Serum biomarker panels for diagnosis of gastric cancer

Establishment and validation of a nomogram model for early diagnosis of gastric cancer: a large-scale cohort study

Purpose

Identifying high-risk populations and diagnosing gastric cancer (GC) early remains challenging. This study aimed to establish and verify a nomogram model for the early diagnosis of GC based on conventional laboratory indicators.

Methods

We performed a retrospective analysis of the clinical data of 2,770 individuals with first diagnosis of GC and 1,513 patients with benign gastric disease from January 2018 to December 2022. The cases were divided into the training set and validation set randomly, with a ratio of 7:3. Variable screening was performed by least absolute shrinkage and selection operator (LASSO) and logistic regression analysis. A nomogram was constructed in the training set to assist in the early diagnosis of GC.

Results

There were 4283 patients included in the study, with 2998 patients assigned in the training set and 1285 patients in the validation set. Through LASSO regression and logistic regression analysis, independent variables associated with GC were identified, including CEA, CA199, LYM, HGB, MCH, MCHC, PLT, ALB, TG, HDL, and AFR. The nomogram model was constructed using the above 11 independent indicators. The AUC was 0.803 for the training set and 0.797 for the validation set, indicating that the model showed high clinical diagnostic efficacy. The calibration curves and decision curve analysis (DCA) of the nomogram presented good calibration and clinical application ability.

Conclusion

Based on the analysis of large sample size, we constructed a nomogram model with 11 routine laboratory indicators, which showed good discrimination ability and calibration.

Advances in the Clinical Application of High-throughput Proteomics

High-throughput proteomics has become an exciting field and a potential frontier of modern medicine since the early 2000s. While significant progress has been made in the technical aspects of the field, translating proteomics to clinical applications has been challenging. This review summarizes recent advances in clinical applications of high-throughput proteomics and discusses the associated challenges, advantages, and future directions. We focus on research progress and clinical applications of high-throughput proteomics in breast cancer, bladder cancer, laryngeal squamous cell carcinoma, gastric cancer, colorectal cancer, and coronavirus disease 2019. The future application of high-throughput proteomics will face challenges such as varying protein properties, limitations of statistical modeling, technical and logistical difficulties in data deposition, integration, and harmonization, as well as regulatory requirements for clinical validation and considerations. However, there are several noteworthy advantages of high-throughput proteomics, including the identification of novel global protein networks, the discovery of new proteins, and the synergistic incorporation with other omic data. We look forward to participating in and embracing future advances in high-throughput proteomics, such as proteomics-based single-cell biology and its clinical applications, individualized proteomics, pathology informatics, digital pathology, and deep learning models for high-throughput proteomics. Several new proteomic technologies are noteworthy, including data-independent acquisition mass spectrometry, nanopore-based proteomics, 4-D proteomics, and secondary ion mass spectrometry. In summary, we believe high-throughput proteomics will drastically shift the paradigm of translational research, clinical practice, and public health in the near future.

Machine learning-driven SERS analysis platform for rapid and accurate detection of precancerous lesions of gastric cancer

A novel approach is proposed leveraging surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) techniques, principal component analysis (PCA)-centroid displacement-based nearest neighbor (CDNN). This label-free approach can identify slight abnormalities between SERS spectra of gastric lesions at different stages, offering a promising avenue for detection and prevention of precancerous lesion of gastric cancer (PLGC). The agaric-shaped nanoarray substrate was prepared using gas-liquid interface self-assembly and reactive ion etching (RIE) technology to measure SERS spectra of serum from mice model with gastric lesions at different stages, and then a SERS spectral recognition model was trained and constructed using the PCA-CDNN algorithm. The results showed that the agaric-shaped nanoarray substrate has good uniformity, stability, cleanliness, and SERS enhancement effect. The trained PCA-CDNN model not only found the most important features of PLGC, but also achieved satisfactory classification results with accuracy, area under curve (AUC), sensitivity, and specificity up to 100%. This demonstrated the enormous potential of this analysis platform in the diagnosis of PLGC.

PG I and PG II show unique value in diagnosing postoperative biochemical recurrence in patients with gastric cancer after total gastrectomy

OBJECTIVE

To investigate the potential of group I pepsinogen (PG I) and group II pepsinogen (PG II) as diagnostic markers for recurrence in gastric cancer (GC) patients post-total gastrectomy.

METHODS

Ninety-six patients who underwent total gastrectomy for GC between June 2022 and June 2023 were included in this study. Clinical data, serum samples, and ascites samples were collected. Patients were categorized based on recurrence status at the time of sample collection and the primary tumor site. PG I and PG II levels were determined using a chemiluminescent immunoassay, and their clinical utility following total gastrectomy for GC was evaluated via receiver operating characteristic (ROC) curve analysis.

