Diagnosis Of Early Gastric Cancer Research Articles

Development of a deep learning model for early gastric cancer diagnosis using preoperative computed tomography images.

Gastric cancer is a highly prevalent and fatal disease. Accurate differentiation between early gastric cancer (EGC) and advanced gastric cancer (AGC) is essential for personalized treatment. Currently, the diagnostic accuracy of computerized tomography (CT) for gastric cancer staging is insufficient to meet clinical requirements. Many studies rely on manual marking of lesion areas, which is not suitable for clinical diagnosis. In this study, we retrospectively collected data from 341 patients with gastric cancer at the First Affiliated Hospital of Wenzhou Medical University. The dataset was randomly divided into a training set (n=273) and a validation set (n=68) using an 8:2 ratio. We developed a two-stage deep learning model that enables fully automated EGC screening based on CT images. In the first stage, an unsupervised domain adaptive segmentation model was employed to automatically segment the stomach on unlabeled portal phase CT images. Subsequently, based on the results of the stomach segmentation model, the image was cropped out of the stomach area and scaled to a uniform size, and then the EGC and AGC classification models were built based on these images. The segmentation accuracy of the model was evaluated using the dice index, while the classification performance was assessed using metrics such as the area under the curve (AUC) of the receiver operating characteristic (ROC), accuracy, sensitivity, specificity, and F1 score. The segmentation model achieved an average dice accuracy of 0.94 on the hand-segmented validation set. On the training set, the EGC screening model demonstrated an AUC, accuracy, sensitivity, specificity, and F1 score of 0.98, 0.93, 0.92, 0.92, and 0.93, respectively. On the validation set, these metrics were 0.96, 0.92, 0.90, 0.89, and 0.93, respectively. After three rounds of data regrouping, the model consistently achieved an AUC above 0.9 on both the validation set and the validation set. The results of this study demonstrate that the proposed method can effectively screen for EGC in portal venous CT images. Furthermore, the model exhibits stability and holds promise for future clinical applications.

Multidimensional Analysis of a Cell-Free DNA Whole Methylome Sequencing Assay for Early Detection of Gastric Cancer: Protocol for an Observational Case-Control Study.

Commonly used noninvasive serological indicators serve as a step before endoscope diagnosis and help identify the high-risk gastric cancer (GC) population. However, they are associated with high false positives and high false negatives. Alternative noninvasive approaches, such as cancer-related features in cell-free DNA (cfDNA) fragments, have been gradually identified and play essential roles in early cancer detection. The integrated analysis of multiple cfDNA features has enhanced detection sensitivity compared to individual features. This study aimed to develop and validate an assay based on assessing genomic-scale methylation and fragmentation profiles of plasma cfDNA for early cancer detection, thereby facilitating the early diagnosis of GC. The primary objective is to evaluate the overall specificity and sensitivity of the assay in predicting GC within the entire cohort, and subsequently within each clinical stage of GC. The secondary objective involved investigating the specificity and sensitivity of the assay in combination with possible serological indicators. This is an observational case-control study. Blood samples will be prospectively collected before gastroscopy from 180 patients with GC and 180 nonmalignant control subjects (healthy or with benign gastric diseases). Cases and controls will be randomly divided into a training and a testing data set at a ratio of 2:1. Plasma cfDNA will be isolated and extracted, followed by bisulfite-free low-depth whole methylome sequencing. A multidimensional model named Thorough Epigenetic Marker Integration Solution (THEMIS) will be constructed in the training data set. The model includes features such as the methylated fragment ratio, chromosomal aneuploidy of featured fragments, fragment size index, and fragment end motif. The performance of the model in distinguishing between patients with cancer and noncancer controls will then be evaluated in the testing data set. Furthermore, GC-related biomarkers, such as pepsinogen, gastrin-17, and Helicobacter pylori, will be measured for each patient, and their predictive accuracy will be assessed both independently and in combination with the THEMIS model. Recruitment began in November 2022 and will be ended in April 2024. As of August 2022,250 patients have been enrolled. The final data analysis is anticipated to be completed by September 2024. This is the first registered case-control study designed to investigate a stacked ensemble model integrating several cfDNA features generated from a bisulfite-free whole methylome sequencing assay. These features include methylation patterns, fragmentation profiles, and chromosomal copy number changes, with the aim of identifying the GC population. This study will determine whether multidimensional analysis of cfDNA will prove to be an effective strategy for distinguishing patients with GC from nonmalignant individuals within the Chinese population. We anticipate the THEMIS model will complement the standard-of-care screening and aid in identifying high-risk patients for further diagnosis. ClinicalTrial.gov NCT05668910; https://www.clinicaltrials.gov/study/NCT05668910. DERR1-10.2196/48247.

