External validation of a modified 8th AJCC TNM system for advanced gastric cancer: Long-term results in southern China

Prognostic significance of lymphovascular invasion in pN0 stage gastric cancer: a propensity score matching analysis

BACKGROUND

To explore the potential impact of lymphovascular invasion (LVI) on overall survival (OS) of pN0 stage gastric cancer (GC) after curative resection.

METHODS

A total of 497 GC patients who underwent curative gastrectomy and postoperative pathology proved negative lymph node metastasis between January 2015 and December 2018 in our center were enrolled in this study. All patients were divided into two groups according to the status of LVI. Their clinical and pathological features were compared and potential prognostic factors were analyzed using the propensity score matching analysis (PSM).

RESULTS

Ninety-nine (19.9%) patients had LVI. The presence of LVI was associated with significantly worse survival outcomes in both the overall and PSM cohorts (χ2 = 19.635, p < 0.001; χ2 = 9.367, p = 0.002). After PSM, data of 99 pairs of patients were extracted. Multivariate analysis revealed that number of examined lymph nodes (LNs), and LVI were independent predictors of OS (all p < 0.05). Following stratified analysis, patients with LNs 11-25 and those without LVI tended to have better OS than those with LVI (LNs 11-15: χ2 = 5.019, p = 0.025; LNs 16-25: χ2 = 11.876, p = 0.001).

CONCLUSIONS

pN0 stage GC patients with LVI have poor prognosis. More than 15 lymph nodes need to be dissected to reduce the influence of LVI on the prognosis of pN0 stage GC patients.

The comparison of clinicopathological characteristics of two distinct manifestations of gastric signet ring cell carcinoma under EUS

Background and Objectives

There are two different endoscopic ultrasonographic manifestations of gastric signet ring cell carcinoma (GSRCC). No studies have been reported on the differences in the clinical profiles of patients based on EUS examination. We aim to study the variations in clinicopathological characteristics between two distinct endoscopic ultrasonographic manifestations of GSRCC.

Methods

A total of 302 patients with GSRCC confirmed by pathological examination who underwent EUS were enrolled in the study. Based on the endoscopic ultrasonographic features, patients were categorized into two groups: type 1, where the entire layer structure disappeared, and type 2, where the layer structure was still present and appeared lymphomatoid. Clinicopathologic features were collected retrospectively and analyzed.

Results

Compared with type 2 patients, type 1 patients tended to develop GSRCC at an older age (P = 0.033) and had higher serum levels of tumor markers and were more likely to experience anemia (P < 0.001) and weight loss (P < 0.001) during the disease progression. Significant increases in the tumor size (P < 0.001), thickness of the affected gastric wall (P < 0.001), and depth of tumor invasion (P < 0.001) were observed in type 1 patients. Furthermore, type 1 patients had higher prevalence of affected blood vessels (P < 0.001), nerves (P < 0.001), lymph nodes (P < 0.001), and peritoneal metastasis (P < 0.001). However, no difference was found in the duration of disease between the two groups, and all deficient mismatch repairs were observed in type 1 patients.

Conclusions

The two distinct endoscopic ultrasonographic manifestations of GSRCC exhibited different clinicopathological characteristics, suggesting that they may represent different subtypes of the disease that require special attention in management strategies.

Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer

OBJECTIVE

This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III).

METHODS

This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA).

RESULTS

A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility.

CONCLUSION

The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

A comprehensive radiopathological nomogram for the prediction of pathological staging in gastric cancer using CT-derived and WSI-based features

OBJECTIVE

This study aims to develop and validate an innovative radiopathomics model that combines radiomics and pathomics features to effectively differentiate between stages I-II and stage III gastric cancer (pathological staging).

METHODS

Our study included 200 patients with well-defined stages of gastric cancer divided into a training cohort (n = 140) and a test cohort (n = 60). Radiomics features were extracted from contrast-enhanced CT images using PyRadiomics, while pathomics features were obtained from whole slide images of pathological specimens through a fine-tuned deep learning model (ResNet-18). After rigorous feature dimensionality reduction and selection, we constructed radiomics models (SVM_rad, LR_rad, and MLP_rad) and pathomics models (SVM_path, LR_path, and MLP_path) utilizing support vector machine (SVM), logistic regression (LR), and multilayer perceptron (MLP) algorithms. The optimal radiomics and pathomics models were chosen based on comprehensive evaluation criteria such as ROC curves, Hosmer‒Lemeshow tests, and calibration curve tests. Feature patterns extracted from the best-performing radiomics model (MLP_rad) and pathomics model (SVM_rad) were integrated to create a powerful radiopathomics nomogram.

