Comprehensive multi-omics analysis and experimental verification reveal PFDN5 is a novel prognostic and therapeutic biomarker for gastric cancer.

Prefoldin Subunit 5 (PFDN5) plays a critical role as a member of the prefoldins (PFDNs) in maintaining a finely tuned equilibrium between protein production and degradation. However, there has been no comprehensive analysis specifically focused on PFDN5 thus far. Here, a comprehensive multi-omics (transcriptomics, genomics, and proteomics) analysis, systematic molecular biology experiments (in vitro and in vivo), transcriptome sequencing and PCR Array were performed for identifying the value of PFDN5 in pan-cancer, especially in Gastric Cancer (GC). We found PFDN5 had the potential to serve as a prognostic and therapeutic biomarker in GC. And PFDN5 could promote the proliferation of GC cells, primarily by affecting the cell cycle, cell death and immune process etc. These findings provide novel insights into the molecular mechanisms and precise treatments of in GC.

GC-CDSS: Personalized gastric cancer treatment recommendations system based on knowledge graph.

BACKGROUND: Gastric cancer (GC) is one of the most common malignant tumors in the world, posing a serious threat to human health. Currently, gastric cancer treatment strategies emphasize a multidisciplinary team (MDT) consultation approach. However, there are numerous treatment guidelines and insights from clinical trials. The application of AI-based Clinical Decision Support System (CDSS) in tumor diagnosis and screening is increasing rapidly. OBJECTIVE: The purpose of this study is to (1) summarize the treatment decision process for GC according to the treatment guidelines in China, and then create a knowledge graph (KG) for GC, (2) based on aforementioned KG, built a CDSS and conducted an initial feasibility evaluation for the current system. METHODS: Firstly, we summarized the decision-making process for treatment of GC. Then, we extracted relevant decision nodes and relationships and utilized Neo4j to create the KG. After obtaining the initial node features for building the graph embedding model, graph embedding algorithm, such as Node2Vec and GraphSAGE, were used to construct the GC-CDSS. At last, a retrospective cohort study was used to compare the consistency between GC-CDSS and MDT in treatment decision making. RESULTS: In current study, we introduce a GC-CDSS, which is constructed based on Chinese GC treatment guidelines knowledge graph (KG). In the KG, we define four types of nodes and four types of relationships, and it comprise a total of 207 nodes and 300 relationships. Regarding GC-CDSS, the system is capable of providing dynamic and personalized diagnostic and treatment recommendations based on the patient's condition. Furthermore, a retrospective cohort study is conducted to compare GC-CDSS recommendations with those of the MDT group, the overall consistency rate of treatment recommendations between the auxiliary decision system and MDT team is 92.96%. CONCLUSIONS: We construct a GC treatment support system, GC-CDSS, based on KG. The GC-CDSS may help oncologists make treatment decisions more efficient and promote standardization in primary healthcare settings.

Inhibition of METTL3 in macrophages provides protection against intestinal inflammation.

Inflammatory bowel disease (IBD) is prevalent, and no satisfactory therapeutic options are available because the mechanisms underlying its development are poorly understood. In this study, we discovered that increased expression of methyltransferase-like 3 (METTL3) in macrophages was correlated with the development of colitis and that depletion of METTL3 in macrophages protected mice against dextran sodium sulfate (DSS)-induced colitis. Mechanistic characterization indicated that METTL3 depletion increased the YTHDF3-mediated expression of phosphoglycolate phosphatase (PGP), which resulted in glucose metabolism reprogramming and the suppression of CD4+ T helper 1 (Th1) cell differentiation. Further analysis revealed that glucose metabolism contributed to the ability of METTL3 depletion to ameliorate colitis symptoms. In addition, we developed two potent small molecule METTL3 inhibitors, namely, F039-0002 and 7460-0250, that strongly ameliorated DSS-induced colitis. Overall, our study suggests that METTL3 plays crucial roles in the progression of colitis and highlights the potential of targeting METTL3 to attenuate intestinal inflammation for the treatment of colitis.

GWAS and Transcriptomic Analysis Identify OsRING315 as a New Candidate Gene Controlling Amylose Content and Gel Consistency in Rice.

