Influential factors and prognostic analysis of blood vessel invasion in advanced gastric cancer

Construction and validation of a prognostic model for gastric cancer patients with tumor deposits

Background

Tumor deposits (TD) was a significant risk factor impacting the prognosis of patients diagnosed with gastric cancer (GC), yet it was not currently incorporated into TNM staging systems. The objective of this research was to develop a predictive model for assessing the prognosis of patients with TD-positive GC.

Methods

Retrospective analysis was performed on the data of 4,972 patients treated for GC with D2 radical gastrectomy at Wannan Medical College's Yijishan Hospital between January 2012 and December 2021. The patients were categorized based on the number of TD (L1: 1, L2: 2-3, L3: ≥4) and the anatomical location of TD (Q1: single area, Q2: multiple areas). In a 3:1 ratio, patients were randomly assigned to one of two groups: training or validation.

Results

The study included a total of 575 patients who were divided into the training group (n = 432) and validation group (n = 143). Survival analysis showed that the number and anatomical location of TD had a significant impact on the prognosis of patients with TD-positive GC. Univariate analysis of the training group data revealed that tumor size, T-stage, N-stage, histological grade, number and distribution of TD, neural invasion, and postoperative chemotherapy were associated with prognosis. Multivariate Cox regression analysis identified poor histological grade, T4 stage, N3 stage, number of TD, neural invasion, and postoperative chemotherapy as independent prognostic factors for GC patients with TD. A nomogram was developed using these variables, demonstrating well predictive ability for 1, 3, and 5-year overall survival (OS) in the validation set. The DCA curve shows that the constructed model shows a large positive net gain compared to the eighth edition Tumour, Node, Metastasis (TNM) staging system.

Conclusion

The prognostic model developed for patients with TD-positive GC has a higher clinical utility compared to the eighth edition of TNM staging.

Detection of CDH1 gene promoter hypermethylation in gastric cancer and chronic gastritis

Aim

The current study aimed to assess the frequency of CDH1 promoter gene hypermethylation in gastric cancer and chronic gastritis and its correlation with clinicopathological aspects.

Methods

Methylation-specific PCR was used to detect CDH1 promoter gene hypermethylation in 53 chronic gastritis patients and 40 gastric cancer patients along with normal adjacent tissues.

Results

The chronic gastritis group comprised 29 males and 24 females with a mean age of 51.8 ± 12.96 years, and 49.1 % of them were positive for H. pylori infection. The frequency of CDH1 hypermethylation in gastritis lesions was 18.8 %. CDH1 hypermethylation showed a significant correlation with H. pylori infection (p = 0.039), but no significant association was observed with other clinical features. The gastric cancer group consisted of individuals with a mean age of 65.4 ± 10.6, among them, 77.5 % were male and 22.5 % were female, 62.5 % had PT3 tumors, 40 % had PN1 lymph node involvement, and the majority (47.5 %) of samples were obtained from body segment. CDH1 hypermethylation was significantly associated with depth of invasion (p = 0.017) and nodal invasion (p = 0.041) in this group. In both groups, normal adjacent specimens lacked CDH1 hypermethylation, and there was no statistically significant correlation between CDH1 hypermethylation and age at which the tumor was diagnosed, gender, activity level, or tumor location.

Conclusion

This study demonstrates that E-cadherin methylation is associated with some characteristics of chronic gastritis and gastric cancer. These findings support previous research indicating that CDH1 hypermethylation may play a significant role in the development of gastric cancer.