RESULTS

This study included 96 GC patients who underwent total gastrectomy, 55 of whom experienced postoperative recurrence (57.29%). The levels of serum PG I (27.86 (27.04, 30.97) vs. 26.05 (24.16, 27.09) ng/mL; P < 0.0001) and PG II (1.95 (1.23, 3.05) vs. 0.63 (0.47, 0.90) ng/mL; P < 0.0001) were significantly greater in the recurrent group compared to the non-recurrent group. The secretion of PG I and/or PG II by metastatic cancer cells correlated with the primary lesion site. When the cut-off value for serum PG I was 26.93 ng/mL, the area under the curve (AUC) for PG I was 0.77. When the cut-off value for serum PG II was 0.96 ng/mL, the AUC reached 0.90. The combined AUC was 0.97.

CONCLUSION

These findings suggest that serum PG I and PG II are valuable biomarkers for identifying GC patients with biochemical recurrence post-total gastrectomy.

Decreased SLC16A13 Expression Level Can Increase Apoptosis in KATO2 Cell Line, A Promising Biomarker

OBJECTIVE

Gastric cancer is a prevalent cancer type worldwide, and significant research efforts are focused on finding effective treatments. Recent studies have highlighted the importance of plasma membrane carriers, particularly solute carriers, in cancer progression. The SLC16A family, notably the SLC16A13 gene, plays a critical role in cancer development and tumor growth. This study aims to explore the impact of reducing SLC16A13 expression in gastric cancer cells on their survival, proliferation, and metastatic potential.

METHODS

Gastric cancer cells (KATO2) were cultured in RPMI medium supplemented with 10% fetal bovine serum. The cells were then transfected with SLC16A13 si-RNA to lower gene expression. The effects of this si-RNA on cell death and apoptosis were assessed using MTT and flow cytometry assays. Cell migration capabilities were evaluated using the scratch test. Western blot and Real-Time PCR were employed to measure SLC16A13 expression levels and protein detection. Additionally, RT-PCR was used to analyze changes in genes related to apoptosis and cell migration.

RESULTS

The reduction of SLC16A13 expression following si-RNA transfection significantly increased apoptosis and cell death in the KATO2 cell line after 72 hours (P < 0.0001). Furthermore, the study revealed that decreased SLC16A13 expression did not impact cancer cell migration. Cell viability, assessed by MTT assay, showed a significant decrease at 48 and 72 hours post-transfection (P < 0.0001).

CONCLUSION

The findings indicate that targeting SLC16A13 can effectively increase cell death and apoptosis in gastric cancer cells, making it a viable therapeutic target.

Hotspots and trends of risk factors in gastric cancer: A visualization and bibliometric analysis

BACKGROUND

The lack of specific symptoms of gastric cancer (GC) causes great challenges in its early diagnosis. Thus it is essential to identify the risk factors for early diagnosis and treatment of GC and to improve the survival rates.

AIM

To assist physicians in identifying changes in the output of publications and research hotspots related to risk factors for GC, constructing a list of key risk factors, and providing a reference for early identification of patients at high risk for GC.

METHODS

Research articles on risk factors for GC were searched in the Web of Science core collection, and relevant information was extracted after screening. The literature was analyzed using Microsoft Excel 2019, CiteSpace V, and VOSviewer 1.6.18.

RESULTS

A total of 2514 papers from 72 countries and 2507 research institutions were retrieved. China (n = 1061), National Cancer Center (n = 138), and Shoichiro Tsugane (n = 36) were the most productive country, institution, or author, respectively. The research hotspots in the study of risk factors for GC are summarized in four areas, namely: Helicobacter pylori (H. pylori) infection, single nucleotide polymorphism, bio-diagnostic markers, and GC risk prediction models.

CONCLUSION

In this study, we found that H. pylori infection is the most significant risk factor for GC; single-nucleotide polymorphism (SNP) is the most dominant genetic factor for GC; bio-diagnostic markers are the most promising diagnostic modality for GC. GC risk prediction models are the latest current research hotspot. We conclude that the most important risk factors for the development of GC are H. pylori infection, SNP, smoking, diet, and alcohol.

LUM as a novel prognostic marker and its correlation with immune infiltration in gastric cancer: a study based on immunohistochemical analysis and bioinformatics

BACKGROUND

Gastric cancer (GC) is considered the sixth highly prevailing malignant neoplasm and is ranked third in terms of cancer mortality rates. To enable an early and efficient diagnosis of GC, it is important to detect the fundamental processes involved in the oncogenesis and progression of gastric malignancy. The understanding of molecular signaling pathways can facilitate the development of more effective therapeutic strategies for GC patients.