Cooking quality is the main factor determining the market value of rice. Although several major genes and a certain number of QTLs controlling cooking quality have been identified, the genetic complexity and environmental susceptibility limit the further improvement for cooking quality by molecular breeding. This research conducted a genome-wide association study to elucidate the QTLs related to cooking quality including amylose content (AC), gel consistency (GC) and alkali spreading value (ASV) by using 450 rice accessions consisting of 300 indica and 150 japonica accessions in two distinct environments. A total of 54 QTLs were identified, including 25 QTLs for AC, 12 QTLs for GC and 17 QTLs for ASV. Among them, 10 QTLs were consistently observed by the same population in both environments. Six QTLs were co-localized with the reported QTLs or cloned genes. The Wx gene for AC and GC, and the ALK gene for ASV were identified in every population across the two environments. The qAC9-2 for AC and the qGC9-2 for GC were defined to the same interval. The OsRING315 gene, encoding an E3 ubiquitin ligase, was considered as the candidate gene for both qAC9-2 and qGC9-2. The higher expression of OsRING315 corresponded to the lower AC and higher GC. Three haplotypes of OsRING315 were identified. The Hap 1 mainly existed in the japonica accessions and had lower AC. The Hap 2 and Hap 3 were predominantly present in the indica accessions, associated with higher AC. Meanwhile, the GC of accessions harboring Hap 1 was higher than that of accessions harboring Hap 3. In addition, the distribution of the three haplotypes in several rice-growing regions was unbalanced. The three traits of cooking quality are controlled by both major and minor genes and susceptible to environmental factors. The expression level of OsRING315 is related to both AC and GC, and this gene can be a promising target in quality improvement by using the gene editing method. Moreover, the haplotypes of OsRING315 differentiate between indica and japonica, and reveal the differences in GC and AC between indica and japonica rice.

Cancer-derived exosomal lncRNA SNHG3 promotes the metastasis of colorectal cancer through hnRNPC-mediating RNA stability of ß-catenin.

Metastasis is the leading cause of death in colorectal cancer (CRC) patients. By mediating intercellular communication, exosomes exhibit considerable value in regulating tumor metastasis. Long non-coding RNAs (lncRNAs) are abundant in exosomes and participate in regulating tumor progression. However, it is poorly understood how the cancer-secreted exosomal lncRNAs affect CRC proliferation and metastasis. Here, by analyzing the public databases we identified a lncRNA SNHG3 and demonstrated that SNHG3 was delivered through CRC cells-derived exosomes to promote metastasis in CRC. Mechanistically, exosomal SNHG3 was internalized by CRC cells and afterward upregulated the expression of ß-catenin by facilitating the intranuclear transport of hnRNPC. Consequently, the RNA stability of ß-catenin was enhanced which led to the activation of EMT and metastasis of CRC cells. Our findings expand the oncogenic mechanisms of exosomal SNHG3 and identify it as a diagnostic marker for CRC.

NDRG1 enhances the sensitivity to Cetuximab by promoting Stat1 ubiquitylation in colorectal cancer.

INTRODUCTION: Cetuximab (CTX) is an effective targeted drug for the treatment of metastatic colorectal cancer, but it is effective only in patients with wild-type KRAS genes. Even in this subset of patients, the sensitivity of CTX in patients with right hemi-colon cancer is much lower than that in patients with left hemi-colon cancer. This significantly limits its clinical application. Therefore, further elucidation of the underlying molecular mechanisms is needed. N-myc downstream-regulated gene 1 (NDRG1) plays an important role in solid tumor invasion and metastasis, but whether it can influence CTX sensitivity has not been thoroughly investigated. OBJECTIVE: Our study aimed to identify a novel mechanism by which NDRG1 affects CTX sensitivity. METHODS: Through mass spectrometry analysis of our previously constructed CTX-resistant RKO and HCT116 cells, we found that the signal transducer and activator of transcription-1 (Stat1) might be a potential target of NDRG1. By knocking out NDRG1 or/and Stat1 genes, we then applied the loss-of-function experiments to explore the regulatory relationship between NDRG1 and Stat1 and their roles in the cell cycle, epithelial-mesenchymal transition (EMT), and the sensitivity to CTX in these two colorectal cancer (CRC) cells. Finally, we used the nude-mouse transplanted tumor model and human CRC samples to verify the expression of NDRG1 and Stat1 and their impact on CTX sensitivity in vivo. RESULTS: Stat1 was upregulated in CTX-resistant cells, whereas NDRG1 was downregulated. Mechanically, NDRG1 was inversely correlated with Stat1 expression. It suppressed CRC cell proliferation, migration, and invasion, and promoted apoptosis and epithelial-mesenchymal transition (EMT) by inhibiting Stat1. In addition, NDRG1 directly interacted with Stat1 and promoted Smurf1-induced Stat1 ubiquitination. Importantly, this novel NDRG1-dependent regulatory loop also enhanced CTX sensitivity both in vitro and in vivo. CONCLUSION: Our study revealed that NDRG1 enhanced the sensitivity to Cetuximab by inhibiting Stat1 expression and promoting its ubiquitination in colorectal cancer, elucidating NDRG1 might be a potential therapeutic target for refractory CTX-resistant CRC tumors. But its clinical value still needs to be validated in a larger sample size as well as a different genetic background.