of GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of MRM assays in a SCIEX QTRAP instrument. Aimed to caterproteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

Clinicopathological correlation of insulin-like growth factor binding protein 3 and their death receptor in patients with gastric cancer

Background and purpose

The insulin-like growth factor binding protein 3 (IGFBP-3) and its novel death receptor (IGFBP-3R) have been exhibited to have tumor suppressor effects. Despite their prognostic value in some cancers, they have not been elucidated in gastric cancer.

Experimental approach

We collected 68 samples from patients with gastric cancer. IGFBP-3 and IGFBP-3R expression levels were evaluated with quantitative real-time polymerase chain reaction (RT-PCR) and western blotting in patients. The relationship between prognostic factors and IGFBP-3/IGFBP-3R expression was also evaluated.

Findings/Results

Our results showed that IGFBP-3 and IGFBP-3R expression was reduced significantly in tumor tissues. We found that there was an association between the reduction of IGFBP-3 with lymph node metastasis and tumor-node-metastasis (TNM) staging. Besides, IGFBP-3R expression was associated with tumor size, lymph node metastasis, differentiation, and TNM classification. Interestingly, we presented that the downregulation of IGFBP-3R was stage-dependent. In survival analysis, our findings showed that low levels of IGFBP-3R mRNA expression exhibited a close correlation with survival rate.

Conclusion and implications

The findings of this study showed that the expression levels of IGFBP-3 and IGFBP-3R are valuable prognostic factors. Despite the potential of IGFBP-3, IGFBP-3R plays a significant role as a prognostic factor in gastric cancer. However, these findings need to be developed and confirmed by further studies.

Identification of plasma proteomic signatures associated with the progression of cardia gastric cancer and precancerous lesions

Objective

Considering that there are no effective biomarkers for the screening of cardia gastric cancer (CGC), we developed a noninvasive diagnostic approach, employing data-independent acquisition (DIA) proteomics to identify candidate protein markers.

Methods

Plasma samples were obtained from 40 subjects, 10 each for CGC, cardia high-grade dysplasia (CHGD), cardia low-grade dysplasia (CLGD), and healthy controls. Proteomic profiles were obtained through liquid chromatography-mass spectrometry (LC-MS/MS-based DIA proteomics. Candidate plasma proteins were identified by weighted gene co-expression network analysis (WGCNA) combined with machine learning and further validated by the Human Protein Atlas (HPA) database. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the biomarker panel.

Results

There was a clear distinction in proteomic features among CGC, CHGD, CLGD, and the healthy controls. According to the WGCNA, we found 42 positively associated and 164 inversely associated proteins related to CGC progression and demonstrated several canonical cancer-associated pathways. Combined with the results from random forests, LASSO regression, and immunohistochemical results from the HPA database, we identified three candidate proteins (GSTP1, CSRP1, and LY6G6F) that could together distinguish CLGD (AUC = 0.91), CHGD (AUC = 0.99) and CGC (AUC = 0.98) from healthy controls with excellent accuracy.

Conclusions

The panel of protein biomarkers showed promising diagnostic potential for CGC and precancerous lesions. Further validation and a larger-scale study are warranted to assess its potential clinical applications, suggesting a potential avenue for CGC prevention in the future.

Mining proteomics data to extract post-translational modifications associated with gastric cancer

Gastric cancers are highly heterogeneous, deep-seated tumours associated with late diagnosis and poor prognosis. Post-translational modifications (PTMs) of proteins are known to be well-associated with oncogenesis and metastasis in most cancers. Several enzymes which drive PTMs have also been used as theranostics in cancers of the breast, ovary, prostate and bladder. However, there is limited data on PTMs in gastric cancers. Considering that experimental protocols for simultaneous analysis of multiple PTMs are being explored, a data-driven approach involving reanalysis of mass spectrometry-derived data is useful in cataloguing altered PTMs. We subjected publicly available mass spectrometry data on gastric cancer to an iterative searching strategy for fetching PTMs including phosphorylation, acetylation, citrullination, methylation and crotonylation. These PTMs were catalogued and further analyzed for their functional enrichment through motif analysis. This value-added approach delivered identification of 21,710 unique modification sites on 16,364 modified peptides. Interestingly, we observed 278 peptides corresponding to 184 proteins to be differentially abundant. Using bioinformatics approaches, we observed that majority of these altered PTMs/proteins belonged to cytoskeletal and extracellular matrix proteins, which are known to be perturbed in gastric cancer. The dataset derived by this mutiPTM investigation can provide leads to further investigate the potential role of altered PTMs in gastric cancer management.