Flexible endoscopic instrument for diagnosis and treatment of early gastric cancer.

Gastric cancer is a common cancer endangering human life and health worldwide. Early detection and diagnosis of gastric cancer that is normally performed by flexible endoscope can significantly improve the survival rate of patients. However, current endoscopic instruments have some problems, such as limitation of degrees of freedom (DOFs) and lack of surgical triangulation. Meanwhile, the lack of an intraoperative technique for the real-time evaluation of early gastric cancer is also a serious problem. To solve these problems, we have developed a dual-bending flexible endoscopic instrument for the diagnosis and treatment of early gastric cancer. This instrument has a compact structure with a maximum outer diameter of 3mm and an insertion length of 1220mm. It has 5 DOFs with a dual-bending function, which can form a surgical operation triangulation to easily perform the endoscopic procedure. Apart from the surgical forceps, the end of the instrument can be equipped with different endoscopic devices to meet the needs of diagnosis and treatment, such as endomicroscopic probes, electrosurgical knives, and laser ablation optical fibers. It is verified that the instrument can carry these devices to complete corresponding tasks, demonstrating the great potential of this instrument in clinical applications.

Extracellular vesicle biomarkers in circulation for the diagnosis of gastric cancer: A systematic review and meta‑analysis.

The prognosis of a gastric cancer (GC) diagnosis is poor due to the current lack of effective early diagnostic methods. Extracellular vesicle (EV) biomarkers have previously demonstrated strong diagnostic efficiency for certain types of cancer, including pancreatic and lung cancer. The present review aimed to summarize the diagnostic value of circulating EV biomarkers for early stage GC. The PubMed, Medline and Web of Science databases were searched from May 1983 to September 18, 2022. All studies that reported the diagnostic performance of EV biomarkers for GC were included for analysis. Overall, 27 studies were selected containing 2,831 patients with GC and 2,117 controls. A total of 58 EV RNAs were reported in 26 studies, including 39 microRNAs (miRNAs), 10 long non-coding RNAs (lncRNAs), five circular RNAs, three PIWI-interacting RNAs and one mRNA, in addition to one protein in the remaining study. Meta-analysis of the aforementioned studies demonstrated that the pooled sensitivity, specificity and AUC value of the total RNAs were 84, 67% and 0.822, respectively. The diagnostic values of miRNAs were consistent with the total RNA, as the pooled sensitivity, specificity and AUC value were 84, 67% and 0.808, respectively. The pooled sensitivity, specificity and AUC values of lncRNAs were 89, 69% and 0.872, respectively, markedly higher compared with that of miRNAs. A total of five studies reported the diagnostic performance of EV RNA panels for early stage GC and reported powerful diagnostic values with a pooled sensitivity, specificity and AUC value of 80, 77% and 0.879, respectively. Circulating EV RNAs could have the potential to be used in the future as effective, noninvasive biomarkers for early GC diagnosis. Further research in this field is necessary to translate these findings into clinical practice.

E-learning system to improve the endoscopic diagnosis of early gastric cancer.