RESULTS

From a pool of 1834 radiomics features extracted from CT images, 14 were selected to construct radiomics models. Among these, the MLP_rad model exhibited the most robust predictive performance (AUC, training cohort: 0.843; test cohort: 0.797). Likewise, 10 pathomics features were chosen from 512 extracted from whole slide images to build pathomics models, with the SVM_path model demonstrating the highest predictive efficiency (AUC, training cohort: 0.937; test cohort: 0.792). The combined radiopathomics nomogram model exhibited optimal discriminative ability (AUC, training cohort: 0.951; test cohort: 0.837), as confirmed by decision curve analysis (DCA), which indicated superior clinical effectiveness.

CONCLUSION

This study presents a cutting-edge radiopathomics nomogram model designed to predict pathological staging in gastric cancer, distinguishing between stages I-II and stage III. Our research leverages preoperative CT images and histopathological slides to forecast gastric cancer staging accurately, potentially facilitating the estimation of staging before radical gastric cancer surgery in the future.

An analysis of the relationship of triglyceride glucose index with gastric cancer prognosis: A retrospective study

AIMS/INTRODUCTION

Gastric cancer, one of the most common malignant tumors worldwide, is affected by insulin resistance. The triglyceride glucose (TYG) index is considered a surrogate indicator of insulin resistance; however, its prognostic value in patients with gastric cancer remains obscure. This study aimed to determine whether the TYG index could predict the long-term prognosis of patients with gastric cancer after radical resection gastrectomy.

MATERIALS AND METHODS

We retrospectively analyzed patients with gastric cancer who underwent radical resection gastrectomy. The preoperative TYG index was calculated using the patients' laboratory data. Patients were divided into two groups based on a high or low TYG index. We observed overall survival and evaluated the clinical application value of the index using Cox proportional hazards regression to calculate independent parameters. A prediction model was also established.

RESULTS

In total, 822 patients with gastric cancer were included. The high and low TYG index groups comprised 353 and 469 patients, respectively. The overall survival time was significantly longer in the high-index group than in the low-index group. In the multivariate analysis, TYG index, preoperative age, surgical procedure, tumor node metastasis (TNM) stage, N stage, and postoperative complications (all p < 0.01) were considered independent prognostic predictors. Based on the multivariate analysis, the riglyceride glucose (TYG) index hazard ratio was 0.70 (95% confidence interval, 0.54-0.89, p = 0.004).

CONCLUSIONS

We established a model with a high clinical application value and clinical practice relevance to predict the prognosis of gastric cancer. In this model, TYG was an independent protective factor for gastric cancer prognosis.

Revisiting the 8th AJCC system for gastric cancer: A review on validations, nomograms, lymph nodes impact, and proposed modifications

Gastric cancer is the fifth most frequently diagnosed cancer worldwide, behind breast, lung, colorectal, and prostate cancers. In gastric cancer, multimodality treatment shows prospective benefits and also improves survival. Surgery, however, is the mainstay of curative treatment. The staging of gastric cancer patients is critical for harmonization of care. Accurate stages assure that informed clinical decisions are timely made. The American Joint Committee on Cancer (AJCC) staging system is the most widely applied system in to determine the disease's prognosis and survival prediction. The recently adopted 8th AJCC TNM staging system has been revised to enhance its survival predictive power. Subsequent studies have established the validity of the current edition, demonstrating improved stage stratification, discriminatory power, and survival prediction. However, other studies have cast doubt on the superiority of the new edition. Innovations aimed at further improving its prognosis have resulted in developing of novel models. Advances in our understanding of the tumor microenvironment and molecular categorization of cancer have resulted in proposals for their inclusion in TNM staging as potential complementary factors that enhance survival prediction and prognostic assessment ability. The purpose of this study is to conduct a review of the published literature regarding the validity of the 8th AJCC TNM staging system, proposed modifications, and nomograms.

•

The 8th AJCC is valid in prognostic stratification of gastric cancer, however, revisions are still required.

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The yPT staging requires some modifications and inclusion of stages that currently don't exist in the 8th AJCC.

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High lymph nodes count and anatomical localization improve the prediction ability of the current AJCC.

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Nomograms comprising of individual prognostic factors are crucial to the current AJCC.

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Molecular markers positively influence survival prediction of gastric cancer.

Development and external validation of a prognostic nomogram for patients with gastric cancer after radical gastrectomy

Background

Gastric cancer (GC) is one of the most malignant diseases and threatens the health of individuals across the globe. Hitherto, the identification of prognosis risk stratification on GC has mainly depended on the TNM staging, but owing to its inaccuracy and incompleteness, the prognostic value it offers remains controversial in the current clinical setting. Thus, an effective prognostic model for GC after radical gastrectomy is still needed.