METHODS

The screening of genes that exhibited differential expression in early and advanced GC was performed utilizing the Gene Expression Omnibus databases (GSE3438). Based on this, the protein and protein interaction network was constructed to screen for hub genes. The resulting list of hub genes was evaluated with bioinformatic analysis and selected genes were validated the protein expression by immunohistochemistry (IHC). Finally, a competing endogenous RNA network of GC was constructed.

RESULTS

The three genes (ITGB1, LUM, and COL5A2) overexpressed in both early and advanced GC were identified for the first time. Their upregulation has been linked with worse overall survival (OS) time in patients with GC. Only LUM was identified as an independent risk factor for OS among GC patients by means of additional analysis. IHC results demonstrated that the expression of LUM protein was increased in GC tissue, and was positively associated with the pathological T stage. LUM expression can effectively differentiate tumorous tissue from normal tissue (area under the curve = 0.743). The area under 1-, 3-, and 5-year survival relative operating characteristics were greater than 0.6. Biological function enrichment analyses suggested that the genes related to LUM expression were involved in extracellular matrix development-related pathways and enriched in several cancer-related pathways. LUM affects the infiltration degree of cells linked to the immune system in the tumor microenvironment. In GC progression, the AC117386.2/hsa-miR-378c/LUM regulatory axis was also identified.

CONCLUSION

Collectively, a thorough bioinformatics analysis was carried out and an AC117386.2/hsa-miR-378c/LUM regulatory axis in the stomach adenocarcinoma dataset was detected. These findings should serve as a guide for future experimental investigations and warrant confirmation from larger studies.

Landscape of Innovative Methods for Early Diagnosis of Gastric Cancer: A Systematic Review

From a global perspective, gastric cancer (GC) persists as a significant healthcare issue. In the Western world, the majority of cases are discovered at late stages, when the treatment is generally unsuccessful. There are no organized screening programs outside of Asia (Japan and Republic of Korea). Traditional diagnosis techniques (such as upper endoscopy), conventional tumor markers (CEA, CA19-9, and CA72-4), radiographic imaging, and CT scanning all have drawbacks. The gold standard for the earliest detection of cancer and related premalignant lesions is still endoscopy with a proper biopsy follow-up. Since there are currently no clinically approved biomarkers for the early diagnosis of GC, the identification of non-invasive biomarkers is expected to help improve the prognosis and survival rate of these patients. The search for new screening biomarkers is currently underway. These include genetic biomarkers, such as circulating tumor cells, microRNAs, and exosomes, as well as metabolic biomarkers obtained from biofluids. Meanwhile, cutting-edge high-resolution endoscopic technologies are demonstrating promising outcomes in the visual diagnosis of mucosal lesions with the aid of linked color imaging and machine learning models. Following the PRISMA guidelines, this study examined the articles in databases such as PubMed, resulting in 167 included articles. This review discusses the currently available and emerging methods for diagnosing GC early on, as well as new developments in the endoscopic detection of early lesions of the stomach.

Circulating Proteins as Diagnostic Markers in Gastric Cancer

Gastric cancer (GC) is a highly malignant disease affecting humans worldwide and has a poor prognosis. Most GC cases are detected at advanced stages due to the cancer lacking early detectable symptoms. Therefore, there is great interest in improving early diagnosis by implementing targeted prevention strategies. Markers are necessary for early detection and to guide clinicians to the best personalized treatment. The current semi-invasive endoscopic methods to detect GC are invasive, costly, and time-consuming. Recent advances in proteomics technologies have enabled the screening of many samples and the detection of novel biomarkers and disease-related signature signaling networks. These biomarkers include circulating proteins from different fluids (e.g., plasma, serum, urine, and saliva) and extracellular vesicles. We review relevant published studies on circulating protein biomarkers in GC and detail their application as potential biomarkers for GC diagnosis. Identifying highly sensitive and highly specific diagnostic markers for GC may improve patient survival rates and contribute to advancing precision/personalized medicine.