We developed three e-learning systems for endoscopists to acquire the necessary skills to improve the diagnosis of early gastric cancer (EGC) and demonstrated their usefulness using randomized controlled trials. The subjects of the three e-learning systems were "detec-tion", "characterization", and "preoperative assessment". The contents of each e-learning system included "technique", "knowledge", and "obtaining experience". All e-learning systems proved useful for endoscopists to learn how to diagnose EGC. Lecture videos describing "the technique" and "the knowledge" can be beneficial. In addition, repeating 100 self-study cases allows learners to gain "experience" and improve their diagnostic skills further. Web-based e-learning systems have more advantages than other teaching methods because the number of participants is unlimited. Histopathological diagnosis is the gold standard for the diagnosis of gastric cancer. Therefore, we developed a comprehensive diagnostic algorithm to standardize the histopathological diagnosis of gastric cancer. Once we have successfully shown that this algorithm is helpful for the accurate histopathological diagnosis of cancer, we will complete a series of e-learning systems designed to assess EGC accurately.

Application of serum gastric function markers and digestive tumor indices to the diagnosis of early gastric cancer and precancerous lesions.

To study the levels of carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 199, CA724, CA242, pepsinogen (PG) I, PGII, gastrin-17 (G-17), the PGI/PGII ratio (PGR), as well as the expression of p27 and Ki67, in patients suffering from early gastric cancer and intraepithelial neoplasia and to provide new markers for the diagnosis of early gastric cancer and precancerous lesions. A retrospective study where the blood serum concentration of CEA, CA199, CA724, CA242, PGI, PGII, G-17 and PGR were tested and also the protein expression of p27 and Ki67 was detected in patients tissues by immunohistochemistry in the Gastrointestinal Endoscopy Center of the Affiliated Hospital of Xuzhou Medical University, Xuzhou, China, from March 2018 to March 2021. Carbohydrate antigen 242 and CA199 levels in tumor tissue significantly differed among the groups. Pepsinogen I levels decreased with increasing disease severity, G-17 levels increased with the aggravation of severity, and p27 expression decreased with the severity. The combination of serum gastric function markers (PGI and G-17) and p27 digestive tumor indices can serve as markers for the diagnosis of early gastric cancer and intraepithelial neoplasia.

Gastric Foveolar-type Adenocarcinoma with Raspberry-like Appearance in a Helicobacter pylori-uninfected Stomach: A Long-term Retrospective Follow-up of 16 Years.

Esophagogastroduodenoscopy in a 58-year-old man revealed a protruding lesion measuring 6 mm in diameter in the fornix. An endoscopic biopsy of the lesion indicated well-differentiated adenocarcinoma.The lesion was resected by polypectomy. According to the Japanese histologic diagnostic criteria, we made a final diagnosis of early gastric cancer (U, Gre, 6×6 mm,Type 0-I, tub1, pT1a (M), pUl0, Ly0, V0, pHM0, pVM0). A retrospective review of the endoscopic images showed that this lesion had already been present in the images taken 16 years ago. The size and morphology of the lesion were the same as those of the first detected lesion.

The Pink Zone Pattern (PP) sign: A novel simple marker for early gastric cancer.

We previously found a pink-colored change in early gastric cancer (EGC) lesions under magnifying endoscopy with narrow-band imaging (ME-NBI) and named it the "Pink Zoon Pattern" (PP) sign, which appeared independent of microvascular and microstructural changes. The aim of this study was to further investigate the characteristics of the PP sign in EGC. The consecutive patients with suspicious gastric lesions detected by ME-NBI and confirmed by pathology at Zhejiang Cancer Hospital between November 2020 and December 2021 were enrolled in the study. The suspicious lesions were observed and assessed by the "VS" system and the PP sign respectively. We found that in the PP-positive group, 238 lesions (96.0%) were diagnosed as malignant. The overall accuracy, sensitivity, and specificity were 84.7%, 85.3%, and 81.8%. Among 164 EGC lesions diagnosed with low confidence (Grades 2, 3, and 4) using the VS system, the overall accuracy of PP to discriminate tumor from normal was 82.3%. The sensitivity and specificity were 82.7% and 81.5% respectively. The PP sign could be a new simple sign for the diagnosis of EGC and as an effective supplement to VS system when using ME-NBI.

