Practical Points in Gastric Pathology

The tumor immune microenvironment remodeling and response to HER2-targeted therapy in HER2-positive advanced gastric cancer

Combination therapy with anti-HER2 agents and immunotherapy has demonstrated significant clinical benefits in gastric cancer (GC), but the underlying mechanism remains unclear. In this study, we used multiplex immunohistochemistry to assess the changes of the tumor microenvironment in 47 advanced GC patients receiving anti-HER2 therapy. Additionally, we performed single-cell transcriptional sequencing to investigate potential cell-to-cell communication and molecular mechanisms in four HER2-positive GC baseline samples. We observed that post-treated the infiltration of NK cells, CD8+ T cells, and B lymphocytes were significantly higher in patients who benefited from anti-HER2 treatment than baseline. Further spatial distribution analysis demonstrated that the interaction scores between NK cells and CD8+ T cells, B lymphocytes and M2 macrophages, B lymphocytes and Tregs were also significantly higher in benefited patients. Cell-cell communication analysis from scRNA sequencing showed that NK cells utilized CCL3/CCL4-CCR5 to recruit CD8+ T cell infiltration. B lymphocytes employed CD74-APP/COPA/MIF to interact with M2 macrophages, and utilized TNF-FAS/ICOS/TNFRSR1B to interact with Tregs. These cell-cell interactions contribute to inhibit the immune resistance of M2 macrophages and Tregs. Our research provides potential guidance for the use of anti-HER2 therapy in combination with immune therapy.

SERPINB5 is a novel serum diagnostic biomarker for gastric high-grade intraepithelial neoplasia and plays a role in regulation of macrophage phenotypes

BACKGROUND

Gastric cancer (GC) develops from gastric precancerous lesions (GPL), and early diagnosis and treatment at the premalignant stage may achieve a higher benefit‒cost ratio with a reduced necessity for surgery. However, reliable noninvasive screening biomarkers of GPL are currently lacking.

METHODS

The marker genes of GPL encoding extracellular proteins were identified by bioinformatics analysis and further verified by immunofluorescence and immunohistochemistry assays. Serum samples were collected to measure the levels of SERPINB5, the diagnostic efficacy of which was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Finally, the effect of SERPINB5 on the phenotypic conversion of macrophages was verified by public data and in vitro experiments.

RESULTS

SERPINB5 was identified as an extracellular biomarker of GPL that had good diagnostic efficacy. High expression of SERPINB5 was observed in the epithelial cells and adjacent extracellular matrix on sections of gastric high-grade intraepithelial neoplasia (HGIN). Importantly, SERPINB5 determined in serum was significantly increased in the HGIN group, and the AUC for discriminating between HGIN and chronic gastritis or low-grade intraepithelial neoplasia was 0.9936 and 0.9750, respectively. Moreover, SERPINB5 expression was positively correlated with macrophage infiltration, and M1 marker NOS2 expression, but negatively correlated with M2 marker CSF1R expression. In THP-1-derived macrophages, SERPINB5 upregulated expression of M1-related cytokines TNF-α and IL-12, and M1 marker CD86, but suppressed production of M2-related cytokines TGF-β and IL-10.

CONCLUSIONS

Our study provides evidence that SERPINB5 may serve as a promising noninvasive serum biomarker for gastric HGIN screening and regulate macrophage phenotype conversion.

Euclidean distance-based Raman spectroscopy (EDRS) for the prognosis analysis of gastric cancer: A solution to tumor heterogeneity

The prognosis analysis of gastric cancer is critical for selection of treatments and development of advanced therapeutic methods. A prognosis approach that is accurate, fast, convenient, and of low cost for gastric cancers is in high demand. Raman spectroscopy is a label-free and non-destructive technique to provide molecular fingerprints of biological samples, holding promises for cancer prognosis. However, the major challenge of gastric cancer prognosis lies in the widely existing tumor heterogeneity, which leads to unexpected spectral variations within one type of samples. In this work, we have developed the Euclidean distance (ED)-based Raman spectroscopy (EDRS) method for the prognosis analysis of gastric cancer to eliminate the influence of tumor heterogeneity. Raman spectra were first collected on the slices of paraffin-preserved tumor tissues from gastric cancer patients. A standard spectrum to represent the 'worst prognostic tumor cells' was then established. The similarity between each spectrum of tissues and the standard spectrum was assessed by ED, to provide a direct assessment on the prognosis status. We have successfully classified the patients into poor and favorable prognosis groups, either based on the averaged regional ED values (sensitivity of 75 %, specificity of 96.8 %), or based on the minimal ED values at the patient level (sensitivity of 90 %, specificity of 100 %). EDRS was also investigated for survival analysis (AUC = 0.955), much better than the commonly applied post-neoadjuvant therapy (ypTNM) category (AUC = 0.718). Our work highlights EDRS as a rapid, accurate, low-cost and robust tool for heterogeneous cancer-related prognosis assessment and survival prediction, providing new insights for spectroscopic tumor analysis.