Serum tRF-27-FDXXE6XRK45 as a Promising Biomarker for the Clinical Diagnosis in Gastric Cancer

Objective: Gastric cancer (GC) has high morbidity and mortality due to inefficient early screening. Therefore, we are searching for more sensitive and specific diagnostic markers for GC. tRNA-derived small RNAs are novel non-coding small RNAs with good abundance and stable presence in body fluids, which may play multiple biological regulatory roles. In this study, we aimed to find a potential biomarker with high accuracy in tRNA-derived small RNAs that can help diagnose GC. Methods: tRF-27-FDXXE6XRK45 was screened as a target molecule by high-throughput sequencing in three pairs of GC tissues. RNA quantitative reverse transcription PCR was conducted to detect the expression levels of tRF-27-FDXXE6XRK45. Agarose gel electrophoresis, Sanger sequencing, cytoplasmic and nuclear RNA isolation assays, gradient dilution experiments, and room temperature and repeated freeze-thaw experiments were used to assess the detection performance of tRF-27-FDXXE6XRK45. Using the chi-square test to analyze the correlation between tRF-27-FDXXE6XRK45 expression levels and clinicopathological parameters. In addition, receiver operating characteristic curves were used to evaluate the diagnostic value of tRF-27-FDXXE6XRK45 in GC. Results: tRF-27-FDXXE6XRK45 expression levels, significantly upregulated in tissues and sera of GC patients and decreased after radical GC surgery, were correlated with the degree of differentiation, depth of tumor infiltration, TNM stage, lymph node metastasis, and nerve/vascular invasion. In comparison with current GC diagnostic markers, tRF-27-FDXXE6XRK45 displayed better efficacy. Conclusions: tRF-27-FDXXE6XRK45, with high diagnostic efficacy, can distinguish GC patients from gastritis patients and healthy donors, suggesting that tRF-27-FDXXE6XRK45 may be a promising candidate as a diagnostic marker for GC.

Urinary Proteomics for Discovery of Gastric Cancer Biomarkers to Enable Precision Clinical Oncology

For precision in clinical oncology practice, detection of tumor-derived peptides and proteins in urine offers an attractive and noninvasive alternative for diagnostic or screening purposes. In this study, we report comparative quantitative proteomic profiling of urine samples from patients with gastric cancer and healthy controls using tandem mass tags-based multiplexed mass spectrometry approach. We identified 1504 proteins, of which 246 were differentially expressed in gastric cancer cases. Notably, ephrin A1 (EFNA1), pepsinogen A3 (PGA3), sortilin 1 (SORT1), and vitronectin (VTN) were among the upregulated proteins, which are known to play crucial roles in the progression of gastric cancer. We also found other overexpressed proteins, including shisa family member 5 (SHISA5), mucin like 1 (MUCL1), and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. Using a novel approach for targeted proteomics, SureQuant, we validated changes in abundance of a subset of proteins discovered in this study. We confirmed the overexpression of vitronectin and sortilin 1 in an independent set of urine samples. Altogether, this study provides molecular candidates for biomarker development in gastric cancer, and the findings also support the promise of urinary proteomics for noninvasive diagnostics and personalized/precision medicine in the oncology clinic.

Real-World Practice of Gastric Cancer Prevention and Screening Calls for Practical Prediction Models

INTRODUCTION

Some gastric cancer prediction models have been published. Still, the value of these models for application in real-world practice remains unclear. We aim to summarize and appraise modeling studies for gastric cancer risk prediction and identify potential barriers to real-world use.

METHODS

This systematic review included studies that developed or validated gastric cancer prediction models in the general population.

RESULTS

A total of 4,223 studies were screened. We included 18 development studies for diagnostic models, 10 for prognostic models, and 1 external validation study. Diagnostic models commonly included biomarkers, such as Helicobacter pylori infection indicator, pepsinogen, hormone, and microRNA. Age, sex, smoking, body mass index, and family history of gastric cancer were frequently used in prognostic models. Most of the models were not validated. Only 25% of models evaluated the calibration. All studies had a high risk of bias, but over half had acceptable applicability. Besides, most studies failed to clearly report the application scenarios of prediction models.

DISCUSSION

Most gastric cancer prediction models showed common shortcomings in methods, validation, and reports. Model developers should further minimize the risk of bias, improve models' applicability, and report targeting application scenarios to promote real-world use.

Expression and the Prognostic Value of Biglycan in Gastric Cancer

Background

Biglycan (BGN) is a family member of small leucine-rich repeat proteoglycans. High expression of BGN might enhance the invasion and metastasis in some types of tumors. Here, the prognostic significance of BGN was evaluated in gastric cancer. Material and Methods. Two independent Gene Expression Omnibus (GEO) gastric cancer microarray datasets (n = 64 and n = 432) were collected for this study. Kaplan-Meier analysis was applied to evaluate if BGN impacts the outcomes of gastric cancer. Protein-protein interaction (PPI) analysis was performed on gastric cancer-related genes and BGN targets, and those interactions with confidence interval (CI) ≥ 0.7 were chosen to construct a PPI network. The gene set enrichment analysis (GSEA) was used to explore BGN and cancer-related gene signatures. Gene Transcription Regulation Database (GTRD) and ALGGEN-PROMO predicted the transcription factor binding sites (TFBSs) of the BGN promoter. BGN protein level in gastric cancer tissue was determined by immunohistochemistry (IHC). Bioinformatic analysis predicted the putative TFs of BGN.