Prediction model based on radiomics and clinical features for preoperative lymphovascular invasion in gastric cancer patients

Background: We explored whether a model based on contrast-enhanced computed tomography radiomics features and clinicopathological factors can evaluate preoperative lymphovascular invasion (LVI) in patients with gastric cancer (GC) with Lauren classification. Methods: Based on clinical and radiomic characteristics, we established three models: Clinical + Arterial phase_Radcore, Clinical + Venous phase_Radcore and a combined model. The relationship between Lauren classification and LVI was analyzed using a histogram. Results: We retrospectively analyzed 495 patients with GC. The areas under the curve of the combined model were 0.8629 and 0.8343 in the training and testing datasets, respectively. The combined model showed a superior performance to the other models. Conclusion: CECT-based radiomics models can effectively predict preoperative LVI in GC patients with Lauren classification.

Application of machine learning algorithm in predicting distant metastasis of T1 gastric cancer

Distant metastasis (DM) is relatively uncommon in T1 stage gastric cancer (GC). The aim of this study was to develop and validate a predictive model for DM in stage T1 GC using machine learning (ML) algorithms. Patients with stage T1 GC from 2010 to 2017 were screened from the public Surveillance, Epidemiology and End Results (SEER) database. Meanwhile, we collected patients with stage T1 GC admitted to the Department of Gastrointestinal Surgery of the Second Affiliated Hospital of Nanchang University from 2015 to 2017. We applied seven ML algorithms: logistic regression, random forest (RF), LASSO, support vector machine, k-Nearest Neighbor, Naive Bayesian Model, Artificial Neural Network. Finally, a RF model for DM of T1 GC was developed. The AUC, sensitivity, specificity, F1-score and accuracy were used to evaluate and compare the predictive performance of the RF model with other models. Finally, we performed a prognostic analysis of patients who developed distant metastases. Independent risk factors for prognosis were analysed by univariate and multifactorial regression. K-M curves were used to express differences in survival prognosis for each variable and subvariable. A total of 2698 cases were included in the SEER dataset, 314 with DM, and 107 hospital patients were included, 14 with DM. Age, T-stage, N-stage, tumour size, grade and tumour location were independent risk factors for the development of DM in stage T1 GC. A combined analysis of seven ML algorithms in the training and test sets found that the RF prediction model had the best prediction performance (AUC: 0.941, Accuracy: 0.917, Recall: 0.841, Specificity: 0.927, F1-score: 0.877). The external validation set ROCAUC was 0.750. Meanwhile, survival prognostic analysis showed that surgery (HR = 3.620, 95% CI 2.164-6.065) and adjuvant chemotherapy (HR = 2.637, 95% CI 2.067-3.365) were independent risk factors for survival prognosis in patients with DM from stage T1 GC. Age, T-stage, N-stage, tumour size, grade and tumour location were independent risk factors for the development of DM in stage T1 GC. ML algorithms had shown that RF prediction models had the best predictive efficacy to accurately screen at-risk populations for further clinical screening for metastases. At the same time, aggressive surgery and adjuvant chemotherapy can improve the survival rate of patients with DM.

Survival and clinicopathological significance of blood vessel invasion in operable breast cancer: a systematic review and meta-analysis

BACKGROUND

Lymphovascular invasion, including lymphatic-vessel invasion and blood-vessel invasion, plays an important role in distant metastases. The metastatic pattern of blood-vessel invasion may differ from that of lymphatic-vessel invasion. However, its prognostic significance in breast cancer remains controversial. We evaluated the role of blood-vessel invasion in the prognosis of operable breast-cancer patients and its association with clinicopathological characteristics.

METHODS

We systematically searched EMBASE, PubMed, the Cochrane Library and Web of Science for studies in English through December 2020. Disease-free survival, overall survival and cancer-specific survival were the primary outcomes. Pooled hazard ratios and 95% confidence intervals were assessed using a random-effects model.

