Objective In this study, we aimed to evaluate the levels of plasma exosomal caveolin-1(CAV1) and determine its prognostic value in ovarian cancer patients. Patients and Methods Exosome-rich fractions were isolated from the plasma of 155 patients with ovarian cancer. TEM, NTA and western blot analysis were used to confirm the exosome integrity and purification. Results Compared with healthy controls, plasma exosomal CAV1 levels in ovarian cancer patient were significantly down-regulated (P less then 0.001). The low plasma levels of exosomal CAV1 in ovarian cancer patient plasma were related to FIGO stages, grades and lymph node metastasis (all P less then 0.01). Among all ovarian cancer patients, DFS was worse in patients who had low plasma exosomal CAV1 levels compared with that in patients with high plasma exosomal CAV1 levels (P less then 0.001). The OS of patients with low plasma exosomal CAV1 levels was shorter than that in patients with high plasma exosomal CAV1 levels (P less then 0.001). The AUROC of plasma exosomal CAV1 was 0.76 (95% CI 0.68-0.82) for DFS prediction in ovarian cancer patients, with a sensitivity 52.9 (95% CI 42.8-62.9) and a specificity 88.7 (95% CI 77.0-95.7). For OS prediction in ovarian cancer patients, the AUROC of plasma exosomal CAV1 was 0.78 (95% CI 0.70-0.84), with a sensitivity 65.1 (95% CI 49.1-79.0) and a specificity 81.2 (95% CI 72.8-88.0). Conclusions Low exosomal CAV1 levels were closely related to the FIGO stages I/II, low grade, lymph node metastasis and prognosis of ovarian cancer patients. Plasma exosomal CAV1 may be a potential biomarker for the prognosis in ovarian cancer patients.Elevated concentrations of circulating low density lipoprotein (LDL) that is abnormally oxidized and desialylated is both a precursor to and a hallmark of atherosclerosis. Peripheral blood mononuclear cells (PBMCs) treated in vitro with interleukin-2 (IL-2) become lymphokine activated killer (LAK) cells, the primary effectors of which are NK cells and NKT cells. LAK cells display antitumor functions such as increased cytotoxicity and IFN-γ production, and they have been evaluated as a potential cancer therapeutic. Atherosclerotic processes may influence innate immunity against cancer. Because prior studies have shown that low density lipoprotein (LDL) reduces T-cell and NK cell antitumor functions, we asked whether oxidized-desialylated LDL affects the functionality of LAK cells in vitro. We show here that LAK cells take up oxidized-desialylated LDL to a significantly greater extent than native LDL over a period of 72 hours. This resulted in a significant downregulation of LAK cell cytotoxicity against K562 cells. In particular, the expression of IFN-γ, CD56, and NKG2D were reduced upon oxidized-desialylated LDL treatment of LAK cells and, conversely, their expression was enhanced with native LDL. It was also observed that as the number of CD56 and NKG2D positive cells decreased upon treatment with oxidized-desialylated LDL, the number of CD3 positive cells increased in proportion. Additionally, only a slight inhibition of LAK cell cytotoxicity was observed with desialylation alone of LDL, and no significant inhibition was observed with oxidation alone of LDL. Thus, this study describes a new role of oxidized-desialylated LDL as an inhibitor of the antitumor functions of LAK cells. These observations have implications for how atherosclerosis processes, namely oxidation and desialylation of LDL, may influence LAK cell antitumor activity.Objective The aim of this study was to evaluate the prognosis of patients with metastatic prostate cancer (mPCa) in different age groups. Methods Patients with mPCa from 2004 to 2016 in the Surveillance, Epidemiology and End Results (SEER) database were identified. Seven groups were divided according to the age at diagnosis, including ≤55 years, 56-60 years, 61-65 years, 66-70 years, 71-75 years, 76-80 years and >80 years. Fine and Gray’s competing risks model and Kaplan-Meier analysis were conducted to evaluate the cancer-specific survival (CSS). Results A total of 36231 patients with mPCa were included. The CSS curves of the overall cohort showed that patients aged ≤55 years had significantly worse CSS than patients in age groups of 56-60 [HR0.93 (0.87~1.00), p=0.039], 61-65 [HR0.91 (0.85~0.97), p=0.003] and 66-70 [HR0.90 (0.84~0.96), p=0.001]. After removing patients dead for other reasons, the differences of CSS curves between ≤55 years group and 56-70 years groups were not significant. check details However, the mean survival time of ≤55 years group (55.78±2.48 months) was still shorter than 56-60 years (57.28±2.35 months), 61-65 years (57.64±2.07 months), and 66-70 years (57.11±2.11 months). When stratified by M stages, similar results were found in M1a, M1b and M1c stage groups. According to Fine-Gray competing risks models, patient ≤55 years featured significantly higher sub-distribution hazard ratio (sdHR) than 61-65 years group [sdHR 0.94(0.88~1.00); p=0.046]. Conclusions The mPCa patients ≤55 years seemed to be associated with worse prognosis in comparison with patients aging 56-70 years.Background It has been confirmed in many tumors that RNA-binding proteins (RBPs) will affect the progress of cancer, but there is still a lack of large-scale research in gastric cancer (GC). Methods We obtained 13 microarray mRNA expression profiles of the GPL570 platform, and extracted expression from them after integration to analyze the expression differences of RBPs. Enrichment analysis studies the role of these RBPs in GC. Univariate, Lasso and multivariate Cox regression analysis are used to identify independent prognostic hub RBPs, thereby constructing and verifying a prognostic signature. External data and rt-PCR verified the expression of hub RBPs. Results We have identified 51 dysregulated RBPs in GC. Enrichment analysis shows that it can mainly participate in RNA decomposition, modification, processing, etc. and affect the progress of GC. After multiple statistical analysis, six independent prognostic RBPs of GC were determined and a prognostic signature was developed. According to the median risk value, the training cohort was divided into high-risk and low-risk groups.