Results

For gastric cancer, the mRNA expression level of BGN in tumor tissue was significantly higher than that in normal tissue. Kaplan-Meier analysis showed that higher expression of BGN mRNA was significantly associated with more reduced recurrence-free survival (RFS). GSEA results suggested that BGN was significantly enriched in gene signatures related to metastasis and poor prognosis, revealing that BGN might be associated with cell proliferation, poor differentiation, and high invasiveness of gastric cancer. Meanwhile, the putative TFs, including AR, E2F1, and TCF4, were predicted by bioinformatic analysis and also significantly correlated with expression of BGN in mRNA levels.

Conclusion

High expression of BGN mRNA was significantly related to poor prognosis, which suggested that BGN was a potential prognostic biomarker and therapeutic target of gastric cancer.

Biomarkers for Gastric Cancer Screening and Early Diagnosis

Gastric cancer is one of the most common cancers worldwide, with a bad prognosis associated with late-stage diagnosis, significantly decreasing the overall survival. This highlights the importance of early detection to improve the clinical course of these patients. Although screening programs, based on endoscopic or radiologic approaches, have been useful in countries with high incidence, they are not cost-effective in low-incidence populations as a massive screening strategy. Additionally, current biomarkers used in daily routine are not specific and sensitive enough, and most of them are obtained invasively. Thus, it is imperative to discover new noninvasive biomarkers able to diagnose early-stage gastric cancer. In this context, liquid biopsy is a promising strategy. In this review, we briefly discuss some of the potential biomarkers for gastric cancer screening and diagnosis identified in blood, saliva, urine, stool, and gastric juice.

Identification of Novel Biomarkers for Pre-diabetic Diagnosis Using a Combinational Approach

Reliable protein markers for pre-diabetes in humans are not clinically available. In order to identify novel and reliable protein markers for pre-diabetes in humans, healthy volunteers and patients diagnosed with pre-diabetes and stroke were recruited for blood collection. Blood samples were collected from healthy and pre-diabetic subjects 12 h after fasting. BMI was calculated from body weight and height. Fasting blood glucose (FBG), glycated hemoglobin (HbA1C), triglyceride (TG), total cholesterol, high-density lipoprotein, low-density lipoprotein (LDL), insulin and albumin were assayed by automated clinical laboratory methods. We used a quantitative proteomics approach to identify 1074 proteins from the sera of pre-diabetic and healthy subjects. Among them, 500 proteins were then selected using Mascot analysis scores. Further, 70 out of 500 proteins were selected via volcano plot analysis according to their statistical significance and average relative protein ratio. Eventually, 7 serum proteins were singled out as candidate markers for pre-diabetes due to their diabetic relevance and statistical significance. Immunoblotting data demonstrated that laminin subunit alpha 2 (LAMA2), mixed-lineage leukemia 4 (MLL4), and plexin domain containing 2 (PLXDC2) were expressed in pre-diabetic patients but not healthy volunteers. Receiver operating characteristic curve analysis indicated that the combination of the three proteins has greater diagnostic efficacy than any individual protein. Thus, LAMA2, MLL4 and PLXDC2 are novel and reliable serum protein markers for pre-diabetic diagnosis in humans.

Role of Mean Platelet Volume in the Prognosis of Locally Advanced Gastric Cancer: A Tertiary Cancer Center Experience

Introduction

Mean platelet volume (MPV) is an inflammatory marker suggesting the activation of platelets. Many studies observed an association between MPV and cancer spread and metastasis. Hence, we have conducted a retrospective study to find the role of MPV as a prognostic marker in locally advanced gastric cancer.

Materials and methods

The present study included a retrospective review of 149 patients with gastric cancer who had neoadjuvant chemotherapy followed by surgery. MPV was obtained and then statistically analyzed to find an association between tumor (T), node (N), and overall stage as per the American Joint Committee on Cancer (AJCC) staging system, using Statistical Package for the Social Sciences (SPSS) software (IBM Corp., Armonk, NY).

Results

In our study, we observed that MPV values were significantly high in N+ disease (OR 3.794 (95% CI 1.903 - 7.563); p-value 0.0001), higher T stage (OR for >T2 3.692 (95% CI 1.876 - 7.266); p-value 0.0001), and advanced stage (OR 7.708 (95% CI 3.258 - 18.237); p-value 0.0001) of gastric cancer.