RESULTS

Twenty-seven studies involving 7954 patients were included. Blood-vessel invasion occurred in 20.4% of tumor samples. Pooled results showed significant associations of blood-vessel invasion with worse disease-free survival (hazard ratio = 1.82; 95% confidence interval = 1.43-2.31) and overall survival (hazard ratio = 1.86; 95% confidence interval = 1.16-2.99) in multivariate analyses. The results of the univariate analyses were similar. Among the clinicopathological factors, blood-vessel invasion was associated with larger tumor size, lymph-node metastasis, nonspecific invasive type, higher histological grade, estrogen receptor-negative breast cancer, human epidermal growth factor receptor 2-positive breast cancer and lymphatic-vessel invasion. In the lymph-node-negative subgroup analyses, the presence of blood-vessel invasion led to poorer disease-free survival (hazard ratio = 2.46; 95%confidence interval = 1.64-3.70) and overall survival (hazard ratio = 2.94; 95%confidence interval = 1.80-4.80).

CONCLUSIONS

We concluded that blood-vessel invasion is an independent predictor of poor prognosis in operable breast cancer and is associated with aggressive clinicopathological features. Breast-cancer patients with blood-vessel invasion require more aggressive treatments after surgery.

Computed tomography-detected extramural venous invasion-related gene signature: a potential negative biomarker of immune checkpoint inhibitor treatment in patients with gastric cancer

BACKGROUND

To investigate the association between computed tomography (CT)-detected extramural venous invasion (EMVI)-related genes and immunotherapy resistance and immune escape in patients with gastric cancer (GC).

METHODS

Thirteen patients with pathologically proven locally advanced GC who had undergone preoperative abdominal contrast-enhanced CT and radical resection surgery were included in this study. Transcriptome sequencing was multidetector performed on the cancerous tissue obtained during surgery, and EMVI-related genes (P value for association < 0.001) were selected. A single-sample gene set enrichment analysis algorithm was also used to divide all GC samples (n = 377) in The Cancer Genome Atlas (TCGA) database into high and low EMVI-immune related groups based on immune-related differential genes. Cluster analysis was used to classify EMVI-immune-related genotypes, and survival among patients was validated in TCGA and Gene Expression Omnibus (GEO) cohorts. The EMVI scores were calculated using principal component analysis (PCA), and GC samples were divided into high and low EMVI score groups. Microsatellite instability (MSI) status, tumor mutation burden (TMB), response rate to immune checkpoint inhibitors (ICIs), immune escape were compared between the high and low EMVI score groups. Hub gene of the model in pan-cancer analysis was also performed.

RESULTS

There were 17 EMVI-immune-related genes used for cluster analysis. PCA identified 8 genes (PCH17, SEMA6B, GJA4, CD34, ACVRL1, SOX17, CXCL12, DYSF) that were used to calculate EMVI scores. High EMVI score groups had lower MSI, TMB and response rate of ICIs, status but higher immune escape status. Among the 8 genes used for EMVI scores, CXCL12 and SOX17 were at the core of the protein-protein interaction (PPI) network and had a higher priority in pan-cancer analysis. Immunohistochemical analysis showed that the expression of CXCL12 and SOX17 was significantly higher in CT-detected EMVI-positive samples than in EMVI-negative samples (P < 0.0001).

CONCLUSION

A CT-detected EMVI gene signature could be a potential negative biomarker for ICIs treatment, as the signature is negatively correlated with TMB, and MSI, resulting in poorer prognosis.

Influence of Lymphangio vascular (V) and perineural (N) invasion on survival of patients with resected esophageal squamous cell carcinoma (ESCC): a single-center retrospective study

Background

Lymphangio vascular invasion (LVI) and perineural invasion (PNI) are associated with survival following resection for gastrointestinal cancer. But the relationship between LVI/PNI and survival of esophageal squamous cell carcinoma (ESCC) is still unclear. We aim to demonstrate the prognostic significance of LVI/PNI in ESCC.