Methods

Patients with pathologically confirmed GC who underwent radical gastrectomy from 2 different centers were retrospectively enrolled into a training and the validation cohort, respectively. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to select variables among multiple factors, including clinical characteristics, pathological parameters, and surgery- and treatment-related indicators. The multivariate Cox regression method was used to establish the model to predict 1-, 2-, and 3-year survival. Both internal and external validations of the nomogram were then completed in terms of discrimination, calibration, and clinical utility. Finally, prognostic risk stratification of GC was conducted with X-tile software.

Results

A total of 1,424 patients with GC were eligible in this study, including 1,010 in the training cohort and 414 in the validation cohort. Seven indicators were selected by LASSO to develop the nomogram, including the number of positive lymph nodes, tumor size, adjacent organ invasion, vascular invasion, the level of carbohydrate antigen 125 (CA 125), depth of invasion, and human epidermal growth factor receptor 2 (HER2) status. The nomogram demonstrated a robust predictive capacity with favorable accuracy, discrimination, and clinical utility both in the internal and external validations. Moreover, we divided the population into 3 risk groups of survival according to the cutoff points generated by X-tile, and in this way, the nomogram was further improved into a risk-stratified prognosis model.

Conclusions

We have developed a prognostic risk stratification nomogram for GC patients after radical gastrectomy with 7 available indicators that may guide clinical practice and help facilitate tailored decision-making, thus avoiding overtreatment or undertreatment and improving communication between clinicians and patients.

Pathologic Lymph Node Staging of Gastric Cancer

OBJECTIVES

The TNM classification is the main tool for lymph node (LN) staging in gastric cancer (GC). However, alternative LN staging systems have been proposed, and the role of features other than the number of metastatic LNs is being investigated. Our aim is to discuss the main challenges of LN assessment in GC.

METHODS

Comprehensive review of the literature on alternative LN staging systems, examined LNs, sentinel LN (SLN) biopsy, LN micrometastases (LNMIs), extracapsular extension (ECE), and tumor deposits (TDs) in GC.

RESULTS

Many controversies exist regarding LN assessment in GC. The TNM classification shows excellent prognostic performance, but alternative prognostic methods such as the LN ratio or log odds of positive LNs have demonstrated to be better than the TNM system in terms of prognostic accuracy. The value of SLN biopsy and LNMIs in GC is still unclear, and several challenges concerning their clinical impact and pathologic analysis must be overcome before their introduction in clinical practice. Most authors have identified ECE and TDs as independent prognostic factors for survival in GC.

CONCLUSIONS

Further studies should be performed to evaluate the impact of these features on the TNM classification and patient outcomes, as well as to standardize alternative LN staging systems.

The New American Joint Committee on Cancer T staging system for stomach: increased complexity without clear improvement in predictive accuracy for endoscopic ultrasound

BACKGROUND

The efficacy of endoscopic ultrasound (EUS) for determining the T category of gastric cancer is variable. The aim of this study was to evaluate the superiority of EUS by using the 6th edition American Joint Committee on Cancer (AJCC) staging system for stomach cancer compared to the new 7th/8th edition.

METHODS

A retrospective analysis of clinical and EUS imaging features of 348 gastric carcinoma patients who underwent radical resection were retrospectively analyzed. Differences between the 6th and 7th/8th edition T staging systems for preoperative EUS evaluation were compared.

RESULTS

The accuracy of EUS T staging was 72.4% for the 7th/8th edition and 78.4% for the 6th edition. T3 stage accuracy was significantly worse when the T3 group status was changed. The tumor location, echoendoscope type, and histological type were associated with inaccuracy. We further analyzed the EUS image features for each tumor T stage and found that an indistinctly visible muscularis propria (MP) or with obvious thickening was considered an indicator of lesions involved in the MP with a sensitivity of 81.3%; an MP completely disappeared and accompanied with a serosal layer intact may be a marker that the lesion invaded to the subserosa. We also found that irregularities in the outer edge of the gastric wall were markers of gastric serosal layer penetration with a positive predictive value of 92.2%.

CONCLUSIONS

The increased complexity of the 7th/8th edition T staging system is accompanied by worsening of the predictive accuracy for EUS as compared to the 6th edition. Furthermore, the tumor location, echoendoscope type, histological type, and EUS image features for each tumor T stage should warrant attention.