Conclusions

MPV is an inflammatory marker that correlates with nodal disease and aids in the staging and prognostication of locally advanced gastric cancer. This inexpensive, convenient marker can aid in the risk stratification of locally advanced gastric cancer.

Evaluation of the value of multiparameter combined analysis of serum markers in the early diagnosis of gastric cancer

BACKGROUND

In early gastric cancer (GC), tumor markers are increased in the blood. The levels of these markers have been used as important indexes for GC screening, early diagnosis and prognostic evaluation. However, specific tumor markers have not yet been discovered. Diagnosis based on a single tumor marker has limited significance. The detection rate of GC is still very low.

AIM

To improve the diagnostic value of blood markers for GC.

METHODS

We used a multiparameter joint analysis of 77 indexes of malignant GC and gastric polyp (GP), 64 indexes of GC and healthy controls (Ctrls).

RESULTS

By analyzing the data, there are 27 indexes in the final Ctrls vs GC with P values < 0.01, the area under the curve (AUC) of albumin is the largest in Ctrls vs GC, and the AUC was 0.907. 30 indexes in GP vs GC have P values < 0.01. Among them, the D-dimer showed an AUC of 0.729. The 27 indexes in Ctrls vs GC and 30 indexes in GP vs GC were used for binary logistic regression, discriminant analysis, classification tree analysis and artificial neural network analysis model. For the ability to distinguish between Ctrls vs GC, GP vs GC, artificial neural networks had better diagnostic value when compared with classification tree, binary logistic regression, and discriminant analysis. When compared Ctrl and GC, the overall prediction accuracy was 92.9%, and the AUC was 0.992 (0.980, 1.000). When compared GP and GC, the overall prediction accuracy was 77.9%, and the AUC was 0.969 (0.948, 0.990).

CONCLUSION

The diagnostic effect of multi-parameter joint artificial neural networks analysis is significantly better than the single-index test diagnosis, and it may provide an assistant method for the detection of GC.

Nesfatin-1 is a potential diagnostic biomarker for gastric cancer

The lack of reliable plasma biomarkers limits their use in the diagnosis of gastric cancer (GC). The current study aimed to determine whether plasma nesfatin-1 can be used as a novel non-invasive biomarker for the diagnosis of GC. The levels of nesfatin-1 in 40 patients with GC and 40 healthy individuals, who were selected from the Chaohu Hospital Affiliated to Anhui Medical University, were assessed. ELISA was used for the measurement of plasma nesfatin-1 levels, while immunohistochemistry was applied to determine Ki67 protein expression in GC and normal gastric tissues. The diagnostic value of plasma nesfatin-1 for GC was further assessed using receiver operating characteristic (ROC) curve analysis. The results revealed that, compared with the controls, the mean nesfatin-1 levels in patients with GC were significantly increased. Furthermore, the protein expression of Ki67 in GC tissue was significantly upregulated compared with that in normal gastric tissue. Plasma nesfatin-1 levels were also demonstrated to be correlated with Ki67 protein expression in GC tissues. Additionally, ROC curve analysis indicated the potential diagnostic value of nesfatin-1, and the area under the ROC curve (AUC) for nesfatin-1 was 0.857 (95% confidence interval, 0.769-0.946). At a threshold nesfatin-1 level of 1.075 ng/ml, the optimal sensitivity and specificity were 70.0 and 95.0%, respectively, in discriminating patients with GC from healthy controls. These results indicated that plasma nesfatin-1 may serve as a novel biomarker for the diagnosis of GC and determination of GC cell proliferation.

E-Cadherin Protein as a Potential Marker for Gastric Cancer and Its Association with Helicobacter Pylori- Induced Gastritis and Gastric Ulcer

BACKGROUND

Gastric cancer is still the main health threat being the third leading cause of deaths from cancers in the world. The major risk behind the gastric cancer is that it remains asymptomatic in the early stages and in (97%) cases it metastasizes to other organs. Gastric cancer is a multifactorial disease in which Helicobacter pylori (H. pylori) has been known as a risk factor. However, patients with gastritis, especially atrophic gastritis and gastric ulcer have been shown to be at an increased risk for developing gastric cancer.

METHODS

This study included measuring the serum levels of E-Cadherin protein, carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) in 30 patients diagnosed with gastritis, 20 gastric ulcer patients, 20 gastric cancer patients and in 20 healthy volunteers serving as the control group.

RESULTS

Infection with H. pylori was diagnosed by serology (IgA and IgG antibodies) as well as by rapid urease test (RUT) and histology. The results showed that 50 (71.4%) of the patients were positive for H. pylori. Levels of E-Cadherin were increased significantly in all patients in comparison to the control group with a large significant increase in the gastric cancer group. The levels of E-Cadherin were also significantly increased in H. pylori infected patients compared to H. pylori negative patients. A non-significant difference in the levels of CA19-9 and CEA was observed in all patients in comparison to healthy controls.