The Human Gastric Juice: A Promising Source for Gastric Cancer Biomarkers

Gastric cancer (GC) is a major public health problem worldwide, with high mortality rates due to late diagnosis and limited treatment options. Biomarker research is essential to improve the early detection of GC. Technological advances and research methodologies have improved diagnostic tools, identifying several potential biomarkers for GC, including microRNA, DNA methylation markers, and protein-based biomarkers. Although most studies have focused on identifying biomarkers in biofluids, the low specificity of these markers has limited their use in clinical practice. This is because many cancers share similar alterations and biomarkers, so obtaining them from the site of disease origin could yield more specific results. As a result, recent research efforts have shifted towards exploring gastric juice (GJ) as an alternative source for biomarker identification. Since GJ is a waste product during a gastroscopic examination, it could provide a "liquid biopsy" enriched with disease-specific biomarkers generated directly at the damaged site. Furthermore, as it contains secretions from the stomach lining, it could reflect changes associated with the developmental stage of GC. This narrative review describes some potential biomarkers for gastric cancer screening identified in gastric juice.

Proteomics analyses of Xiaopi granules in MNNG-induced gastric epithelial dysplasia rat model by LC-MS

OBJECTIVE

Xiaopi granules have been shown to ameliorate gastric epithelial dysplasia in patients. However, the therapeutic mechanism is unclear. Herein, the proteomics method was applied to identify the differentially expressed proteins and related pathways.

METHODS

Sixty male Sprague-Dawley (SD) rats were randomly divided into four groups: control (C group, n=10), model (M group), Xiaopi granules (X group), and vitacoenzyme (V group). The rat gastric epithelial dysplasia model was established by intragastrically administering N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) and ranitidine, and drinking 0.05% ammonia solution. After 12 weeks, the stomach tissue was analyzed by H&E staining and proteomics analyses. Western blot analysis was applied to further validate the proteomics results.

RESULTS

Compared to the M group, levels of 326 and 350 proteins were altered significantly in the X and V groups (1.5-fold, P<0.05), which were significantly enriched in digestion, metabolism, coagulation, and cell apoptosis. CELA2A, GHRL, NDUFB9, and PGC were significantly upregulated (P<0.0001), while CLCA1, PLG, and DAC2 were downregulated (P<0.001 or P<0.0001) in the M group vs. the C group. The change in the above proteins could be reversed after the treatment of Xiaopi granules or vitacoenzyme tablets.

CONCLUSION

Xiaopi granules improve ameliorated gastric epithelial dysplasia by intervening in digestion, metabolism, blood coagulation, cell apoptosis, and other related pathways.

Current Advances and Outlook in Gastric Cancer Chemoresistance: A Review

BACKGROUND

Surgical resection of the lesion is the standard primary treatment of gastric cancer. Unfortunately, most patients are already in the advanced stage of the disease when they are diagnosed with gastric cancer. Alternative therapies, such as radiation therapy and chemotherapy, can achieve only very limited benefits. The emergence of cancer drug resistance has always been the major obstacle to the cure of tumors. The main goal of modern cancer pharmacology is to determine the underlying mechanism of anticancer drugs.

OBJECTIVE

Here, we mainly review the latest research results related to the mechanism of chemotherapy resistance in gastric cancer, the application of natural products in overcoming the chemotherapy resistance of gastric cancer, and the new strategies currently being developed to treat tumors based on immunotherapy and gene therapy.