Multiple metabolic parameters and visual assessment of 18F-FDG uptake heterogeneity of PET/CT in advanced gastric cancer and primary gastric lymphoma

PURPOSE

Advanced gastric cancer (AGC) and primary gastric lymphoma (PGL) are the two most common malignant tumors of the stomach. Conventional imaging examinations have difficulty distinguishing the two. This study explored the values of multiple parameters and visual assessment of ¹⁸F-fluorodeoxyglucose(¹⁸F-FDG) uptake heterogeneity of positron emission tomography/computed tomography(PET/CT) for differentiating between AGC and PGL.

METHODS

This retrospective study included 70 AGC and 26 PGL patients, all of whom had undergone ¹⁸F-FDG PET/CT before treatment. We analyzed the differences between AGC and PGL in the distribution of metastatic lesions and multiple metabolic parameters, including the maximum standardized uptake value (SUVmax), SUVmax/maximal thickness(THKmax), metabolic tumor volume and total lesion glycolysis (TLG). In addition, ¹⁸F-FDG uptake heterogeneity was visually assessed using a visual scoring method and a method of measuring SUVmax differences (SUVmax-d).

RESULTS

The most common metastasis of AGC patients were liver, bone, peritoneal and proximal lymph nodes; PGL patients had fewer peritoneal metastases and lymph node metastasis could appeared to be "skip metastasis." The metabolic parameters-SUVmax, SUVmax/THKmax and TLG-were higher in patients who had PGL, especially in diffuse large B-cell lymphoma (DLBCL). In the visual assessment of ¹⁸F-FDG uptake heterogeneity, the measurements of SUVmax-d in PGL were significantly higher than in AGC. Receiver operating characteristics curve analysis suggested that SUVmax has the highest comprehensive diagnostic efficiency due to having the highest value of area under the curve and the highest accuracy (77.2%).

CONCLUSION

¹⁸F-FDG PET/CT had a high diagnostic efficiency for discrimination of AGC and PGL, especially between DLBCL and other pathological subtypes. Visual assessment used to evaluate ¹⁸F-FDG uptake heterogeneity could help to distinguish the two types of tumors. In addition, our innovative method of measuring the heterogeneity of ¹⁸F-FDG uptake-namely, SUVmax-d-could contribute to identification of the two tumor types and should have its significance clarified by future studies.

Diffuse Reduction of Spleen Density Is an Independent Predictor of Post-Operative Outcomes After Curative Gastrectomy in Gastric Cancer: A Multi-Center Study

Objectives: The present study aimed to explore the association between spleen density and post-operative outcomes of patients after curative gastrectomy.

Methods: From June 2014 to December 2015, we conducted a retrospective study to analyze pertinent clinical data from gastric cancer patients who underwent gastrectomy at the First and the Second Affiliated Hospital of Wenzhou Medical University. Spleen density was determined via computed tomography scans. Univariate and multivariate analyses were performed to determine the risk factors associated with post-operative outcomes after gastric cancer surgery.

Results: Three hundred and ninety five patients were included, of whom 98 (24.8%) were defined as having a diffuse reduction of spleen density based on diagnostic cutoff values (spleen density ≤43.89 HU). Multivariate analysis revealed diffuse reduction of spleen density as an independent risk factor for post-operative complications and long-term overall survival.

Conclusions: Spleen density can predict severe postoperative complications and long-term overall survival in gastric cancer patients. As an imaging evaluation method, spleen density is a novel tool can be used in clinical as a prognostic predictor for patients with gastric cancer.

Complement C3 overexpression activates JAK2/STAT3 pathway and correlates with gastric cancer progression

Background

Localized C3 deposition is a well-known factor of inflammation. However, its role in oncoprogression of gastric cancer (GC) remains obscured. This study aims to explore the prognostic value of C3 deposition and to elucidate the mechanism of C3-related oncoprogression for GC.

Methods

From August to December 2013, 106 GC patients were prospectively included. The regional expression of C3 and other effectors in gastric tissues were detected by WB, IHC, qRT-PCR and other tests. The correlation of localized C3 deposition and oncologic outcomes was determined by 5-year survival significance. Human GC and normal epithelial cell lines were employed to detect a relationship between C3 and STAT3 signaling pathway in vitro experiments.

Results

C3 and C3a expression were markedly enhanced in GC tissues at both mRNA and protein levels compared with those in paired nontumorous tissues. According to IHC C3 score, 65 (61.3%) and 41 (38.7%) patients had high and low C3 deposition, respectively. C3 deposition was negatively correlated with plasma levels of C3 and C3a (both P < 0.001) and positively correlated with pathological T and TNM stages (both P < 0.001). High C3 deposition was identified as an independent prognostic factor of poor 5-year overall survival (P = 0.045). In vitro C3 administration remarkably enhanced p-JAK2/p-STAT3 expression in GC cell lines but caused a reduction of such activation when pre-incubated with a C3 blocker. Importantly, C3 failed to activate such signaling in cells pre-treated with a JAK2 inhibitor.

