Identification of BRMS1L as Metastasis Suppressing Gene in Esophageal Squamous Cell Carcinoma

BRMS1L confers anticancer activity in non-small cell lung cancer by transcriptionally inducing a redox imbalance in the GPX2-ROS pathway

Low expression levels of breast cancer metastasis suppressor 1 like (BRMS1L) have been associated with the growth of cancer cells. However, the mechanisms underlying the role of BRMS1L as an antitumour transcription factor in the progression of NSCLC have not been explored. Herein, we reveal that BRMS1L plays a key role as a tumour suppressor in inhibiting NSCLC proliferation and metastasis. Mechanistically, BRMS1L overexpression results in the downregulation of glutathione peroxidase 2 (GPX2) expression and consequently causes abnormal glutathione metabolism and increased levels of reactive oxygen species (ROS) in cells, inducing oxidative stress injury and apoptosis. Furthermore, overexpression of GPX2 enhances the growth advantage and oxidative stress repair conferred by knockdown of BRMS1L. Importantly, we show that low expression of BRMS1L in NSCLC cells causes relatively high levels of antioxidant accumulation to maintain cell redox balance and renders cancer cells more sensitive to treatment with piperlongumine as an ROS inducer both in vitro and in vivo. These findings offer new insights into the role of BRMS1L as a transcriptional repressor in NSCLC and suggest that the BRMS1L expression level may be a potential biomarker for predicting the therapeutic response to small molecule ROS inducers, providing new ideas for targeted therapy.

Machine learning-identified stemness features and constructed stemness-related subtype with prognosis, chemotherapy, and immunotherapy responses for non-small cell lung cancer patients

AIM

This study aimed to explore a novel subtype classification method based on the stemness characteristics of patients with non-small cell lung cancer (NSCLC).

METHODS

Based on the Cancer Genome Atlas database to calculate the stemness index (mRNAsi) of NSCLC patients, an unsupervised consensus clustering method was used to classify patients into two subtypes and analyze the survival differences, somatic mutational load, copy number variation, and immune characteristics differences between them. Subsequently, four machine learning methods were used to construct and validate a stemness subtype classification model, and cell function experiments were performed to verify the effect of the signature gene ARTN on NSCLC.

RESULTS

Patients with Stemness Subtype I had better PFS and a higher somatic mutational burden and copy number alteration than patients with Stemness Subtype II. In addition, the two stemness subtypes have different patterns of tumor immune microenvironment. The immune score and stromal score and overall score of Stemness Subtype II were higher than those of Stemness Subtype I, suggesting a relatively small benefit to immune checkpoints. Four machine learning methods constructed and validated classification model for stemness subtypes and obtained multiple logistic regression equations for 22 characteristic genes. The results of cell function experiments showed that ARTN can promote the proliferation, invasion, and migration of NSCLC and is closely related to cancer stem cell properties.

CONCLUSION

This new classification method based on stemness characteristics can effectively distinguish patients' characteristics and thus provide possible directions for the selection and optimization of clinical treatment plans.

Cancer chemoprevention through Frizzled receptors and EMT

Frizzled (FZD) transmembrane receptors are well known for their role in β-catenin signaling and development and now understanding of their role in the context of cancer is growing. FZDs are often associated with the process of epithelial to mesenchymal transition (EMT) through β-catenin, but some also influence EMT through non-canonical pathways. With ten different FZDs, there is a wide range of activity from oncogenic to tumor suppressive depending on the tissue context. Alterations in FZD signaling can occur during development of premalignant lesions, supporting their potential as targets of chemoprevention agents. Agonizing or antagonizing FZD activity may affect EMT, which is a key process in lesion progression often targeted by chemoprevention agents. Recent studies identified a specific FZD as important for activity of an EMT inhibiting chemopreventive agent and other studies have highlighted the previously unrecognized potential for targeting small molecules to FZD receptors. This work demonstrates the value of investigating FZDs in chemoprevention and here we provide a review of FZDs in cancer EMT and their potential as chemoprevention targets.

Identification of CDC5L as bridge gene between chronic obstructive pulmonary disease and lung adenocarcinoma

Aim: This study aimed to explore the genetic and epigenetic similarities between chronic obstructive pulmonary disease (COPD) and lung adenocarcinoma (LUAD). Materials & methods: We mainly used Weighted correlation network analysis, protein-protein interaction network and pivot analysis to identify hub modules, bridge regulators, bridge genes and hub-driving genes in both diseases and carried out verifying using external datasets. Results: We identified eight bridge regulators, 19 key molecules in the COPD model and ten key molecules in the LUAD model. Moreover, we validated that CDC5L could be a reliable biomarker in COPD and may regulate cell proliferation and metastasis in LUAD via promoter methylation. Conclusion: Our results might form a theoretical foundation for future study at an epigenetic level.