Background: The effect of multidisciplinary team intervention (MDT) on the prognosis of advanced gastric cancer (GC) is still controversial. This study aims to analyze the effect of MDTs on the overall survival time of advanced gastric cancer patients. Methods: Patients with advanced GC who underwent surgical treatment between 2007 and 2014 were included in the study. They were divided into two groups; the MDT group received MDT treatment and the non-MDT group received conventional treatment. The Kaplan-Meier method was used to compare the overall survival (OS) of the two groups. The prognostic factors of advanced GC were evaluated by multivariate Cox regression analysis. Results: 394 patients were included in our study. Kaplan-Meier survival analysis showed that the prognosis of advanced GC patients with who underwent MDT intervention was better than those without (3-year OS of 55.6% vs. 46.1%, p = 0.005), Multivariate analysis indicated that MDT intervention could reduce mortality (HR = 0.493, p < 0.001). Conclusions: MDT intervention is an effective measure that improves the survival of patients with advanced GC.

Objectives: The absence of non-invasive biomarkers for the early diagnosis of colorectal cancer (CRC) has contributed to poor prognosis. Extracellular vesicles (EVs) have emerged as promising candidates for cancer monitoring using liquid biopsy. However, the complexity of EVs isolation procedures and the absence of clear targets for detecting serum-derived EVs have hindered the clinical application of EVs in early CRC diagnosis. Methods: In the discovery phase, we conducted a comprehensive 4D-DIA proteomic analysis of serum-derived EVs samples from 37 individuals, performing an initial screening of EVs surface proteins. In the technical validation phase, we developed an extraction-free CRC-EVArray microarray to assess the expression of these potential EVs surface proteins in a multi-centre study comprising 404 individuals. In the application phase, the authors evaluated the diagnostic efficacy of the CRC-EVArray model based on machine-learning algorithms. Results: Through 4D-DIA proteomic analysis, the authors identified seven potential EVs surface proteins showing significantly differential expression in CRC patients compared to healthy controls. Utilizing our developed high-throughput CRC-EVArray microarray, we further confirmed the differential expression of three EVs surface proteins, FIBG, PDGF-β and TGF-β, in a large sample population. Moreover, we established an optimal CRC-EVArray model using the NNET algorithm, demonstrating superior diagnostic efficacy with an area under the curve (AUC) of 0.882 in the train set and 0.937 in the test set. Additionally, we predicted the functions and potential origins of these EVs-derived proteins through a series of multi-omics approaches. Conclusions: Our systematic exploration of surface protein expression profiles on serum-derived EVs has identified FIBG, PDGF-β, and TGF-β as novel diagnostic biomarkers for CRC. The development of CRC-EVArray diagnostic model based on these findings provided an effective tool for the large-scale CRC screening, thus facilitating its translation into clinical practice.

Syntaxin-6 (STX6), a vesicular transport protein, is a direct target of the tumor suppressor gene P53, supporting cancer growth dependent on P53. However, STX6’s function in the tumor microenvironment has yet to be reported. In this research, we comprehensively explored the role of the oncogene STX6 in pan-cancer by combining data from several databases, including the Cancer Genome Atlas, CPTAC, cBioPortal, and TIMER. Then, we verified the carcinogenic effect of STX6 in hepatocellular carcinoma (HCC) and colorectal cancer (CRC) through a series of experiments in vitro and in vivo. Bioinformatics analysis demonstrated that STX6 is an oncogene for several cancers and is mainly involved in the cell cycle, epithelial–mesenchymal transition, oxidative phosphorylation, and tumor immune modulation, especially for tumor-associated fibroblasts (CAFs) and NKT cells. Additionally, a high level of STX6 could indicate patients’ resistance to immunotherapy. Our own data indicated that the STX6 level was upregulated in HCC and CRC. Knockdown of the STX6 levels could arrest the cell cycle and restrain cell proliferation, migration, and invasion. RNA-seq indicated that STX6 was significantly involved in pathways for cancer, such as the MAPK signal pathway. In a mouse model, knockdown of STX6 inhibited tumor growth and potentiated anti-PD-1 efficacy. In light of the essential roles STX6 plays in carcinogenesis and cancer immunology, it has the potential to be a predictive biomarker and a target for cancer immunotherapy.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are highly heterogeneous neoplasms of the gastrointestinal tract and pancreas. The objective of this study was to develop and verify a prediction nomogram for determining the overall survival rate of stage IV GEP-NENs. Data from 2139 stage IV GEP-NENs patients between 2010 and 2017 were extracted from the SEER database. Concordance index (C-index), calibration curve analysis, receiver operating curve (ROC) analysis, and decision curve analysis (DCA) were used to evaluate and validate the predictive performance of the nomogram. The difference in survival rates between the low-risk and high-risk groups was analyzed using the Kaplan-Meier method. Ten risk factors were integrated into the prognostic nomogram. The C-index (0.7961 in the training set and 0.801 in the validating set) and calibration curve analysis exhibited an excellent consistency between the two groups. The AUC value was 0.879, 0.857, and 0.839, respectively, for nomograms predicting 1-, 3-, and 5-year overall survival in the training set. In the validation set, AUC values were 0.859, 0.844, and 0.831 for nomograms predicting 1-, 3-, and 5-year overall survival. According to the DCA analysis, the nomogram offered significant clinical benefits. The scatter plot of risk score demonstrated that with the increase in risk score, the proportion of death also increased. In both training and validation sets, the Kaplan-Meier analysis displayed that patients in the high-risk group with stage IV GEP-NENs had a worse overall survival rate than patients in the low-risk group. A prognostic nomogram of stage IV GEP-NENs was established by integrating age, sex, differentiation, primary site, tumor size, surgery, chemotherapy, and bone, brain, and lung metastases. With further verification, the nomogram with favorable specificity, sensitivity, and added clinical benefit could help clinicians assess prognosis and provide treatment guidance for stage IV GEP-NENs patients.