Methods

A total of 195 ESCC patients underwent curative surgery from 2012 to 2018 was collected in the 2nd Affiliated Hospital of Fujian Medical University. All the patients were divided into four groups based on the status of the neurovascular invasion: (1) neither LVI nor PNI (V0N0); (2) LVI alone (V1N0); (3) PNI alone (V0N1); (4) combined LVI and PNI (V1N1). First, the analysis included the Kaplan-Meier survival estimates with the Log rank test were performed to determine median overall survival (OS) in different groups divided according to the clinical factor, respectively. And the association between OS with multi clinical factors was examined using Cox regression analysis. Next, the risk factors for recurrence in patients with V1N1 were analyzed with univariate and multivariate logistic regression analyses, respectively.

Results

The cases in V0N0, V1N0, V0N1, and V1N1 groups were 91 (46.7%), 62 (31.8%), 9 (4.6%) and 33 (16.9%), respectively. The OS in the four groups was different (P < 0.001). The 1-, 3- and 5-year OS in V0N0 group was higher than that in V1N1 group, respectively (1-year OS: 93.4% vs 75.8%, 3-year OS: 53.8 % vs 24.2%, 5-year OS: 48.1% vs 10.5%). The OS in stage I-II for patients with V1N1 was significantly lower than that in the other groups (V0N0, V1N0, V0N1) (P < 0.001). The postoperative adjuvant chemotherapy was a significant impact factor of OS for ESCC patients with V1N1 (P = 0.004). Lymphatic invasion and LVI were significantly prognosis factors associated (P = 0.036, P = 0.030, respectively). The ulcerative type is a risk factor for V1N1 occurance (P = 0.040).

Conclusions

The LVI and PNI are important prognosis factors for ESCC patients. ESCC patients with simultaneous lymphangio vascular and perineural invasion (V1N1) showed worse OS than patients with either lymphangio vascular or perineural invasion alone (V1N0 or V0N1) or none (V0N0). In addition, adjuvant chemotherapy may prolong the OS for ESCC patients with V1N1.

CT-detected extramural venous invasion-related gene signature for the overall survival prediction in patients with gastric cancer

Background

Computed tomography (CT)‐detected extramural venous invasion (EMVI) has been identified as an independent factor that can be used for risk stratification and prediction of prognosis in patients with gastric cancer (GC). Overall survival (OS) is identified as the most important prognostic indicator for GC patients. However, the molecular mechanism of EMVI development and its potential relationship with OS in GC are not fully understood. In this radiogenomics‐based study, we sought to investigate the molecular mechanism underlying CT‐detected EMVI in patients with GC, and aimed to construct a genomic signature based on EMVI‐related genes with the goal of using this signature to predict the OS.

Materials and Methods

Whole mRNA genome sequencing of frozen tumor samples from 13 locally advanced GC patients was performed to identify EMVI‐related genes. EMVI‐prognostic hub genes were selected based on overlapping EMVI‐related differentially expressed genes and OS‐related genes, using a training cohort of 176 GC patients who were included in The Cancer Genome Atlas database. Another 174 GC patients from this database comprised the external validation cohort. A risk stratification model using a seven‐gene signature was constructed through the use of a least absolute shrinkage and selection operator Cox regression model.

Results

Patients with high risk score showed significantly reduced OS (training cohort, p = 1.143e‐04; validation cohort, p = 2.429e‐02). Risk score was an independent predictor of OS in multivariate Cox regression analyses (training cohort, HR = 2.758; 95% CI: 1.825–4.169; validation cohort, HR = 2.173; 95% CI: 1.347–3.505; p < 0.001 for both). Gene functions/pathways of the seven‐gene signature mainly included cell proliferation, cell adhesion, regulation of metal ion transport, and epithelial to mesenchymal transition.

Conclusions

A CT‐detected EMVI‐related gene model could be used to predict the prognosis in GC patients, potentially providing clinicians with additional information regarding appropriate therapeutic strategy and medical decision‐making.

Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma

Objectives

To develop a radiomics model based on contrast-enhanced CT (CECT) to predict the lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC) and provide decision-making support for clinicians.

