Mechanistic insights into genomic structure and functions of a novel oncogene YEATS4.

As a novel oncogene, the role of YEATS domain-containing protein 4 (YEATS4) in the occurrence, development, and treatment of tumors is now beginning to be appreciated. YEATS4 plays an important role in regulating DNA repair during replication. The upregulation of YEAST4 promotes DNA damage repair and prevents cell death, whereas its downregulation inhibits DNA replication and induces apoptosis. Additionally, accumulating evidence indicates that the aberrant activation of YEATS4 leads to changes in drug resistance, epithelial-mesenchymal transition and also in the migration and invasion capacity of tumor cells. Therefore, specific inhibition of the expression or activity of YEATS4 protein may be an effective strategy for inhibiting the proliferation, motility, differentiation, and/or survival of tumor cells. Taken together, YEATS4 has emerged as a potential target for multiple cancers and is an attractive protein for the development of small-molecule inhibitors. However, research on YEAST4 in tumor-related fields is limited and its biological functions, metabolism, and the regulatory mechanism of YEATS4 in numerous cancers remain undetermined. This review comprehensively and extensively summarizes the functions, structure and oncogenic roles of YEATS4 in cancer progression and aims to further contribute to the study of its underlying molecular mechanism and targeted drugs.

Mechanistic insights into UHRF1­mediated DNA methylation by structure­based functional clarification of UHRF1 domains (Review).

Epigenetic modification is crucial for transmitting genetic information, while abnormalities in DNA methylation modification are primarily associated with cancer and neurological diseases. As a multifunctional epigenetic modifier, ubiquitin like with PHD and ring finger domains 1 (UHRF1) mainly affects cell energy metabolism and cell cycle control. It also inhibits the transcription of tumor suppressor genes through DNA and/or histone methylation modifications, promoting the occurrence and development of cancer. Therefore, comprehensively understanding the molecular mechanism of the epigenetic modification of UHRF1 in tumors will help identify targets for inhibiting the expression and function of UHRF1. Notably, each domain of UHRF1 functions as a whole and differently. Thus, the abnormality of any domain can lead to a change in phenotype or disease. However, the specific regulatory mechanism and proteins of each domain have not been fully elucidated. The present review aimed to contribute to the study of the regulatory mechanism of UHRF1 to a greater extent in different cancers and provide ideas for drug research by clarifying the function of UHRF1 domains.

Functions and modulation of PKM2 activity by human papillomavirus E7 oncoprotein (Review).

Most tumor cells still exhibit active glucose uptake and glycolysis under aerobic conditions, a phenomenon known as the Warburg effect or aerobic glycolysis. Pyruvate kinase, one of the key enzymes in the cell glycolysis pathway, can promote the conversion of glucose to pyruvate and produce energy. Pyruvate kinase M2 (PKM2), a competitive PK subtype, is an important regulator of the aerobic glycolysis pathway in tumor cells and plays a direct role in gene expression and cell cycle regulation. Human papillomavirus (HPV) persistence is the main risk factor for cervical cancer. In recent years, it has been discovered that HPV plays an important role in malignant anal tumors and oral cancer. HPV oncoprotein E7 can promote the Warburg effect and produce a large amount of ATP, which may meet the energy requirements of cancer cell division. There appears to be a regulatory relationship between HPV E7 and PKM2, but the specific mechanism is mostly unknown. The present review article discusses the role of HPV E7 in transcriptional regulation, enzyme activity regulation, protein kinase activity regulation, post-translational modification and the immune microenvironment of PKM2 in the occurrence and development of cervical cancer.

Radiomics and artificial neural networks modelling for identification of high-risk carotid plaques.

Objective: In this study, we aimed to investigate the classification of symptomatic plaques by evaluating the models generated via two different approaches, a radiomics-based machine learning (ML) approach, and an end-to-end learning approach which utilized deep learning (DL) techniques with several representative model frameworks. Methods: We collected high-resolution magnetic resonance imaging (HRMRI) data from 104 patients with carotid artery stenosis, who were diagnosed with either symptomatic plaques (SPs) or asymptomatic plaques (ASPs), in two medical centers. 74 patients were diagnosed with SPs and 30 patients were ASPs. Sampling Perfection with Application-optimized Contrasts (SPACE) by using different flip angle Evolutions was used for MRI imaging. Repeated stratified five-fold cross-validation was used to evaluate the accuracy and receiver operating characteristic (ROC) of the trained classifier. The two proposed approaches were investigated to train the models separately. The difference in the model performance of the two proposed methods was quantitatively evaluated to find a better model to differentiate between SPs and ASPs. Results: 3D-SE-Densenet-121 model showed the best performance among all prediction models (AUC, accuracy, precision, sensitivity, and F1-score of 0.9300, 0.9308, 0.9008, 0.8588, and 0.8614, respectively), which were 0.0689, 0.1119, 0.1043, 0.0805, and 0.1089 higher than the best radiomics-based ML model (MLP). Decision curve analysis showed that the 3D-SE-Densenet-121 model delivered more net benefit than the best radiomics-based ML model (MLP) with a wider threshold probability. Conclusion: The DL models were able to accurately differentiate between symptomatic and asymptomatic carotid plaques with limited data, which outperformed radiomics-based ML models in identifying symptomatic plaques.

The α5-nAChR/PD-L1 axis facilitates lung adenocarcinoma cell migration and invasion.

α5 nicotinic acetylcholine receptor (α5-nAChR) is associated with the progression of smoking-related lung adenocarcinoma (LUAD), but the molecular mechanism is unclear. Programmed death ligand 1 (PD-L1) is encoded by the CD274 gene, which not only inhibits the immune system, but also plays a unique role in tumor growth and metastasis. Here, we gained important insights into the underlying mechanism between α5-nAChR and PD-L1 in LUAD progression. α5-nAChR was overexpressed in various histological subtypes, cancer stages and metastasis statuses of LUAD. The group that coexpressed α5-nAChR and PD-L1 had a worse prognosis than the other subgroups at different stages of LUAD lymph node metastasis. The expression of α5-nAChR and PD-L1 was associated with epithelial-mesenchymal transition (EMT) marker CDH2. In vitro, α5-nAChR mediated nicotine-induced PD-L1 expression via STAT3 and the expression of EMT markers. Downregulation of α5-nAChR and/or PD-L1 inhibited EMT marker expression, cell proliferation, migration and invasion compared to silencing α5-nAChR or PD-L1 alone in LUAD cells. Furthermore, α5-nAChR expression was associated with PD-L1 and EMT marker expression in mouse xenograft models. These results highlight that α5-nAChR mediates STAT3/PD-L1 signaling, which contributes to cell migration and invasion. Therefore, our study may reveal a new interaction between α5-nAChR and PD-L1 that is involved in tumor cell growth and progression in LUAD, which may be a promising target for NSCLC diagnosis and immunotherapy.