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.

Identification of Hub Genes and Pathways in Gastric Adenocarcinoma Based on Bioinformatics Analysis

BACKGROUND Gastric adenocarcinoma accounts for 95% of all gastric malignant tumors. The purpose of this research was to identify differentially expressed genes (DEGs) of gastric adenocarcinoma by use of bioinformatics methods. MATERIAL AND METHODS The gene microarray datasets of GSE103236, GSE79973, and GSE29998 were imported from the GEO database, containing 70 gastric adenocarcinoma samples and 68 matched normal samples. Gene ontology (GO) and KEGG analysis were applied to screened DEGs; Cytoscape software was used for constructing protein-protein interaction (PPI) networks and to perform module analysis of the DEGs. UALCAN was used for prognostic analysis. RESULTS We identified 2909 upregulated DEGs (uDEGs) and 7106 downregulated DEGs (dDEGs) of gastric adenocarcinoma. The GO analysis showed uDEGs were enriched in skeletal system development, cell adhesion, and biological adhesion. KEGG pathway analysis showed uDEGs were enriched in ECM-receptor interaction, focal adhesion, and Cytokine-cytokine receptor interaction. The top 10 hub genes - COL1A1, COL3A1, COL1A2, BGN, COL5A2, THBS2, TIMP1, SPP1, PDGFRB, and COL4A1 - were distinguished from the PPI network. These 10 hub genes were shown to be significantly upregulated in gastric adenocarcinoma tissues in GEPIA. Prognostic analysis of the 10 hub genes via UALCAN showed that the upregulated expression of COL3A1, COL1A2, BGN, and THBS2 significantly reduced the survival time of gastric adenocarcinoma patients. Module analysis revealed that gastric adenocarcinoma was related to 2 pathways: including focal adhesion signaling and ECM-receptor interaction. CONCLUSIONS This research distinguished hub genes and relevant signal pathways, which contributes to our understanding of the molecular mechanisms, and could be used as diagnostic indicators and therapeutic biomarkers for gastric adenocarcinoma.

Inter-observer Reproducibility in the Pathologic Diagnosis of Gastric Intraepithelial Neoplasia and Early Carcinoma in Endoscopic Submucosal Dissection Specimens: A Multi-center Study

PURPOSE

The diagnostic criteria of gastric intraepithelial neoplasia (IEN) are controversial across the world. We investigated how many discrepancies occur in the pathologic diagnosis of IEN and early gastric carcinoma in endoscopic submucosal dissection (ESD) specimens, and evaluated the reasons of the discordance.

Materials and Methods

We retrospectively reviewed 1,202 ESD specimens that were originally diagnosed as gastric IEN and early carcinoma at 12 institutions.

RESULTS

The final consensus diagnosis of carcinoma were 756 cases, which were originally 692 carcinomas (91.5%), 43 high-grade dysplasias (5.7%), 20 low-grade dysplasias (2.6%), and 1 others (0.1%), respectively. High- and low-grade dysplasia were finally made in 63 and 342 cases, respectively. The diagnostic concordance with the consensus diagnosis was the highest for carcinoma (91.5%), followed by low-grade dysplasia (86.3%), others (63.4%) and high-grade dysplasia (50.8%). The general kappa value was 0.83, indicating excellent concordance. The kappa values of individual institutions ranged from 0.74 to 1 and correlated with the proportion of carcinoma cases. The cases revised to a final diagnosis of carcinoma exhibited both architectural abnormalities and cytologic atypia. The main differential points between low- and high-grade dysplasias were the glandular distribution and glandular shape. Additional features such as the glandular axis, surface maturation, nuclear stratification and nuclear polarity were also important.

CONCLUSION

The overall concordance of the diagnosis of gastric IEN and early carcinoma in ESD specimens was excellent. It correlated with the proportion of carcinoma cases, demonstrating that the diagnostic criteria for carcinoma are more reproducible than those for dysplasia.

