Pancreatic ductal adenocarcinoma (PDAC) features substantial matrix stiffening and reprogrammed glucose metabolism, particularly the Warburg effect. However, the complex interplay between these traits and their impact on tumor advancement remains inadequately explored. Here, we integrated clinical, cellular, and bioinformatics approaches to explore the connection between matrix stiffness and the Warburg effect in PDAC, identifying CLIC1 as a key mediator.
View Article and Find Full Text PDFBackground: This study investigated the molecular mechanism of long intergenic non-protein coding RNA 1605 (LINC01605) in the process of tumor growth and liver metastasis of pancreatic ductal adenocarcinoma (PDAC).
Methods: LINC01605 was filtered out with specificity through TCGA datasets (related to DFS) and our RNA-sequencing data of PDAC tissue samples from Renji Hospital. The expression level and clinical relevance of LINC01605 were then verified in clinical cohorts and samples by immunohistochemical staining assay and survival analysis.
Background: OCIAD2(Ovarian carcinoma immunoreactive antigen-like protein 2) is a protein reported in various cancers. However, the role of OCIAD2 has not been explored in pan-cancer datasets. The purpose of this research lies in analyzing the expression level and prognostic-related value of OCIAD2 in different human cancers, as well as revealing the underlying mechanism in specific cancer type (pancreatic adenocarcinoma, PAAD).
View Article and Find Full Text PDFPancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer, is characterized by poor treatment response and low survival time. The current clinical treatment for advanced PDAC is still not effective. In recent years, the research and application of immunotherapy have developed rapidly and achieved substantial results in many malignant tumors.
View Article and Find Full Text PDFPancreatic adenocarcinoma (PAAD), one of the most malignant tumors, not only has abundant mesenchymal components, but is also characterized by an extremely high metastatic risk. The purpose of this study was to construct a model of stroma- and metastasis-associated prognostic signature, aiming to benefit the existing clinical staging system and predict the prognosis of patients. First, stroma-associated genes were screened from the TCGA database with the ESTIMATE algorithm.
View Article and Find Full Text PDFSichuan Da Xue Xue Bao Yi Xue Ban
May 2022
Objective: To establish a brain hematoma CT image segmentation method based on watershed and region-growing algorithm so as to measure hematoma volume quickly and accurately, to explore the consistency between the results of this segmentation method and those of manual segmentation, the clinical gold standard, and to compare the results of this method with the calculation of the two Tada formulas commonly used in clinical practice.
Methods: The preoperative CT images of 152 patients who were treated for spontaneous cerebral hemorrhage at the Department of Neurosurgery, West China Hospital, Sichuan University between January 2018 and June 2019 were retrospectively collected. The CT images were randomly assigned, by using a random number table, to the training set, the test set and the validation set, which contained 100 patients, 22 patients and 30 patients, respectively.