Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

DKK3 and SERPINB5 as novel serum biomarkers for gastric cancer: facilitating the development of risk prediction models for gastric cancer

The existing gastric cancer (GC) risk prediction models based on biomarkers are limited. This study aims to identify new promising biomarkers for GC to develop a risk prediction model for effective assessment, screening, and early diagnosis. This study was conducted utilizing a large combined cohort for upper gastrointestinal cancer that was established in Hebei Province, China. General macro risk factors, Helicobacter pylori (H.pylori) infection status, and protein biomarkers were collected through questionnaire surveys and laboratory tests. Novel GC biomarkers were explored using data-independent acquisition (DIA) proteomics and enzyme-linked immunosorbent assay (ELISA). Multiple machine learning algorithms were used to identify key predictors for the GC risk prediction model, which was validated with an independent external cohort from multiple hospitals. A total of 530 participants aged 40 to 74 were analyzed, with 104 ultimately diagnosed with GC. Significant biomarkers in GC patients were identified by DIA combined ELISA, including elevated Keratin 7 (KRT7) and Mammary fibrostatin (SERPINB5) (P<0.001) and decreased Dickkopf-associated protein 3 (DKK3) (P<0.001). Factors such as sex, age, smoking status, alcohol consumption, family history of GC, H. pylori infection, DKK3 and SERPINB5 were used to create a multidimensional risk prediction model for GC. This model achieved an area under the curve (AUC) of 0.938 (95% confidence interval: 0.913-0.962). The risk prediction model developed in this study shows high accuracy and practical utility, serving as an effective preliminary screening tool for identifying high-risk individuals for GC.

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.

The prognostic role of fatty acid metabolism-related genes in patients with gastric cancer

BACKGROUND

With the deepening research on fatty acid metabolism, people have achieved a preliminary understanding of it in the development and prognosis of tumors. However, few studies are still on the expression pattern and prognostic value of fatty acid metabolism-related genes in gastric cancer (GC).

METHODS

We chose 93 genes relevant to fatty acid metabolism from the Gene Set Enrichment Analysis (GSEA) database. We analyzed differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA) patients. Univariate Cox analysis and LASSO regression were used to select the genes most related to prognosis and therefore developed a prognosis model. In addition, a dataset of 76 samples from Gene Expression Omnibus (GEO) selected as a test set to aid in the development of a prognostic model. The prognostic relevance of this model was confirmed using Kaplan-Meier survival analysis, univariate/multivariate Cox analysis, and receiver operating characteristic (ROC) curve. Finally, enrichment analysis and protein-protein interaction (PPI) were used to analyze the functional differences of patients with different risk. Immune infiltration analysis based on CIBERSORT could check the infiltration degree and immune function changes of immune cell subtypes in patients with different risk groups.

RESULTS

Overexpression of ELOVL4, ADH4, CPT1C, and ADH1B was linked to poor overall survival (OS) in GC patients, according to our findings. Furthermore, according to prognostic factors, patients with lower risk score tend to have better prognosis than patients with higher risk score. In addition, we also found that the infiltration levels of B cells, dendritic cells, auxiliary T cells, mast cells, neutrophils and tumor-infiltrating lymphocytes in patients with high-risk group were significantly increased, and the type II IFN response of immune cells, CCR and MHC class I receptor functions were significantly enhanced, suggesting that the tumor microenvironment immune activity in patients with high-risk group was active.

CONCLUSIONS

Four fatty acid metabolism-related genes were discovered to be closely connected to the prognosis of individuals with GC. Through analysis and verification, we believed that this prognostic model was reliable and instructive in the prediction of the prognosis of GC.

Circulating exosomal gastric cancer-associated long noncoding RNA1 as a noninvasive biomarker for predicting chemotherapy response and prognosis of advanced gastric cancer: A multi-cohort, multi-phase study

Background

A previous validated study has identified the diagnostic value of circulating exosomal lncRNA-GC1 for detecting and monitoring gastric cancer. We aimed to further determine the predictive role of circulating exosomal lncRNA-GC1 for prognosis and chemotherapy response.

Methods

We retrospectively conducted a multi-phase analysis with four independent cohorts of 981 patients. A training cohort was used to generate the predictive model. One internal and two external cohorts were recruited as validation cohorts. Patients with stage II or III gastric cancer in the combined cohort were used to evaluate the predictive value of circulating exosomal lncRNA-GC1 for chemotherapy response.

Findings

In the training cohort, circulating exosomal lncRNA-GC1 was identified as an independent prognostic predictor for disease-free and overall survival. A prognostic risk stratification model based on circulating exosomal lncRNA-GC1 and AJCC stage revealed better predictive accuracy for disease-free and overall survival than the traditional AJCC stage system alone (C-index: DFS 0.701 vs 0.614; OS 0.720 vs 0.611, both P<0.05). And it has been further verified in the validation cohorts. In interaction analysis, for stage II and III GC, patients with low-level of circulating exosomal lncRNA-GC1 derived more survival benefit from adjuvant chemotherapy (P < 0.05); while those with high-level did not.