Involvement of the anti-inflammatory, anti-apoptotic, and anti-secretory activity of bee venom in its therapeutic effects on acetylsalicylic acid-induced gastric ulceration in rats

Acetylsalicylic acid (ASA) is the most highly consumed pharmaceutical product worldwide. Importantly, gastrointestinal ulceration due to ASA is a major complication. Hence, the present work aimed to examine, for the first time, the healing properties of bee venom (BV) in acute gastric ulceration induced by ASA. Forty adult male Sprague-Dawley rats were divided into four groups that received distilled water only, ASA (500 mg/kg BW) twice daily for 3 days, ASA for 3 days followed by BV (2 mg/kg BW) for 7 days, or ASA for 3 days followed by ranitidine hydrochloride (50 mg/kg BW) for 7 days. Haematological analysis, haemostatic evaluation, and inflammatory marker estimation were performed. Rat stomachs were collected for ulcer scoring, gene expression analysis, oxidative stress assays, histopathological and immunohistochemical examinations, and tissue eosinophil scoring. The results revealed that BV markedly decreased the ulcer index, pro-inflammatory cytokine levels, malondialdehyde levels, BAX distribution, caspase-3 expression, and tissue eosinophil levels. Additionally, significant increases in antioxidant enzymes and heat shock protein 70 localization in gastric tissue were evident following BV treatment after ASA exposure. Also, BV has been found to attenuate the haematological, haemostatic, and histopathological alterations induced by ASA. Our findings collectively indicate that the gastroprotective effect of BV against ASA-induced ulceration in rats is mediated by its antioxidant, anti-inflammatory, anti-apoptotic, and anti-secretory properties.

Multiple cytokine profiling in serum for early detection of gastric cancer

AIM

To investigate the value of multiparameter joint analysis in the early diagnosis of gastric cancer (GC) in clinical practice.

METHODS

Concentrations of CEA, CA724 and three kinds of cytokines (TNF-α, IL-6 and IL-8) in 176 GC patients, 117 atypical hyperplasia patients, and 204 healthy control individuals were used for building the diagnostic model, then 58 GC patients, 41 atypical hyperplasia patients, and 66 healthy control individuals were enrolled independently. The joints of the indicators were analyzed by binary logistic regression analysis method.

RESULTS

For discriminating the healthy control group and the GC group, IL-6 had the best diagnostic value, and the area under curve (AUC) of joint analysis was 0.95 (0.93-0.97). For the early stage and advanced stage GC, the AUC were 0.95 (0.92-0.98) and 0.95 (0.92-0.97). For discriminating the atypical hyperplasia group and GC group, CA724 had the best diagnostic value, and the AUC of joint analysis was 0.97 (0.95-0.99). For the early stage and advanced stage GC groups, the AUC were 0.98 (0.96-0.99) and 0.96 (0.94-0.98). After evaluation, for discriminating the GC, early stage GC and advanced cancer group from the healthy control group, the diagnostic sensitivity was 89.66%, 84.21% and 92.31%, respectively, and the specificity was 92.42%, 90.91% and 90.91%. For discriminating the GC, early stage GC and advanced cancer groups from the atypical hyperplasia group, the diagnostic sensitivity was 87.93%, 78.95% and 92.31%, respectively, and the specificity was 87.80%, 85.37% and 90.24%.

CONCLUSION

We have built a diagnostic model including CEA, CA724, IL-6, IL-8, and TNF-α. It may provide potential assistance as a screening method for the early detection of GC.

Automated histological classification of whole-slide images of gastric biopsy specimens

BACKGROUND

Automated image analysis has been developed currently in the field of surgical pathology. The aim of the present study was to evaluate the classification accuracy of the e-Pathologist image analysis software.

METHODS

A total of 3062 gastric biopsy specimens were consecutively obtained and stained. The specimen slides were anonymized and digitized. At least two experienced gastrointestinal pathologists evaluated each slide for pathological diagnosis. We compared the three-tier (positive for carcinoma or suspicion of carcinoma; caution for adenoma or suspicion of a neoplastic lesion; or negative for a neoplastic lesion) or two-tier (negative or non-negative) classification results of human pathologists and of the e-Pathologist.

RESULTS

Of 3062 cases, 33.4% showed an abnormal finding. For the three-tier classification, the overall concordance rate was 55.6% (1702/3062). The kappa coefficient was 0.28 (95% CI, 0.26-0.30; fair agreement). For the negative biopsy specimens, the concordance rate was 90.6% (1033/1140), but for the positive biopsy specimens, the concordance rate was less than 50%. For the two-tier classification, the sensitivity, specificity, positive predictive value, and negative predictive value were 89.5% (95% CI, 87.5-91.4%), 50.7% (95% CI, 48.5-52.9%), 47.7% (95% CI, 45.4-49.9%), and 90.6% (95% CI, 88.8-92.2%), respectively.

CONCLUSIONS

Although there are limitations and requirements for applying automated histopathological classification of gastric biopsy specimens in the clinical setting, the results of the present study are promising.