CONCLUSION

The emergence of cancer drug resistance is the main obstacle in achieving alleviation and final cure for gastric cancer. Mixed therapies are considered to be a possible way to overcome chemoresistance. Natural products are the main resource for discovering new drugs specific for treating chemoresistance, and further research is needed to clarify the mechanism of natural product activity in patients. .

IGHG1 induces EMT in gastric cancer cells by regulating TGF-β/SMAD3 signaling pathway

Objective: Gastric cancer is one of the most common malignant tumors in the world. IGHG1 is a differentially expressed protein screened out in gastric cancer in the early stage of the subject group. This topic explores the expression of IGHG1 in gastric cancer and the effect of IGHG1 on the proliferation, migration, invasion and EMT of gastric cancer SGC7901 cells and its mechanism of action.

Methods: Twenty cases of gastric cancer were purified by laser Capture Microdissection. The isotopic tags for relative and absolute quantification was used to label the proteins, and then analyzed and identified them by quantitative proteomics. Immunohistochemical staining method was used to detect the expression of IGHG1 protein in gastric cancer tissues. Western blot was used to detect the expression of IGHG1 in gastric cancer cells. The MTT and Petri dish clone formation experiment analyzed the effect of low expression of IGHG1 on the proliferation of SGC7901 cells. Scratch test and Transwell migration and invasion test to observe the effect of low expression of IGHG1 on the migration and invasion of SGC7901 cells. Western blot was used to detect the effect of low expression of IGHG1 on the expression of EMT-related proteins.

Results: 243 proteins related to gastric mucosal lesions were preliminarily identified. We found that IGHG1 is highly expressed in gastric cancer tissues compared with normal control tissues. IGHG1 promotes the proliferation, migration and invasion of gastric cancer cells. Compared with the control group, the expression of EMT-related proteins Vimentin, N-cadherin, TGF-β, P-SMAD3 was decreased and the expression of E-cadherin was increased after IGHG1 low expression.

Conclusions: IGHG1 induces EMT in SGC7901 cells by regulating the TGF-β/SMAD3 signaling pathway.

A targeted proteomics approach reveals a serum protein signature as diagnostic biomarker for resectable gastric cancer

BACKGROUND

Gastric cancer (GC) is the third leading cause of cancer death. Early detection is a key factor to reduce its mortality.

METHODS

We retrospectively collected pre- and postoperative serum samples as well as tumour tissues and adjacent normal tissues from 100 GC patients. Serum samples from non-cancerous patients were served as controls (n = 50). A high-throughput protein detection technology, multiplex proximity extension assays (PEA), was applied to measure levels of over 300 proteins. Alteration of each protein was analysed by univariate analysis. Elastic-net logistic regression was performed to select serum proteins into the diagnostic model.

FINDINGS

We identified 19 serum proteins (CEACAM5, CA9, MSLN, CCL20, SCF, TGF-alpha, MMP-1, MMP-10, IGF-1, CDCP1, PPIA, DDAH-1, HMOX-1, FLI1, IL-7, ZBTB-17, APBB1IP, KAZALD-1, and ADAMTS-15) that together distinguish GC cases from controls with a diagnostic sensitivity of 93%, specificity of 100%, and area under receiver operating characteristic curve (AUC) of 0·99 (95% CI: 0·98-1). Moreover, the 19-serum protein signature provided an increased diagnostic capacity in patients at TNM I-II stage (sensitivity 89%, specificity 100%, AUC 0·99) and in patients with high microsatellite instability (MSI) (91%, 98%, and 0·99) compared to individual proteins. These promising results will inspire a large-scale independent cohort study to be pursued for validating the proposed protein signature.

INTERPRETATION

Based on targeted proteomics and elastic-net logistic regression, we identified a 19-serum protein signature which could contribute to clinical GC diagnosis, especially for patients at early stage and those with high MSI. FUND: This study was supported by a European H2020-Marie Skłodowska-Curie Innovative Training Networks grant (316,929, GastricGlycoExplorer). Funder had no influence on trial design, data evaluation, and interpretation.