Patients and Methods

This retrospective study enrolled 334 patients with surgically resected and pathologically confirmed ESCC, including 96 patients with LVI and 238 patients without LVI. All enrolled patients were randomly divided into a training cohort and a testing cohort at a ratio of 7:3, with the training cohort containing 234 patients (68 patients with LVI and 166 without LVI) and the testing cohort containing 100 patients (28 patients with LVI and 72 without LVI). All patients underwent preoperative CECT scans within 2 weeks before operation. Quantitative radiomics features were extracted from CECT images, and the least absolute shrinkage and selection operator (LASSO) method was applied to select radiomics features. Logistic regression (Logistic), support vector machine (SVM), and decision tree (Tree) methods were separately used to establish radiomics models to predict the LVI status in ESCC, and the best model was selected to calculate Radscore, which combined with two clinical CT predictors to build a combined model. The clinical model was also developed by using logistic regression. The receiver characteristic curve (ROC) and decision curve (DCA) analysis were used to evaluate the model performance in predicting the LVI status in ESCC.

Results

In the radiomics model, Sphericity and gray-level non-uniformity (GLNU) were the most significant radiomics features for predicting LVI. In the clinical model, the maximum tumor thickness based on CECT (cThick) in patients with LVI was significantly greater than that in patients without LVI (P<0.001). Patients with LVI had higher clinical N stage based on CECT (cN stage) than patients without LVI (P<0.001). The ROC analysis showed that both the radiomics model (AUC values were 0.847 and 0.826 in the training and testing cohort, respectively) and the combined model (0.876 and 0.867, respectively) performed better than the clinical model (0.775 and 0.798, respectively), with the combined model exhibiting the best performance.

Conclusions

The combined model incorporating radiomics features and clinical CT predictors may potentially predict the LVI status in ESCC and provide support for clinical treatment decisions.

Apatinib inhibits gastric carcinoma development by regulating the expression levels of IL-17 via the Bax/Bcl-2 signaling pathway

Gastric carcinoma is a common type of gastrointestinal tumor with high morbidity and mortality rates. IL-17 is a newly discovered cytokine that has been reported to serve an important role in the development of gastric carcinoma. The potential effect of apatinib on IL-17 expression levels in the development of gastric carcinoma has been rarely reported. The present study aimed to investigate the potential mechanism of IL-17 and apatinib in the development of gastric carcinoma. A total of 30 tumor and para-carcinoma tissues were collected from 30 patients with gastric carcinoma between January 2019 and December 2019 and the expression levels of IL-17 in the tissues were analyzed by reverse transcription-quantitative PCR and western blotting. An in vitro model of gastric carcinoma was also established using the HGC-27 cell line, in which the cells were divided into control, IL-17, IL-17-apatinib and apatinib groups. The expression levels of IL-17, Bax, Bcl-2 and caspase-3 were analyzed using reverse transcription-quantitative PCR and western blotting. An MTT assay and flow cytometry were used to analyze the proliferation and apoptosis of HGC-27 cells, respectively, and a Transwell assay was used to analyze the invasive ability of HGC-27 cells. The results revealed that the expression levels of IL-17 were significantly upregulated in the gastric carcinoma tissues compared with the para-carcinoma tissues. In vitro, IL-17 treatment promoted the proliferation and invasive ability of HGC-27 cells, but inhibited the apoptosis with the significantly downregulated expression levels of Bax and caspase-3 and the upregulated expression levels of Bcl-2 than control group. Conversely, apatinib treatment significantly inhibited the proliferative and invasive abilities of HGC-27 cells, but promoted cell apoptosis in the IL-17 and IL-17-apatinib groups.. Collectively, the present results suggested that the upregulation of IL-17 may be associated with the occurrence and development of gastric carcinoma. The findings indicated that apatinib may inhibit gastric carcinoma development by regulating IL-17 expression via the Bax/Bcl-2 signaling pathway. Therefore, the present findings may enhance the current knowledge of the effect of apatinib on gastric carcinoma cells.