Background Pancreatic cancer (PC) is a highly lethal malignancy that requires effective novel therapies. M2 macrophages are abundant in the PC microenvironment and promote cancer progression. Exosomes are emerging mediators of the crosstalk between cancer cells and the microenvironment. This study was conducted to explore the role of M2 macrophage-derived exosomes in PC. Methods Exosomes derived from M2 macrophages were extracted. miR-193b-3p and TRIM62 were overexpressed or silenced to examine their function in PC. Luminescence assays were used to investigate the interaction between miR-193b-3p and TRIM62. Cell proliferation was examined by EdU staining. Would healing and transwell assays were applied to evaluate cell migration and invasion. Co-immunoprecipitation was used to assess the interaction between TRIM62 and c-Myc. Gene and protein expressions were analyzed by quantitative RT-PCR and immunoblotting, respectively. Results M2 macrophage-derived exosomal miR-193b-3p promoted the proliferation, migration, invasion, and glutamine uptake of SW1990 cells. Mechanism study revealed that TRIM62 is a target of miR-193b-3p. TRIM62 inhibited the proliferation, migration, invasion, and glutamine uptake of SW1990 cells by promoting c-Myc ubiquitination. Our data also suggested that TRIM62 expression negatively correlated with miR-193b-3p and c-Myc expression. High-expression of miR-193b-3p and c-Myc predicts poor prognosis, whereas low-expression of TRIM62 predicts poor prognosis in patients with PC. Conclusion M2 macrophage-derived exosomal miR-193b-3p enhances the proliferation, migration, invasion, and glutamine uptake of PC cells by targeting TRIM62, resulting in the decrease of c-Myc ubiquitination. This study not only reveals the mechanism underlying the crosstalk between M2 macrophages and PC cells but also suggests a promising therapeutic target for PC.

While randomized controlled trials (RCTs) are the gold standard for evidence-based medicine, they do not always reflect the real condition of patients in the real-world setting, which limits their generalizability and external validity. Real-world evidence (RWE), generated during routine clinical practice, is increasingly important in determining external effectiveness of the tightly controlled conditions of RCTs and is well recognized as a valuable complement to RCTs by regulatory bodies currently. Since it could provide new ideas and methods for clinical efficacy and safety evaluation of traditional Chinese medicine (TCM) and high-quality evidence support, real-world study (RWS) has received great attention in the field of medicine, especially in the field of TCM. RWS has shown desirable adaptability in the clinical diagnosis and treatment practice of traditional Chinese medicine. Consequently, it is increasingly essential for physicians and researchers to understand how RWE can be used alongside clinical trial data on TCM. Here, we discuss what real-world study is and outline the benefits and limitations of real-world study. Furthermore, using examples from TCM treatment on cancer, including Chinese herbal medicine, acupuncture, moxibustion, integrated TCM and Western medicine treatment, and other treatments, we elaborate how RWE can be used to help inform treatment decisions when doctoring patients with cancer in the clinic.

Background Pancreatic adenocarcinoma (PDAC) is a malignant tumor with high heterogeneity and poor prognosis. In this study, we sought to identify the value of platelet-related genes in prognosis and heterogeneity of PDAC through multiple transcriptomic methods. Methods Based on datasets from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA), platelet-related genes were screened out, and the TCGA cohort (n = 171) was identified into two subtypes by unsupervised clustering. The platelet-related risk score model (PLRScore) was constructed by univariate Cox and LASSO regression, and the predictive ability was evaluated by Kaplan-Meier test and time-dependent receiver operating characteristic (ROC) curves. The results were validated in two other external validation sets, ICGC-CA (n = 140) and GSE62452 (n = 66). Furthermore, predictive nomogram containing clinical characteristics and PLRScore was established. In addition, we determined the possible correlation between PLRScore and immune infiltration and response of immunotherapy. Finally, we analyzed the heterogeneity of our signature in various types of cells using single-cell analysis. Results Platelet-related subtypes that have significant difference of overall survival and immune states (p < 0.05) were identified. PLRScore model based on four-gene signature (CEP55, LAMA3, CA12, SCN8A) was constructed to predict patient prognosis. The AUCs of training cohort were 0.697, 0.687 and 0.675 for 1-, 3-and 5-year, respectively. Further evaluation of the validation cohorts yielded similar results. In addition, PLRScore was associated with immune cell infiltration and immune checkpoint expression, and had promising ability to predict response to immunotherapy of PDAC. Conclusions In this study, the platelet-related subtypes were identified and the four-gene signature was constructed and validated. It may provide new insights into the therapeutic decision-making and molecular targets of PDAC.