Knockdown of SETD5 Inhibits Colorectal Cancer Cell Growth and Stemness by Regulating PI3K/AKT/mTOR Pathway.

SET domain-containing 5 (SETD5), a member of protein lysine methyltransferase family, is expressed in multiple cancers, making it potential therapeutic targets. However, the role of SETD5 in colorectal cancer remains largely unknown. The expression of SETD5 in the 30 pairs colorectal cancer tissues samples and cell lines were determined by qRT-PCR. The functions of SETD5 was detected by knocked-down or overexpression in colorectal cancer cell lines SW480 and HCT116 cells. Cell proliferative activity, cell death, and stemness characteristics were assessed. BEZ235, a PI3K/AKT/mTOR pathway inhibitor, was used to perform rescue experiment to analyze whether SETD5 exerted its effects through activating PI3K/AKT/mTOR pathway. SETD5 was substantially upregulated in colorectal cancer, and correlated to metastasis and clinical stage of patients. Knockdown of SETD5 inhibited SW480 and HCT116 cell growth, as evidenced by the inhibition of cell viability and clone-forming. Moreover, Knockdown of SETD5 suppressed the capability of tumor sphere formation of SW480 and HCT116 cells, and reduced the expression of stemness-related proteins Nanog and Sox2. Further western blot analysis revealed that SETD5 knockdown inhibited the phosphorylation of proteins associated with the PI3K/AKT/mTOR pathway. In contrast, overexpression of SETD5 exerted the opposite effects. Mechanistically, by blocking PI3K/AKT/mTOR pathway with BEZ235, the effects of SETD5 overexpression on cell viability and Nanog and Sox2 protein expression were reversed. Our results substantiated that SETD5 functioned as an oncogene by promoting cell growth and stemness in colorectal cancer cells through activating the PI3K/AKT/mTOR signaling pathway.

A deep learning-based model improves diagnosis of early gastric cancer under narrow band imaging endoscopy.

BACKGROUND: Diagnosis of early gastric cancer (EGC) under narrow band imaging endoscopy (NBI) is dependent on expertise and skills. We aimed to elucidate whether artificial intelligence (AI) could diagnose EGC under NBI and evaluate the diagnostic assistance of the AI system. METHODS: In this retrospective diagnostic study, 21,785 NBI images and 20 videos from five centers were divided into a training dataset (13,151 images, 810 patients), an internal validation dataset (7057 images, 283 patients), four external validation datasets (1577 images, 147 patients), and a video validation dataset (20 videos, 20 patients). All the images were labeled manually and used to train an AI system using You look only once v3 (YOLOv3). Next, the diagnostic performance of the AI system and endoscopists were compared and the diagnostic assistance of the AI system was assessed. The accuracy, sensitivity, specificity, and AUC were primary outcomes. RESULTS: The AI system diagnosed EGCs on validation datasets with AUCs of 0.888-0.951 and diagnosed all the EGCs (100.0%) in video dataset. The AI system achieved better diagnostic performance (accuracy, 93.2%, 95% CI, 90.0-94.9%) than senior (85.9%, 95% CI, 84.2-87.4%) and junior (79.5%, 95% CI, 77.8-81.0%) endoscopists. The AI system significantly enhanced the performance of endoscopists in senior (89.4%, 95% CI, 87.9-90.7%) and junior (84.9%, 95% CI, 83.4-86.3%) endoscopists. CONCLUSION: The NBI AI system outperformed the endoscopists and exerted potential assistant impact in EGC identification. Prospective validations are needed to evaluate the clinical reinforce of the system in real clinical practice.

Inhibition of ribosomal RNA processing 15 Homolog (RRP15), which is overexpressed in hepatocellular carcinoma, suppresses tumour growth via induction of senescence and apoptosis.

Recent studies suggest that RRP15 (Ribosomal RNA Processing 15 Homolog) might be a potential target for cancer therapy. However, the role of RRP15 in hepatocarcinogenesis remains poorly delineated. In this study, we aimed to evaluate the expression and biological function of RRP15 in human hepatocellular carcinoma (HCC). We show that RRP15 was up regulated in HCC cell lines and tumours. Up-regulation of RRP15 in HCC tumours was also correlated with unfavorable prognosis. We further show that the frequent up-regulation of RRP15 in HCCs is at least partly driven by recurrent gene copy gain at chromosome 1q41. Functional studies indicated that RRP15 knockdown suppresses HCC proliferation and growth both in vitro and in vivo. Mechanistically, RRP15 depletion in p53-wild-type HepG2 cells induced senescence via activation of the p53-p21 signalling pathway through enhanced interaction of RPL11 with MDM2, as well as inhibition of SIRT1-mediated p53 deacetylation. Moreover, RRP15 depletion in p53-mutant PLC5 and p53-deleted Hep3B cells induced metabolic shift from the glycolytic pentose-phosphate to mitochondrial oxidative phosphorylation via regulating a series of key genes such as HK2 and TIGAR, and thus, promoted the generation of ROS and apoptosis. Taken together, our findings provide evidence for an important role of the RRP15 gene in hepatocarcinogenesis through regulation of HCC proliferation and growth, raising the possibility that targeting RRP15 may represent a potential therapeutic strategy for HCC treatment.

Dual threat of comorbidity of celiac disease and systemic lupus erythematosus.

Celiac disease (CD) is a chronic immune-mediated intestinal disease that is characterized by production of autoantibodies directed against the small intestine. The main clinical manifestations of CD are typically defined as those related to indigestion and malabsorption. These manifestations include unexplained diarrhea or constipation, abdominal pain, bloating, weight loss, anemia, failure-to-thrive in children, and decreased bone density. Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by heterogeneous clinical manifestations, which may also involve the gastrointestinal tract. Comorbidity of CD and SLE is rare, and the overlapping symptoms and nonspecific clinical presentation may pose a diagnostic challenge to clinicians. We report here a case of SLE with CD, which mainly manifested as recurrent diarrhea, uncorrectable electrolyte disorders, and severe malnutrition. Through review, we hope to further improve our understanding and diagnostic level of this combination of diseases.

Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study.

BACKGROUND: We aimed to develop and validate a real-time deep convolutional neural networks (DCNNs) system for detecting early gastric cancer (EGC). METHODS: All 45,240 endoscopic images from 1364 patients were divided into a training dataset (35823 images from 1085 patients) and a validation dataset (9417 images from 279 patients). Another 1514 images from three other hospitals were used as external validation. We compared the diagnostic performance of the DCNN system with endoscopists, and then evaluated the performance of endoscopists with or without referring to the system. Thereafter, we evaluated the diagnostic ability of the DCNN system in video streams. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value and Cohen's kappa coefficient were measured to assess the detection performance. FINDING: The DCNN system showed good performance in EGC detection in validation datasets, with accuracy (85.1%-91.2%), sensitivity (85.9%-95.5%), specificity (81.7%-90.3%), and AUC (0.887-0.940). The DCNN system showed better diagnostic performance than endoscopists and improved the performance of endoscopists. The DCNN system was able to process oesophagogastroduodenoscopy (OGD) video streams to detect EGC lesions in real time. INTERPRETATION: We developed a real-time DCNN system for EGC detection with high accuracy and stability. Multicentre prospective validation is needed to acquire high-level evidence for its clinical application. FUNDING: This work was supported by the National Natural Science Foundation of China (grant nos. 81672935 and 81871947), Jiangsu Clinical Medical Center of Digestive System Diseases and Gastrointestinal Cancer (grant no. YXZXB2016002), and Nanjing Science and Technology Development Foundation (grant no. 2017sb332019).