Interpretation

Measurement of circulating exosomal lncRNA-GC1 provides clinically important prognostic information and could complement the AJCC stage to optimize decision-making for selecting patients who could benefit more from fluorouracil-based chemotherapy after surgery.

Funding

The funders are listed in the Acknowledgement.

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.

Efficacy and Safety of Brucea javanica Oil Emulsion Injection for Treating Gastric Cancer: A Protocol for a Systematic Review and Meta Analysis

Introduction. Brucea javanica oil emulsion injection (BJOEI) is an antitumor drug extracted from the traditional Chinese medicinal plant Brucea javanica, which has broad prospects as an adjuvant treatment for gastric cancer (GC); however, its efficacy and safety are still controversial. We plan to conduct a systematic review and meta-analysis to summarise the clinical efficacy and safety of BJOEI in the treatment of GC and provide credible evidence for the clinical application and subsequent studies of BJOEI. Methods and Analysis. This systematic review will include articles identified by electronically searching the following databases: PubMed, EMBASE, CENTRAL, Web of Science, the Chinese Biomedical Literature Database (CBM), the China National Knowledge Infrastructure (CNKI), Wanfang Database, and Chinese Scientific Journals Database (VIP Database) from inception to 31 July 2021. The primary outcomes of this research will be the clinical total effective rate, performance status, and adverse drug reactions (ADRs). The systematic review will be performed using RevMan 5 software. Finally, we will use the Grading of Recommendations Assessment, Development and Evaluation System (GRADE) to assess the quality of evidence. Ethics and Dissemination. Ethical approval is not required for literature-based studies. The results of this systematic review will be published in a peer-reviewed journal. PROSPERO registration number: CRD42021265646.

Glutathione Peroxidase 8 as a Prognostic Biomarker of Gastric Cancer: An Analysis of The Cancer Genome Atlas (TCGA) Data

Background

Glutathione peroxidase 8 (GPX8) has previously been shown to play a role in Keshan disease. In the present study, we explored the prognostic relevance of GPX8 expression in patients with gastric cancer (GC) based upon The Cancer Genome Atlas (TCGA) data.

Material/Methods

We assessed the relationship between the expression of GPX8 and clinicopathological findings in GC patients via logistic regression analyses, Kruskal-Wallis tests, and Wilcoxon signed-rank tests. We further assessed the prognostic relevance of specific variables using Kaplan-Meier and Cox regression analyses. We lastly conducted gene set enrichment analyses (GSEA).

Results

We detected a significant association between elevated GPX8 levels and more advanced GC tumor stage (OR=5.92 for I vs. IV), as well as more advanced T (OR=22.91 for T1 vs. T4) and N classification (OR=1.82 for N0 vs. N3). We found worse prognosis in patients expressing high levels of GPX8 relative to those with lower expression of this gene (P=0.021). In a univariate analysis, we found high GPX8 expression was strongly correlated with worse OS (hazard ratio [HR]: 1.05; 95% confidence interval [CI]: 1.01–1.08; P=0.018), and multivariate analysis confirmed that GPX8 expression independently predicts GC patient OS (HR: 1.04; CI: 1.00–1.08, P=0.041). GSEA revealed that elevated GPX8 expression was associated with enrichment of pathways consistent with MAPK signaling, JAK/STAT signaling, TGF-β signaling, melanoma, and basal cell carcinoma.

Conclusions

The expression of GPX8 may have prognostic relevance, being positively associated with worse OS in GC patients.

All-trans retinoic acid suppressed GES-1 cell proliferation induced by exosomes from patients with precancerous lesions by arresting the cell cycle in S-phase

We aimed to detect the expression of specific LncRNAs in exosomes isolated from the serum of patients with precancerous lesions and to study the effect of these serum exosomes on the activity of GES-1 cells in patients with precancerous lesions, as well as the activity of all-trans retinoic acid on GES-1 cells with or without the exosomes. Exosomes were extracted from the serum of patients with precancerous lesions and normal controls. Based on our previous sequencing results, quantitative real time-PCR was used to detect differentially expressed LncRNAs. Exosomes from the serum of patients with precancerous lesions were cocultured with GES-1 cells, and 5 μM all-trans retinoic acid was added as an intervention. Changes in cell viability and expression of LncHOXA10 were observed. Compared with the blank group, the proliferation activity of GES-1 cells cocultured with exosomes derived from the serum of patients with precancerous lesions was increased (P < 0.01), the proportion of cells in S phase was increased (P < 0.05). After adding 5 μM all-trans retinoic acid, the viability of cells decreased significantly (P < 0.01), the proportion of cells in S phase decreased significantly (P < 0.05). The expression of LncHOXA10 was decreased (P < 0.05). All-trans retinoic acid can conduct its chemopreventive effects by inhibiting the expression of LncHOXA10, thereby reducing the activity of LncHOXA10 in GES-1 cells cocultured with serum exosomes from patients with precancerous lesions.