CONCLUSION

This study concluded that serum E-Cadherin could be considered as a potential marker in diagnosis of gastric cancer.

A Disintegrin and Metalloproteinase 8 as a Potential Blood Biomarker for Early Diagnosis of Gastric Cancer

PURPOSE

We aimed to evaluate the clinical significance of a disintegrin and metalloproteinase 8 (ADAM 8) as a potential blood biomarker for gastric cancer (GC).

MATERIALS AND METHODS

Blood ADAM 8 was measured by ELISA. Cytokines/chemokines [interleukin-23 (IL-23), stromal cell-derived factor 1α/CXC chemokine ligand 12 (SDF-1α/CXCL12), interleukin-8 (IL-8), and soluble CD40 ligand (sCD40L)] were measured by chemiluminescent immunoassay. They were compared among five groups; normal/gastritis, high-risk, early GC (EGC), advanced GC (AGC) without distant metastasis, and AGC with distant metastasis by one-way analysis of variance in both training (n=80) and validation dataset (n=241). Clinicopathological features of GC and GC-associated cytokines were evaluated for their correlations with blood ADAM 8. To evaluate the diagnostic accuracy to predict GC, receiver operating characteristic (ROC) curve and logistic regression were used.

RESULTS

Blood ADAM 8 significantly increased along GC carcinogenesis in both training (ANOVA, p<0.001) and validation dataset (p<0.001). It was significantly higher in EGC compared to high-risk (post-hoc Bonferroni, p=0.041) and normal (p<0.001). It was also higher in AGC compared with high-risk (p<0.001) and normal (p<0.001) groups. However, no significant difference was found between cancer groups. Blood ADAM 8 was correlated with N-stage (Spearman's correlation, γ_s=0.320, p=0.011), but not with T-stage or M-stage. Pearson's correlations showed blood ADAM 8 was closely correlated with pre-inflammatory cytokines, IL-23 (p=0.036) and SDF-1α/CXCL12 (p=0.037); however, it was not correlated with pro-angiogenic cytokine IL-8 (p=0.313), and sCD40L (p=0.702). ROC curve and logistic regression demonstrated that blood ADAM 8 showed higher diagnostic accuracy (sensitivity, 73.7%; specificity, 86.2%) than CEA (sensitivity, 23.1%; specificity, 91.4%). Combination of ADAM 8 and CEA further increased the diagnostic accuracy to predict GC (sensitivity, 81.8%; specificity, 84.0%).

CONCLUSION

Blood ADAM 8 is a promising biomarker for early detection of GC.

Recent advances in gastric cancer early diagnosis

Gastric cancer (GC) remains an important cause of cancer death worldwide with a high mortality rate due to the fact that the majority of GC cases are diagnosed at an advanced stage when the prognosis is poor and the treatment options are limited. Unfortunately, the existing circulating biomarkers for GC diagnosis and prognosis display low sensitivity and specificity and the GC diagnosis is based only on the invasive procedures such as upper digestive endoscopy. There is a huge need for less invasive or non-invasive tests but also highly specific biomarkers in case of GC. Body fluids such as peripheral blood, urine or saliva, stomach wash/gastric juice could be a source of specific biomarkers, providing important data for screening and diagnosis in GC. This review summarized the recently discovered circulating molecules such as microRNAs, long non-coding RNAs, circular RNAs, which hold the promise to develop new strategies for early diagnosis of GC.

Dowregulation of OTX1 attenuates gastric cancer cell proliferation, migration and invasion

Orthodenticle homolog 1 (OTX1) has previously been revealed to be tightly associated with the development and progression of several human tumors. However, the functional roles and underlying molecular mechanisms of OTX1 in gastric cancer (GC) remain poorly understood. In the present study, we observed that OTX1 was highly expressed in GC tissues compared with adjacent non-tumor tissues based on a large cohort of samples from The Cancer Genome Atlas (TCGA) database. An immunohistochemical analysis indicated that OTX1 levels were increased in tumors that became metastatic compared with those in tumors that did not. This finding was significantly associated with patients who had shorter overall survival times. The knockdown of OTX1 significantly inhibited the proliferation, migration and invasion of SGC-7901 and MGC-803 cells. Furthermore, the knockdown of OTX1 induced cell cycle arrest in the G₀/G₁ phase and reduced the expression of cyclin D1. In addition, the inhibition of OTX1 led to increased GC cell apoptosis by upregulating cleaved PARP, cleaved caspase-3 and Bax. In conclusion, our data indicated that OTX1 functions as a key regulator in tumor growth and metastasis of GC cells. Thus, OTX1 may be a promising novel target for molecular therapy directed toward GC.