Risk and prediction of multiple primary malignancies after early gastric cancer.

Patients with early gastric cancer have increased risk of developing multiple primary malignancies (MPM) due to improved survival rates. The purpose of this study was to evaluate the clinicopathological features of MPM and to generate a useful tool for predicting the development of MPM after early gastric cancer. We selected 1025 early gastric cancer patients with complete medical records for a retrospective analysis. The Cox proportional risk regression model was used to analyze the independent risk factors for the development of MPM in early gastric cancer. RStudio software was used to compare the OS of early gastric cancer patients with and without MPM, and a nomogram was established to predict the probability of MPM 1-, 2-, 3-year after early gastric cancer. The predictive effectiveness of the nomogram was evaluated by the C-index and calibration curve. Decision curve analysis (DCA) measured the applicability of the nomogram to clinical practice. Of the 1025 patients with early gastric cancer, 66 patients (6.4%) had 69 primary cancers other than early gastric cancer. They had a median follow-up of 41 months, and their cumulative incidence of MPM was 4.9%, 5.4% and 5.9% after 1-, 2-, and 3- year, respectively. Oesophageal cancer was the most frequently detected MPM, followed by lung and colorectal cancers. Male (p=0.038), age ≥65 years (p=0.003), smoking history (p=0.036), and lymph node metastasis (p=0.013) were independent risk factors for MPM in patients with early gastric cancer. Patients with early gastric cancer with MPM had a worse OS prognosis than patients with early gastric cancer without MPM (p<0.001). The internally validated nomogram predicted the probability of developing MPM after early gastric cancer (C index= 0.697). The calibration chart showed that the predicted probability of MPM in early gastric cancer was similar to the observed result, and the DCA showed strong clinical practicability. After the diagnosis and treatment of early gastric cancer, we should be alert to the possibility of MPM and perform regular and careful monitoring.

Characteristic analysis of early gastric cancer after Helicobacter pylori eradication: a multicenter retrospective propensity score-matched study

Background Helicobacter pylori (H. pylori) is recognized as a type I carcinogen in gastric cancer (GC). However, GC still occurs after H. pylori eradication, and its diagnosis is more complicated. This study aimed to summarize the characteristics of early GC (EGC) after H. pylori eradication to help accurately identify EGC and avoid missed diagnosis and misdiagnosis. Methods A total of 81 patients of EGC after H. pylori eradication (Hp-eradicated group), resected by endoscopic submucosal dissection (ESD), and 105 cases of H. pylori infection-related EGC (control group) were assessed. After propensity-score matching, the clinical characteristics, endoscopic manifestations, and histopathological features of the 62 matched patients in each group were analyzed. We also conducted specific analyses in combination with endoscopic and histopathological images. Results There were more patients in the Hp-eradicated group who received proton pump inhibitor (PPI) for >1 year compared to the control group (p < 0.001). More patients at OLGA stages I-II before the diagnosis of EGC were in the control group (p = 0.045), especially at stage II. The mucosa in the Hp-eradicated group showed more moderate-to-severe atrophy (p = 0.047), map-like redness (p < 0.001) and mild activity (p < 0.001). The predominant histopathological types differed between the two groups (p < 0.001), and the majority of cases in the Hp-eradicated group were high-grade intraepithelial neoplasia (HGIN). Ki-67 expression was lower in the Hp-eradicated group (p = 0.025). But different eradication intervals of H. pylori have little effect on the characteristics of EGC. Furthermore, PPI uses for >1 year (p = 0.005), mucosal map-like redness (p < 0.001), moderate mucosal atrophy (p = 0.017), and mild activity of gastric mucosa (p = 0.005) were independent characteristics of EGC after H. pylori eradication. Conclusion Our multicenter study revealed that EGC after H. pylori eradication was characterized by long-term PPI use, moderate mucosal atrophy, mucosal map-like redness, the mild activity of gastric mucosa, a higher proportion of HGIN cases, and lower levels of Ki-67.