Identification of Peptide Biomarkers for Discrimination of Shrimp Species through SWATH-MS-Based Proteomics and Chemometrics

Incorrect labeling and adulteration of shrimp occurs due to interspecies similarities and carapace removal during processing. This study attempted to identify three related commercial shrimp species of the order Decapoda: Marsupenaeus japonicus, Fenneropenaeus chinensis, and Litopenaeus vannamei. All measurable trypsin-digested peptides in the individual shrimp were detected using ultrahigh-performance liquid chromatography quadrupole time-of-flight (UPLC-Q-TOF) mass spectrometry with sequential window acquisition of all theoretical fragment ion spectra (SWATH) data-independent acquisition. Further analysis of peptide biomarkers was carried out with an orthogonal partial least-squares discriminant analysis (OPLS-DA) model. BLAST was used for species-specific analysis. Subsequently, multiple reaction monitoring (MRM) methods were developed for sensitivity and selectivity screening of the selected peptides, and 27 were identified as biomarkers allowing rapid and accurate discrimination of shrimp species without high-resolution mass spectrometry or statistical model building. These strategies could be applied in authentication of other products containing highly homologous proteomes.

Quantitative Proteomic Approach Targeted to Fibrinogen β Chain in Tissue Gastric Carcinoma

Elevated plasma fibrinogen levels and tumor progression in patients with gastric cancer (GC) have been largely reported. However, distinct fibrinogen chains and domains have different effects on coagulation, inflammation, and angiogenesis. The aim of this study was to characterize fibrinogen β chain (FGB) in GC tissues. Retrospectively we analyzed the data of matched pairs of normal (N) and malignant tissues (T) of 28 consecutive patients with GC at diagnosis by combining one- and two-dimensional electrophoresis (1DE and 2DE) with immunoblotting and mass spectrometry together with two-dimensional difference in gel electrophoresis (2D-DIGE). 1DE showed bands of the intact FGB at 50 kDa and the cleaved forms containing the fragment D at ~37–40 kDa, which corresponded to 19 spots in 2DE. In particular, spot 402 at ~50 kDa and spots 526 and 548 at ~37 kDa were of interest by showing an increased expression in tumor tissues. A higher content of spot 402 was associated with stomach antrum, while spots 526 and 548 amounts correlated with corpus and high platelet count (>208 × 10⁹/L). The quantification of FGB and cleaved products may help to further characterize the interconnections between GC and platelet/coagulation pathways.

Matrix-Assisted Laser Desorption/Ionisation Mass Spectrometry Imaging in the Study of Gastric Cancer: A Mini Review

Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide and the disease outcome commonly depends upon the tumour stage at the time of diagnosis. However, this cancer can often be asymptomatic during the early stages and remain undetected until the later stages of tumour development, having a significant impact on patient prognosis. However, our comprehension of the mechanisms underlying the development of gastric malignancies is still lacking. For these reasons, the search for new diagnostic and prognostic markers for gastric cancer is an ongoing pursuit. Modern mass spectrometry imaging (MSI) techniques, in particular matrix-assisted laser desorption/ionisation (MALDI), have emerged as a plausible tool in clinical pathology as a whole. More specifically, MALDI-MSI is being increasingly employed in the study of gastric cancer and has already elucidated some important disease checkpoints that may help us to better understand the molecular mechanisms underpinning this aggressive cancer. Here we report the state of the art of MALDI-MSI approaches, ranging from sample preparation to statistical analysis, and provide a complete review of the key findings that have been reported in the literature thus far.