BI2536, a potent and selective inhibitor of polo-like kinase 1, in combination with cisplatin exerts synergistic effects on gastric cancer cells

BI2536 is a highly selective and potent inhibitor of polo-like kinase 1 (PLK1). In this study, we aimed to determine whether BI2536 and cisplatin can synergistically inhibit the malignant behavior of gastric cancer cells. For this purpose, the expression of PLK1 in gastric cancer cells was determined. The effects of BI2536, cisplatin, and the combination of BI2536 and cisplatin on gastric cancer cell viability, invasion, cell cycle arrest and apoptosis were assessed. Furthermore, the expression of cell cycle-regulated proteins was examined. Moreover, the differentially expressed proteins between the SGC-7901 and SGC-7901/DDP (cisplatin-resistant) cells, and the enriched signaling pathways were analyzed by protein pathway array following treatment with BI2536 (IC50) for 48 h. Our results revealed that PLK1 was upregulated in the SGC-7901/DDP (cisplatin-resistant) gastric cancer cells compared with the SGC-7901 cells. BI2536 enhanced the inhibitory effect of cisplatin on SGC-7901 cell viability and invasion. BI2536 induced G2/M arrest in SGC-7901 and SGC-7901/DDP cells. BI2536 promoted cisplatin-induced gastric cancer SGC-7901/DDP cell apoptosis. It also induced the differential expression of 68 proteins between the SGC-7901 and SGC-7901/DDP cells, and these differentially expressed proteins were involved in a number of cellular functions and signaling pathways, such as cell death, cell development, tumorigenesis, the cell cycle, DNA duplication/recombination/repair, cellular movement, and the Wnt/β-catenin and mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK)/ribosomal S6 kinase 1 (RSK1) signaling pathways. On the whole, our findings suggest that BI2536 and cisplatin synergistically inhibit the malignant behavior of SGC-7901/DDP (cisplatin‑resistant) gastric cancer cells.

REG3A promotes the proliferation, migration, and invasion of gastric cancer cells

The mechanism underlying the metastasis of gastric cancer (GC) cells remains elusive. REG3A is considered an oncogene in various cancers, but in GC its role is unclear. Here, we report that the expression of REG3A was significantly increased in the tumor tissues of patients with GC compared with the matched normal tissues. Knockdown of REG3A induced by specific small interfering RNA (siRNA) significantly repressed the proliferation of GC cells for 24 h or 48 h. Moreover, knockdown of REG3A significantly suppressed the migration, invasion, and adhesion of GC cells in vitro. Furthermore, knockdown of REG3A reduced the phosphorylation of JAK2 and STAT3, and altered the messenger RNA (mRNA) and protein expression levels of E-cadherin, Snail, RhoC, MTA1, MMP-2, and MMP-9. Taken together, REG3A is overexpressed in GC and promotes the proliferation, migration, invasion, and adhesion of GC cells by regulating the JAK2/STAT3 signal pathway. REG3A may be a potential therapeutic target for GC.

Chemotherapy regimen based on sorafenib combined with 5-FU on HIF-1α and VEGF expression and survival in advanced gastric cancer patients

The present study investigated the effect of combined sorafenib chemotherapy on hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) expression and survival time of patients with advanced gastric cancer. From January 2010 to December 2011, 92 patients diagnosed with advanced gastric cancer were selected and randomly divided into the treatment group and control group. The treatment group was treated with sorafenib chemotherapy combined with 5-fluorouracil (5-FU), and the control group received 5-FU. The treatment course was 3-4 cycles. During the same period, 46 healthy persons admitted to the Second People's Hospital of Huaian were selected as the controls. A volume of 3-4 ml peripheral blood from each patient and control was collected before and after treatment. The expression levels of HIF-1α and VEGF in peripheral blood were measured by ELISA. The survival time of patients with advanced gastric cancer was followed and analyzed. Compared with healthy controls, serum levels of HIF-1α and VEGF were significantly higher in patients with advanced gastric cancer (P<0.05). After chemotherapy combined with sorafenib, the peripheral blood levels of HIF-1α and VEGF decreased significantly in the treatment group (P<0.05). The 5-year survival rate of patients in the two groups was followed. Compared with the control group, the 1-year survival rate of the treatment group was significantly higher (P<0.05). In conclusion, chemotherapy combined with sorafenib can effectively reduce serum levels of HIF-1α and VEGF in patients with advanced gastric cancer, and improve their 1-year survival rate and prognosis. Therefore, it has significant clinical application value.