Transfer RNA-derived fragments as novel biomarkers of the onset and progression of gastric cancer.

Gastric cancer (GC) is a particularly malignant disease; thus, early diagnosis and treatment are especially important. Transfer RNA-derived small RNAs (tsRNAs) have been implicated in the onset and progression of various cancers. Therefore, the aim of this study was to explore the role of tRF-18-79MP9P04 (previously named tRF-5026a) in the onset and progression of GC. Expression levels of tRF-18-79MP9P04 were quantified in gastric mucosa specimens of healthy controls and plasma samples of patients with different stages of GC. The results showed that plasma levels of tRF-18-79MP9P04 were significantly decreased in the early and advanced stages of GC. The results of the nucleocytoplasmic separation assay found that tRF-18-79MP9P04 was localized in the nuclei of GC cells. High-throughput transcriptome sequencing identified genes regulated by tRF-18-79MP9P04 in GC cells, and the function of tRF-18-79MP9P04 was predicted by bioinformatics. Collectively, the findings of this study suggest that tRF-18-79MP9P04 would be useful as non-invasive biomarker for early diagnosis of GC and is related to cornification, the type I interferon signaling pathway, RNA polymerase II activities, and DNA binding.

Artificial intelligence in theranostics of gastric cancer, a review.

Gastric cancer (GC) is one of the commonest cancers with high morbidity and mortality in the world. How to realize precise diagnosis and therapy of GC owns great clinical requirement. In recent years, artificial intelligence (AI) has been actively explored to apply to early diagnosis and treatment and prognosis of gastric carcinoma. Herein, we review recent advance of AI in early screening, diagnosis, therapy and prognosis of stomach carcinoma. Especially AI combined with breath screening early GC system improved 97.4 % of early GC diagnosis ratio, AI model on stomach cancer diagnosis system of saliva biomarkers obtained an overall accuracy of 97.18 %, specificity of 97.44 %, and sensitivity of 96.88 %. We also discuss concept, issues, approaches and challenges of AI applied in stomach cancer. This review provides a comprehensive view and roadmap for readers working in this field, with the aim of pushing application of AI in theranostics of stomach cancer to increase the early discovery ratio and curative ratio of GC patients.

Immunology and immunotherapy in gastric cancer.

Gastric cancer is the fifth leading cause of cancer-related deaths worldwide. As the diagnosis of early gastric cancer is difficult, most patients are at a late stage of cancer progression when diagnosed. The current therapeutic approaches based on surgical or endoscopic resection and chemotherapy indeed improve patients' outcomes. Immunotherapy based on immune checkpoint inhibitors has opened a new era for cancer treatment, and the immune system of the host is reshaped to combat tumor cells and the strategy differs according to the patient's immune system. Thus, an in-depth understanding of the roles of various immune cells in the progression of gastric cancer is beneficial to application for immunotherapy and the discovery of new therapeutic targets. This review describes the functions of different immune cells in gastric cancer development, mainly focusing on T cells, B cells, macrophages, natural killer cells, dendritic cells, neutrophils as well as chemokines or cytokines secreted by tumor cells. And this review also discusses the latest advances in immune-related therapeutic approaches such as immune checkpoint inhibitors, CAR-T or vaccine, to reveal potential and promising strategies for gastric cancer treatment.

Bioinformatic analysis of hub markers and immune cell infiltration characteristics of gastric cancer.