Comparing intestinal versus diffuse gastric cancer using a PEFF-oriented proteomic pipeline

Gastric cancer is the fifth most common malignant neoplasia and the third leading cause of cancer death worldwide. Mac-Cormick et al. recently showed the importance of considering the anatomical region of the tumor in proteomic gastric cancer studies; more differences were found between distinct anatomical regions than when comparing healthy versus diseased tissue. Thus, failing to consider the anatomical region could lead to differential proteins that are not disease specific. With this as motivation, we compared the proteomic profiles of intestinal and diffuse adenocarcinoma from the same anatomical region, the corpus. To achieve this, we used isobaric labeling (iTRAQ) of peptides, a 10-step HILIC fractionation, and reversed-phase nano-chromatography coupled online with a Q-Exactive Plus mass spectrometer. We updated PatternLab to take advantage of the new Comet-PEFF search engine that enables identifying post-translational modifications and mutations included in neXtProt's PSI Extended FASTA Format (PEFF) metadata. Our pipeline then uses a text-mining tool that automatically extracts PubMed IDs from the proteomic result metadata and drills down keywords from manuscripts related with the biological processes at hand. Our results disclose important proteins such as apolipoprotein B-100, S100 and 14-3-3 proteins, among many others, highlighting the different pathways enriched by each cancer type.

SIGNIFICANCE

Gastric cancer is a heterogeneous and multifactorial disease responsible for a significant number of deaths every year. Despite the constant improvement of surgical techniques and multimodal treatments, survival rates are low, mostly due to limited diagnostic techniques and late symptoms. Intestinal and diffuse types of gastric cancer have distinct clinical and pathological characteristics; yet little is known about the molecular mechanisms regulating these two types of gastric tumors. Here we compared the proteomic profile of diffuse and intestinal types of gastric cancer from the same anatomical location, the corpus, from four male patients. This methodological design aimed to eliminate proteomic variations resulting from comparison of tumors from distinct anatomical regions. Our PEFF-tailored proteomic pipeline significantly increased the identifications as when compared to previous versions of PatternLab.

[Analysis of contribution of protein phosphorylation in the development of the diseases]

In recent decades, studies in the molecular origins of socially significant diseases have made a big step forward with the development and using of high-performance methods in genomics and proteomics. Numerous studies in the framework of the global program "Human Proteome" were aimed at the identification of all possible proteins in various cell cultures and tissues, including cancer. One of the objectives was to identify biomarkers - proteins with high specificity to certain pathologies. However, in many cases, it is shown that the development of the disease is not associated with the appearance of new proteins, but depends on the level of gene expression or forming of proteoforms - splice variants, single amino acid substitutions (SAP variants), and post-translational modifications (PTM) of proteins. PTM may play a key role in the development of pathology because they activate a variety of regulatory or structural proteins in the majority of cell physiological processes. Phosphorylation is among the most significant of these protein modifications.This review will describe methods for analysis of protein phosphorylation used in the studies of such diseases as cancer and neurodegenerative diseases, as well as examples of cases when the modified proteins are involved directly to their development, and screening such significant PTM is used for the diagnosis and choice of treatment.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Introducing crucial protein panel of gastric adenocarcinoma disease

AIM

Since interactome analysis of diseases can provide candidate biomarker panel related to the diseases, in this research, protein-protein interaction (PPI) network analysis is used to introduce the involved crucial proteins in Gastric adenocarcinoma (GA).

BACKGROUND

Gastric adenocarcinoma (GA) is the most common type of stomach cancer. There is no efficient diagnostic molecular method for GA.

METHOD

Applying Cytoscape software 3.4.0 and String Database, the PPI network was constructed for 200 genes. Based on centrality parameters, the critical nodes were screened. Gene ontology of the key proteins for pathway analysis and molecular function processing were done and the highlighted pathways and activities were discussed.

RESULTS

Among 200 initial genes, 141 genes were included in a main connected network. Seven crucial proteins, including tumor protein p53, epidermal growth factor receptor, albumin, v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian), v-akt murine thymoma viral oncogene homolog 1, v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) and catenin (cadherin-associated protein), beta 1, 88kDa, and Myogenic differentiation 1, were introduced as key nodes of the network. These identified proteins are mostly involved in pathways and activities related to cancer.

CONCLUSION

In conclusion, the finding is corresponding to the significant roles of these introduced proteins in GA disease. This protein panel may be a useful probe in the management of GA.