Effect of Perioperative Interleukin-6 and Tumor Necrosis Factor-α on Long-Term Outcomes in Locally Advanced Gastric Cancer: Results from the CLASS-01 Trial

LightGBM is an Effective Predictive Model for Postoperative Complications in Gastric Cancer: A Study Integrating Radiomics with Ensemble Learning

Postoperative complications of radical gastrectomy seriously affect postoperative recovery and require accurate risk prediction. Therefore, this study aimed to develop a prediction model specifically tailored to guide perioperative clinical decision-making for postoperative complications in patients with gastric cancer. A retrospective analysis was conducted on patients who underwent radical gastrectomy at the First Affiliated Hospital of Nanjing Medical University between April 2022 and June 2023. A total of 166 patients were enrolled. Patient demographic characteristics, laboratory examination results, and surgical pathological features were recorded. Preoperative abdominal CT scans were used to segment the visceral fat region of the patients through 3Dslicer, a 3D Convolutional Neural Network (3D-CNN) to extract image features and the LASSO regression model was employed for feature selection. Moreover, an ensemble learning strategy was adopted to train the features and predict postoperative complications of gastric cancer. The prediction performance of the LGBM (Light Gradient Boosting Machine), XGB (XGBoost), RF (Random Forest), and GBDT (Gradient Boosting Decision Tree) models was evaluated through fivefold cross-validation. This study successfully constructed a model for predicting early complications following radical gastrectomy based on the optimal algorithm, LGBM. The LGBM model yielded an AUC value of 0.9232 and an accuracy of 87.28% (95% CI, 75.61-98.95%), surpassing the performance of other models. Through ensemble learning and integration of perioperative clinical data and visceral fat radiomics, a predictive LGBM model was established. This model has the potential to facilitate individualized clinical decision-making and the early recovery of patients with gastric cancer post-surgery.

Targeting interleukin-6 as a treatment approach for peritoneal carcinomatosis

Peritoneal carcinomatosis (PC) is a complex manifestation of abdominal cancers, with a poor prognosis and limited treatment options. Recent work identifying high concentrations of the cytokine interleukin-6 (IL-6) and its soluble receptor (sIL-6-Rα) in the peritoneal cavity of patients with PC has highlighted this pathway as an emerging potential therapeutic target. This review article provides a comprehensive overview of the current understanding of the potential role of IL-6 in the development and progression of PC. We discuss mechansims by which the IL-6 pathway may contribute to peritoneal tumor dissemination, mesothelial adhesion and invasion, stromal invasion and proliferation, and immune response modulation. Finally, we review the prospects for targeting the IL-6 pathway in the treatment of PC, focusing on common sites of origin, including ovarian, gastric, pancreatic, colorectal and appendiceal cancer, and mesothelioma.

IL-6/IL-10 mRNA expression ratio in tumor tissues predicts prognosis in gastric cancer patients without distant metastasis

There was growing evidence that inflammatory responses played significant roles in malignancies. However, the impact of pro-inflammatory-to-anti-inflammatory factor ratio in tumor tissues has not been investigated in gastric cancer (GC) yet. We collected patient data from The Cancer Genome Atlas (TCGA) database. A total of 270 stomach adenocarcinoma (STAD) patients without distant metastasis were included in the study. After screening 12 candidate pro-inflammatory-to-anti-inflammatory pairs, only the IL-6/IL-10 mRNA expression ratio in tumor tissues had a significant effect on overall survival (OS) of STAD patients (P = 0.014). X-tile analysis showed that the greatest survival differences were obtained when the cutoff value of IL-6/IL-10 mRNA expression ratio was set at 1.3 and 5.5. With the low-ratio group (IL-6/IL-10 mRNA expression ratio: < 1.3) as reference, OS time for both the medium-ratio group (IL-6/IL-10 mRNA expression ratio: 1.3-5.5) and the high-ratio group (IL-6/IL-10 mRNA expression ratio: > 5.5) was significantly shorter (P < 0.05). Multivariate Cox regression analyses indicated that IL-6/IL-10 mRNA expression ratio was an independent prognostic factor for OS and disease-specific survival (DSS). These findings provided a novel and powerful tool for a more rational management of GC patients.

Tanshinone IIA May Inhibit Gastric Cancer via Affecting the Intestinal Microbiome

Background

Gastric cancer (GC) belongs to a type of the most deadly cancer in the world, and the incidence rate of GC will increase in the coming decades. Tanshinone IIA (Tan IIA) is an active component that separated from Danshen. Tan IIA may also exert its therapeutic effects in disease with intestinal dysbacteriosis, at least partially, via regulating the intestinal microbiome. Nevertheless, it is obscure whether Tanshinone IIA affects the intestinal dysbacteriosis and plays antitumor roles. This research was designed to explore Tanshinone IIA potential on the intestinal dysbacteriosis of GC xenograft mice.

Methods

Mouse xenograft GC tumor models were built and treated by Tan IIA. The tumor growth as well as microbiome in the intestinal were compared. Western blot was used to detect the phosphorylation of the NF-κB and expressions of the downstream cytokines IL-6 and IL-1β.

Results

Microbiome in the intestinal was changed in xenograft tumor mice in comparison with the control mice. What is more, Tan IIA could influence the microbiome in the intestinal of the tumor mice. Tan IIA hinders the growth of xenograft tumor and change the microbiome in the intestinal, but intestinal dysbacteriosis condition partially blocked Tan IIA-stimulated antitumor effects. In addition, intestinal dysbacteriosis abrogated Tan IIA-stimulated decrease in the NF-κB signaling in xenograft tumor mice.

Conclusions

Tanshinone IIA may inhibit GC tumor growth via affecting the intestinal microbiome through regulating the NF-κB signaling.