Gastric cancer (GC) is the fifth most common cancer and the second leading cause of cancer-related deaths worldwide. Due to the lack of specific markers, the early diagnosis of gastric cancer is very low, and most patients with gastric cancer are diagnosed at advanced stages. The aim of this study was to identify key biomarkers of GC and to elucidate GC-associated immune cell infiltration and related pathways. Gene microarray data associated with GC were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were analyzed using Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia, Gene Set Enrichment Analysis (GSEA) and Protein-Protein Interaction (PPI) networks. Weighted gene coexpression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to identify pivotal genes for GC and to assess the diagnostic accuracy of GC hub markers using the subjects' working characteristic curves. In addition, the infiltration levels of 28 immune cells in GC and their interrelationship with hub markers were analyzed using ssGSEA. And further validated by RT-qPCR. A total of 133 DEGs were identified. The biological functions and signaling pathways closely associated with GC were inflammatory and immune processes. Nine expression modules were obtained by WGCNA, with the pink module having the highest correlation with GC; 13 crossover genes were obtained by combining DEGs. Subsequently, the LASSO algorithm and validation set verification analysis were used to finally identify three hub genes as potential biomarkers of GC. In the immune cell infiltration analysis, infiltration of activated CD4 T cell, macrophages, regulatory T cells and plasmacytoid dendritic cells was more significant in GC. The validation part demonstrated that three hub genes were expressed at lower levels in the gastric cancer cells. The use of WGCNA combined with the LASSO algorithm to identify hub biomarkers closely related to GC can help to elucidate the molecular mechanism of GC development and is important for finding new immunotherapeutic targets and disease prevention.

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis.

Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis. Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively. KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.

Research Progress on the Relationship between Gastric Microorganisms and the Occurrence and Development of Gastric Cancer

The changes of composition and function of gastric microflora are closely related to the occurrence and development of gastric cancer (Gastriccancer, GC). Gastric microflora has great potential as a biomarker for diagnosis and risk assessment of gastric cancer. There is a complex flora structure in the stomach. The changes of gastric microenvironment caused by Helicobacter pylori (H. pylori HP) may change the flora structure and mainly participate in the early process of gastric carcinogenesis. Gastric microflora other than Helicobacter pylori may play a role in the last steps of gastric carcinogenesis. Exploring the mechanism of gastric microorganisms in the occurrence and development of gastric cancer is helpful to provide a basis for early diagnosis and treatment of gastric cancer. This article mainly reviews the role of Helicobacter pylori and other microorganisms in the occurrence and development of gastric cancer.

Computer-aided demarcation of early gastric cancer: a pilot comparative study with endoscopists.

Precise area diagnosis of early gastric cancer (EGC) is critical for reliable endoscopic resection. Computer-aided diagnosis (CAD) shows strong potential for detecting EGC and reducing cancer-care disparities caused by differences in endoscopists' skills. To be used in clinical practice, CAD should enable both the detection and the demarcation of lesions. This study proposes a scheme for the detection and delineation of EGC under white-light endoscopy and validates its performance using 1-year consecutive cases. Only 300 endoscopic images randomly selected from 68 consecutive cases were used for training a convolutional neural network. All cases were treated with endoscopic submucosal dissection, enabling the accumulation of a training dataset in which the extent of lesions was precisely determined. For validation, 462 cancer images and 396 normal images from 137 consecutive cases were used. From the validation results, 38 randomly selected images were compared with those delineated by six endoscopists. Successful detections of EGC in 387 cancer images (83.8%) and the absence of lesions in 307 normal images (77.5%) were achieved. Positive and negative predictive values were 81.3% and 80.4%, respectively. Successful detection was achieved in 130 cases (94.9%). We achieved precise demarcation of EGC with a mean intersection over union of 66.5%, showing the extent of lesions with a smooth boundary; the results were comparable to those achieved by specialists. Our scheme, validated using 1-year consecutive cases, shows potential for demarcating EGC. Its performance matched that of specialists; it might therefore be suitable for clinical use in the future.

