Hub gene identification and molecular subtype construction for Helicobacter pylori in gastric cancer via machine learning methods and NMF algorithm.

Helicobacter pylori (HP) is a gram-negative and spiral-shaped bacterium colonizing the human stomach and has been recognized as the risk factor of gastritis, peptic ulcer disease, and gastric cancer (GC). Moreover, it was recently identified as a class I carcinogen, which affects the occurrence and progression of GC via inducing various oncogenic pathways. Therefore, identifying the HP-related key genes is crucial for understanding the oncogenic mechanisms and improving the outcomes of GC patients. We retrieved the list of HP-related gene sets from the Molecular Signatures Database. Based on the HP-related genes, unsupervised non-negative matrix factorization (NMF) clustering method was conducted to stratify TCGA-STAD, GSE15459, GSE84433 samples into two clusters with distinct clinical outcomes and immune infiltration characterization. Subsequently, two machine learning (ML) strategies, including support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF), were employed to determine twelve hub HP-related genes. Beyond that, receiver operating characteristic and Kaplan-Meier curves further confirmed the diagnostic value and prognostic significance of hub genes. Finally, expression of HP-related hub genes was tested by qRT-PCR array and immunohistochemical images. Additionally, functional pathway enrichment analysis indicated that these hub genes were implicated in the genesis and progression of GC by activating or inhibiting the classical cancer-associated pathways, such as epithelial-mesenchymal transition, cell cycle, apoptosis, RAS/MAPK, etc. In the present study, we constructed a novel HP-related tumor classification in different datasets, and screened out twelve hub genes via performing the ML algorithms, which may contribute to the molecular diagnosis and personalized therapy of GC.

Soluble epoxide hydrolase deficiency promotes liver regeneration and ameliorates liver injury in mice by regulating angiocrine factors and angiogenesis.

BACKGROUND: Soluble epoxide hydrolase (sEH) is a key enzyme for the hydrolysis of epoxyeicosatrienoic acids (EETs) and has been implicated in the pathogenesis of hepatic inflammation, fibrosis, cancer, and nonalcoholic fatty liver disease. However, the role of sEH in liver regeneration and injury remains unclear. METHODS: This study used sEH-deficient (sEH-/-) mice and wild-type (WT) mice. Hepatocyte proliferation was assessed by immunohistochemical (IHC) staining for Ki67. Liver injury was evaluated by histological staining with hematoxylin and eosin (H&E), Masson's trichrome, and Sirius red, as well as IHC staining for α-SMA. Hepatic macrophage infiltration and angiogenesis were reflected by IHC staining for CD68 and CD31. Liver angiocrine levels were detected by ELISA. The mRNA levels of angiocrine or cell cycle-related genes were measured by quantitative real-time RT-PCR (qPCR). The protein levels of cell proliferation-related protein and phosphorylated signal transducer and activator of transcription 3 (STAT3) were detected by western blotting. RESULTS: sEH mRNA and protein levels were significantly upregulated in mice after 2/3 partial hepatectomy (PHx). Compared with WT mice, sEH-/- mice exhibited a higher liver/body weight ratio and more Ki67-positive cells on days 2 and 3 after PHx. The accelerated liver regeneration in sEH-/- mice was attributed to angiogenesis and endothelial-derived angiocrine (HGF) production. Subsequently, hepatic protein expression of cyclinD1 (CYCD1) and the downstream direct targets of the STAT3 pathway, such as c-fos, c-jun, and c-myc, were also suppressed post-PHx in sEH-/- compared to WT mice. Furthermore, sEH deficiency attenuated CCl4-induced acute liver injury and reduced fibrosis in both CCl4 and bile duct ligation (BDL)-induced liver fibrosis rodent models. Compared with WT mice, sEH-/- mice had slightly decreased hepatic macrophage infiltration and angiogenesis. Meanwhile, sEH-/- BDL mice had more Ki67-positive cells in the liver than WT BDL mice. CONCLUSIONS: sEH deficiency alters the angiocrine profile of liver endothelial to accelerate hepatocyte proliferation and liver regeneration, and blunts acute liver injury and fibrosis by inhibiting inflammation and angiogenesis. sEH inhibition is a promising target for liver diseases to improve liver regeneration and damage.

A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022).

Background: Colorectal cancer (CRC) has the third-highest incidence and second-highest mortality rate of all cancers worldwide. Early diagnosis and screening of CRC have been the focus of research in this field. With the continuous development of artificial intelligence (AI) technology, AI has advantages in many aspects of CRC, such as adenoma screening, genetic testing, and prediction of tumor metastasis. Objective: This study uses bibliometrics to analyze research in AI in CRC, summarize the field's history and current status of research, and predict future research directions. Method: We searched the SCIE database for all literature on CRC and AI. The documents span the period 2002-2022. we used bibliometrics to analyze the data of these papers, such as authors, countries, institutions, and references. Co-authorship, co-citation, and co-occurrence analysis were the main methods of analysis. Citespace, VOSviewer, and SCImago Graphica were used to visualize the results. Result: This study selected 1,531 articles on AI in CRC. China has published a maximum number of 580 such articles in this field. The U.S. had the most quality publications, boasting an average citation per article of 46.13. Mori Y and Ding K were the two authors with the highest number of articles. Scientific Reports, Cancers, and Frontiers in Oncology are this field's most widely published journals. Institutions from China occupy the top 9 positions among the most published institutions. We found that research on AI in this field mainly focuses on colonoscopy-assisted diagnosis, imaging histology, and pathology examination. Conclusion: AI in CRC is currently in the development stage with good prospects. AI is currently widely used in colonoscopy, imageomics, and pathology. However, the scope of AI applications is still limited, and there is a lack of inter-institutional collaboration. The pervasiveness of AI technology is the main direction of future housing development in this field.

Multiomics characteristics and immunotherapeutic potential of EZH2 in pan-cancer.

Enhancer of zeste homolog 2 (EZH2) is a significant epigenetic regulator that plays a critical role in the development and progression of cancer. However, the multiomics features and immunological effects of EZH2 in pan-cancer remain unclear. Transcriptome and clinical raw data of pan-cancer samples were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and subsequent data analyses were conducted by using R software (version 4.1.0). Furthermore, numerous bioinformatics analysis databases also reapplied to comprehensively explore and elucidate the oncogenic mechanism and therapeutic potential of EZH2 from pan-cancer insight. Finally, quantitative reverse transcription polymerase chain reaction and immunohistochemical assays were performed to verify the differential expression of EZH2 gene in various cancers at the mRNA and protein levels. EZH2 was widely expressed in multiple normal and tumor tissues, predominantly located in the nucleoplasm. Compared with matched normal tissues, EZH2 was aberrantly expressed in most cancers either at the mRNA or protein level, which might be caused by genetic mutations, DNA methylation, and protein phosphorylation. Additionally, EZH2 expression was correlated with clinical prognosis, and its up-regulation usually indicated poor survival outcomes in cancer patients. Subsequent analysis revealed that EZH2 could promote tumor immune evasion through T-cell dysfunction and T-cell exclusion. Furthermore, expression of EZH2 exhibited a strong correlation with several immunotherapy-associated responses (i.e., immune checkpoint molecules, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) status, and neoantigens), suggesting that EZH2 appeared to be a novel target for evaluating the therapeutic efficacy of immunotherapy.