High expression of APC is an unfavorable prognostic biomarker in T4 gastric cancer patients

BACKGROUND

Adenoma polyposis coli (APC) mutation is associated with tumorigenesis via the Wnt signaling pathway.

AIM

To investigate the clinical features and mechanism of APC expression in gastric cancer (GC).

METHODS

Based on APC expression profile, the related genome-wide mRNA expression, microRNA (miRNA) expression, and methylation profile in GC, the relationship between APC and GC, as well as the prognostic significance of APC were systematically analyzed by multi-dimensional methods.

RESULTS

We found that high expression of APC (APC high) was significantly associated with adverse outcomes of T4 GC patients. Genome-wide gene expression analysis revealed that varying APC expression levels in GC were associated with some important oncogenes, and corresponding cellular functional pathways. Genome-wide miRNA expression analysis indicated that most of miRNAs associated with high APC expression were downregulated. The mRNA-miRNA regulatory network analysis revealed that down-regulated miRNAs affected their inhibitory effect on tumor genes. Genome-wide methylation profiles associated with APC expression showed that there was differential methylation between the APC high and APC low groups. The number of hypermethylation sites was larger than that of hypomethylation sites, and most of hypermethylation sites were enriched in CpG islands.

CONCLUSION

Our research demonstrated that high APC expression is an unfavorable prognostic factor for T4 GC patients and may be used as a novel biomarker for pathogenesis research, diagnosis, and treatment of GC.

Downregulation of serum CXCL4L1 predicts progression and poor prognosis in prostate cancer patients treated by radical prostatectomy

Our previous study found that plate factor-4 variant (CXCL4L1) was downregulated in the serum of patients with prostate cancer (PCa). The aim of the present study was to investigate the prognostic value of CXCL4L1 in PCa. In total, 213 PCa patients treated with radical prostatectomy were enrolled and peripheral blood samples of all patients were collected. Expression of serum CXCL4L1 in patients with different tumor stages and grades were measured by enzyme-linked immunosorbent assay (ELISA). The Kaplan–Meier method was applied to estimate the progression to castration-resistant prostate cancer (CRPC), metastasis, biochemical recurrence (BCR)-free survival, and overall survival (OS). Prognostic factors for BCR-free survival and OS were determined by univariate and multivariate analyses using the Cox proportional hazards regression model. The expression of CXCL4L1 was significantly lower in PCa patients with advanced pathological tumor stage, high-grade Gleason score, and metastasis. Moreover, downregulation of CXCL4L1 not only strongly correlated with aggressive clinicopathological features, but also predicted tumor progression and unfavorable outcomes. Finally, multivariate Cox regression analyses identified CXCL4L1 as an independent prognostic factor for both BCR-free survival (hazard ratio [HR]: 2.03, 95% confidence interval [CI]: 1.26–3.27; P = 0.004) and OS (HR: 2.26, 95% CI: 1.07–4.79; P = 0.033). In conclusion, our results indicate that CXCL4L1 might serve as a novel and promising prognostic biomarker for patients with PCa and potential therapeutic target in the future.

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.

Lab-on-a-Chip Platforms for Detection of Cardiovascular Disease and Cancer Biomarkers

Cardiovascular disease (CVD) and cancer are two leading causes of death worldwide. CVD and cancer share risk factors such as obesity and diabetes mellitus and have common diagnostic biomarkers such as interleukin-6 and C-reactive protein. Thus, timely and accurate diagnosis of these two correlated diseases is of high interest to both the research and healthcare communities. Most conventional methods for CVD and cancer biomarker detection such as microwell plate-based immunoassay and polymerase chain reaction often suffer from high costs, low test speeds, and complicated procedures. Recently, lab-on-a-chip (LoC)-based platforms have been increasingly developed for CVD and cancer biomarker sensing and analysis using various molecular and cell-based diagnostic biomarkers. These new platforms not only enable better sample preparation, chemical manipulation and reaction, high-throughput and portability, but also provide attractive features such as label-free detection and improved sensitivity due to the integration of various novel detection techniques. These features effectively improve the diagnostic test speed and simplify the detection procedure. In addition, microfluidic cell assays and organ-on-chip models offer new potential approaches for CVD and cancer diagnosis. Here we provide a mini-review focusing on recent development of LoC-based methods for CVD and cancer diagnostic biomarker measurements, and our perspectives of the challenges, opportunities and future directions.

Pharmacology and clinical application of compound Qifang Weitong formula

Previous studies on the pharmacology and clinical application of compound Qifang Weitong formula have shown that it can ameliorate inflammation-induced gastric mucosal injury, protect the gastric mucosa, improve the structure of regenerated tissue, promote gastric ulcer healing and regeneration, and inhibit gastric ulcer recurrence. Therefore, this formula can be used to treat gastric ulcer, chronic atrophic gastritis (CAG), CAG with atypical hyperplasia, irritable bowel syndrome and functional dyspepsia.