Conclusions

Localized C3 deposition in the tumor microenvironment is a relevant immune signature for predicting prognosis of GC. It may aberrantly activate JAK2/STAT3 pathway allowing oncoprogression.

Trial registration

ClinicalTrials.gov, NCT02425930, Registered 1st August 2013.

Development and validation of a prognostic nomogram in gastric cancer with hepatitis B virus infection

Background

Patients with HBsAg-positive gastric cancer (GC) are a heterogeneous group, and it is not possible to accurately predict the overall survival (OS) in these patients.

Methods

We developed and validated a nomogram to help improve prediction of OS in patients with HBsAg-positive GC. The nomogram was established by a development cohort (n = 245), and the validation cohort included 84 patients. Factors in the nomogram were identified by univariate and multivariate Cox hazard analysis. We tested the accuracy of the nomograms by discrimination and calibration, and plotted decision curves to assess the benefits of nomogram-assisted decisions in a clinical context. Then we evaluated the risk in the two cohort.

Results

Significant predictors were age, tumor stage, distant metastases, gamma-glutamyl transpeptidase (GGT) and alkaline phosphatase (ALP). The proportional-hazards model (nomogram) was based on pre-treatment characteristics. The nomogram had a concordance index (C-index) of 0.812 (95% CI 0.762–0.862), which was superior than the C-index of AJCC TNM Stage (0.755, 95% CI 0.702–0.808). The calibration plot in the validation cohort based on 5 predictors suggested good agreement between actual and nomogram-predicted OS probabilities. The decision curve showed that the nomogram in predicting OS is better than that of TNM staging system in all range. Moreover, patients were divided into three distinct risk groups for OS by the nomogram: low risk group, middle risk group and high risk group, respectively.

Conclusion

This nomogram, using five pre-treatment characteristics, improves prediction of OS in patients with HBsAg-positive gastric cancer. It represents an improvement in prognostication over the current TNM stage. To generalize the use of this nomogram in other groups, additional validation with data from other institutions is required.

Combination of lymphovascular invasion and the AJCC TNM staging system improves prediction of prognosis in N0 stage gastric cancer: results from a high-volume institution

BACKGROUND

This study sought to explore whether lymphovascular invasion can affect the prognosis of patients with stage N0 gastric cancer and to evaluate the survival benefit of adjuvant chemotherapy for such patients.

METHOD

From January 2006 to December 2011, a total of 2102 gastric cancer patients undergoing radical gastric resection were enrolled in this study. Homogeneity, discriminatory ability, and monotonicity of gradients in the combination of lymphovascular invasion and the 8th edition of the AJCC staging system and the 8th edition of the AJCC staging system alone were compared using linear trend χ2, likelihood ratio χ2 statistics, and Akaike information criterion (AIC) calculations. The Kaplan-Meier method and the log-rank test were used to analyze between-group differences in survival rate.

RESULT

The median follow-up time of the whole group was 58 months, and the average age of the whole group was 63.9 years (range 21-89 years). The 3-year and 5-year overall survival rates in N0 patients with lymphovascular invasion were lower than those in N0 patients without lymphovascular invasion (3-year OS: 78.3% vs 92.5%, 5-year OS: 70.0% vs 88.3%, p < 0.001). A multivariate analysis showed that age (p < 0.001), lymphovascular invasion (p < 0.001), and pT (p < 0.001) were independent risk factors for the prognosis of N0 patients. Compared with the 8th edition of the AJCC staging system alone, the 8th AJCC staging system combined with lymphovascular invasion demonstrated a better linear trend χ2, likelihood ratio χ2 statistics, and AIC value (68.99 vs 58.58, 70.18 vs 58.36, 1473.38 vs 1485.04). In pT3N0M0 patients with lymphovascular invasion, the 3-year and 5-year overall survival rates of the adjuvant chemotherapy group were higher than those of the surgery alone group (3-year OS: 83.3% vs 68.2%, 5-year OS: 72.3% vs 50.0%, p = 0.048).

CONCLUSION

Lymphovascular invasion is an independent prognostic factor in N0 patients. The 8th AJCC staging system combined with lymphovascular invasion can improve the accuracy of the AJCC staging system for N0 patients. Moreover, adjuvant chemotherapy improves the survival of pT3N0M0 patients with lymphovascular invasion.