Metabolomic profiling of plasma reveals potential biomarkers for screening and early diagnosis of gastric cancer and precancerous stages

AbstractGastric cancer (GC) faces a great challenge in clinical diagnosis, that it often is detected at advanced stages and there is a loss of optimum time for treatment. Thus, it is necessary to develop effective strategies for diagnosis of GC. In this study, 82 participants were enrolled, including 50 chronic superficial gastritis (CSG) patients, 7 early gastric cancer (EGC), and 25 advanced gastric cancer (AGC) ones. Metabolites profiling on patient plasma was performed. Furthermore, the proposed biomarkers were used to create random forest models, in which discrimination efficiency and accuracy were ascertained by receiver operating characteristic (ROC) curve analysis. l‐carnitine, l‐proline, pyruvaldehyde, phosphatidylcholines (PC) (14:0/18:0), lysophosphatidylcholine (14:0) (LysoPC 14:0), lysinoalanine were defined as the potential biomarker panel for the diagnosis among CSG and EGC patients. Compared with EGC patients, PC(O‐18:0/0:0) and LysoPC(20:4(5Z,8Z,11Z,14Z)) were found to be upregulated in AGC patients, whereasl‐proline, l‐valine, adrenic acid, and pyruvaldehyde downregulated. Pathway analysis revealed several metabolism disorders, involving amino acids and lipid metabolism. ROC analysis demonstrated a high diagnostic performance in disease diagnosis between CSG and GC. The above results indicate that the biomarker panels are sensitive to early diagnosis of GC disease, which is expected to be a promising diagnostic tool for disease stratification studies.

Diagnostic Utility of NLR, PLR and MLR in Early Diagnosis of Gastric Cancer: an Analytical Cross-Sectional Study.

Inflammatory markers such as neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR) are linked with the pathogenesis of gastric cancer (GC). However, the clinical significance of the combination of these markers is unclear. Hence, this study was carried out to determine the individual and combined diagnostic accuracy of NLR, PLR and MLR among patients with GC. In this prospective, cross-sectional study, patients were recruited into three groups, GC, precancerous lesions and age and gender-matched controls. The primary outcome was to determine the diagnostic accuracy of inflammatory markers in the diagnosis of GC. The secondary outcome was to determine the correlation of inflammatory markers with the stage of gastric cancer, nodal involvement and metastasis. A total of 228 patients, 76 in each group, were enrolled. The cut-off value of NLR, PLR and MLR were 2.23, 146.8 and 0.26, respectively, for the diagnosis of GC. The diagnostic abilities of NLR, PLR and MLR were significantly high at 79, 75 and 68.4, respectively, to predict GC compared to precancerous and control groups. All the models of inflammatory markers showed excellent discrimination between GC and the controls with an AUC > 0.7. The models also showed acceptable discrimination between GC and the precancerous lesion group with AUC between 0.65 and 0.70. No significant difference was found in correlating inflammatory markers with clinicopathological features. The discrimination capacity of the inflammatory markers could be used as screening biomarkers in diagnosing GC, even in its early stages.

Screening and Study of Aptamer Based on Gastric Cancer Cell Culture Medium

AbstractGastric Cancer (GC) is one of the fifth most malignant tumors in the world and the third leading cause of cancer‐related deaths. At present, one of the methods to diagnose gastric cancer patients is screening for gastric cancer tumor markers. However, the specificity and detection rate of existing tumor markers are low. Aptamer, also known as chemical antibody, is a kind of single‐stranded oligonucleotide (DNA or RNA) obtained by SELEX. It is widely used in the diagnosis of new diseases and as a molecular probe for treatment. This study used Med‐SELEX technology, using agarose magnetic beads as the carrier, and cancer culture medium as the screening target. APT‐1 specific to gastric cancer cell culture medium was screened out from random library through q‐PCR real‐time monitoring and screening process, and its affinity and specificity for gastric cancer serum were verified by subsequent q‐PCR and quantum dot methods. Serum stability test and cytotoxicity test proved its practicability. APT‐1 is not only of great significance for the early diagnosis of gastric cancer and the construction of targeted drug delivery system for gastric cancer, but also may be used as a probe to discover new tumor markers for gastric cancer.