Background Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nomogram to preoperatively identify occult PMs in AGC patients. Patients and methods A total of 554 AGC patients from 4 centers were divided into 1 training, 1 internal validation, and 2 external validation cohorts. All patients’ PM status was firstly diagnosed as negative by CT, but later confirmed by laparoscopy (PM-positive n = 122, PM-negative n = 432). Radiomic signatures reflecting phenotypes of the primary tumor (RS1) and peritoneum region (RS2) were built as predictors of PM from 266 quantitative image features. Individualized nomograms of PM status incorporating RS1, RS2, or clinical factors were developed and evaluated regarding prediction ability. Results RS1, RS2, and Lauren type were significant predictors of occult PM (all P < 0.05). A nomogram of these three factors demonstrated better diagnostic accuracy than the model with RS1, RS2, or clinical factors alone (all net reclassification improvement P < 0.05). The area under curve yielded was 0.958 [95% confidence interval (CI) 0.923–0.993], 0.941 (95% CI 0.904–0.977), 0.928 (95% CI 0.886–0.971), and 0.920 (95% CI 0.862–0.978) for the training, internal, and two external validation cohorts, respectively. Stratification analysis showed that this nomogram had potential generalization ability. Conclusion CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occult PM for AGC.

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IMPORTANCE Laparoscopic distal gastrectomy and neoadjuvant chemotherapy are increasingly used to treat locally advanced gastric cancer. However, the safety and efficacy of the laparoscopic procedure after neoadjuvant chemotherapy remain unclear. OBJECTIVE To evaluate the short-term outcomes of patients with locally advanced gastric cancer who received either laparoscopic distal gastrectomy or open distal gastrectomy.

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Several patient-derived tumor models emerged recently as robust preclinical drug-testing platforms. However, their potential to guide clinical therapy remained unclear. Here, we report a model called patient-derived tumor-like cell clusters (PTCs). PTCs result from the self-assembly and proliferation of primary epithelial, fibroblast, and immune cells, which structurally and functionally recapitulate original tumors. PTCs enabled us to accomplish personalized drug testing within 2 weeks after obtaining the tumor samples. The defined culture conditions and drug concentrations in the PTC model facilitate its clinical application in precision oncology. PTC tests of 59 patients with gastric, colorectal, or breast cancers revealed an overall accuracy of 93% in predicting their clinical outcomes. We implemented PTC to guide chemotherapy selection for a patient with mucinous rectal adenocarcinoma who experienced recurrence with metastases after conventional therapy. After three cycles of a nonconventional therapy identified by the PTC, the patient showed a positive response. These findings need to be validated in larger clinical trials, but they suggest that the PTC model could be prospectively implemented in clinical decision-making for therapy selection.

Background The clinical values of inflammatory and nutritional markers remained unclear for gastric cancer with neoadjuvant chemotherapy (NACT). Methods The inflammatory, nutritional markers and their changes were analyzed for locally advanced gastric cancer with NACT. The predictive value was evaluated by the Cox proportional hazards regressions under three hypothesized scenarios. The nomograms including independent prognostic factors were plotted for survival prediction. Results A total of 225 patients were included in the study. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index, and hemoglobin (Hgb) were significantly reduced, and the body mass index was significantly increased after NACT (all P < 0.05). The pre-NACT NLR [hazard ratio (HR) = 1.176, P = 0.059] showed a trend to correlate with the overall survival (OS) when only pre-NACT markers available; The post-NACT Hgb (HR = 0.982, P = 0.015) was the independent prognostic factor when only post-NACT markers available; The post-NACT Hgb (HR = 0.984, P = 0.025) and the change value of LMR (HR = 1.183, P = 0.036) were the independent prognostic factors when both pre-and post-NACT markers available. The nomogram had a similar Harrell's C-statistic compared to ypTNM stage (0.719 vs. 0.706). Conclusion For locally advanced gastric cancer, the NACT could significantly decrease some inflammatory markers. The pre-NACT NLR, the post-NACT Hgb and the change value of LMR had some values in survival prediction combined with age, sex, tumor location and the clinical stages under different clinical scenarios. The elevated initial NLR, the preoperative anemia and the greater change value of LMR implied a poor prognosis.

CHO appears to be safe, and may attenuate postoperative insulin resistance as compared to placebo. However, the quality of most of the published trials has been poor, and the evidence levels for most outcomes were low, so rigorous and larger RCTs are needed in the future.

The consumption of green tea did not decrease the levels of fasting plasma glucose, fasting serum insulin, OGTT-2 h glucose, haemoglobin A₁c and HOMA(IR) in populations at risk of T2DM. Larger, longer-term and high-quality RCTs are needed to further definitely determine the effect of green tea or green tea extract on insulin sensitivity and glycaemic control in populations at risk of T2DM.