EVI1 Promotes the Proliferation and Invasive Properties of Human Head and Neck Squamous Cell Carcinoma Cells

The C. elegans anchor cell: A model to elucidate mechanisms underlying invasion through basement membrane

Cell invasion through basement membrane barriers is crucial during many developmental processes and in immune surveillance. Dysregulation of invasion also drives the pathology of numerous human diseases, such as metastasis and inflammatory disorders. Cell invasion involves dynamic interactions between the invading cell, basement membrane, and neighboring tissues. Owing to this complexity, cell invasion is challenging to study in vivo, which has hampered the understanding of mechanisms controlling invasion. Caenorhabditis elegans anchor cell invasion is a powerful in vivo model where subcellular imaging of cell-basement membrane interactions can be combined with genetic, genomic, and single-cell molecular perturbation studies. In this review, we outline insights gained by studying anchor cell invasion, which span transcriptional networks, translational regulation, secretory apparatus expansion, dynamic and adaptable protrusions that breach and clear basement membrane, and a complex, localized metabolic network that fuels invasion. Together, investigation of anchor cell invasion is building a comprehensive understanding of the mechanisms that underlie invasion, which we expect will ultimately facilitate better therapeutic strategies to control cell invasive activity in human disease.

MECOM: a bioinformatics and experimentally identified marker for the diagnosis and prognosis of lung adenocarcinoma

Objective: We aimed to explore the clinical value of MDS1 and EVI1 complex locus (MECOM) in lung adenocarcinoma (LUAD). Methods: Bioinformatics and experimental validation confirmed MECOM expression levels in LUAD. The value of MECOM was analyzed by receiver operating characteristic (ROC) curve and Cox regression analysis. Results: Serum MECOM levels were lower in LUAD and correlated with gender, TNM stage, tumor size, lymph node metastasis and distant metastasis. The ROC curve showed that the area under the curve of MECOM was 0.804 for LUAD and, of note, could reach 0.889 for advanced LUAD; specificity was up to 90%. Conclusion: MECOM may contribute to independently identifying LUAD patients, particularly in advanced stages.

ImaGene: a web-based software platform for tumor radiogenomic evaluation and reporting

Summary

Radiographic imaging techniques provide insight into the imaging features of tumor regions of interest, while immunohistochemistry and sequencing techniques performed on biopsy samples yield omics data. Relationships between tumor genotype and phenotype can be identified from these data through traditional correlation analyses and artificial intelligence (AI) models. However, the radiogenomics community lacks a unified software platform with which to conduct such analyses in a reproducible manner. To address this gap, we developed ImaGene, a web-based platform that takes tumor omics and imaging datasets as inputs, performs correlation analysis between them, and constructs AI models. ImaGene has several modifiable configuration parameters and produces a report displaying model diagnostics. To demonstrate the utility of ImaGene, we utilized data for invasive breast carcinoma (IBC) and head and neck squamous cell carcinoma (HNSCC) and identified potential associations between imaging features and nine genes (WT1, LGI3, SP7, DSG1, ORM1, CLDN10, CST1, SMTNL2, and SLC22A31) for IBC and eight genes (NR0B1, PLA2G2A, MAL, CLDN16, PRDM14, VRTN, LRRN1, and MECOM) for HNSCC. ImaGene has the potential to become a standard platform for radiogenomic tumor analyses due to its ease of use, flexibility, and reproducibility, playing a central role in the establishment of an emerging radiogenomic knowledge base.

Availability and implementation

www.ImaGene.pgxguide.org, https://github.com/skr1/Imagene.git.

Supplementary information

Supplementary data are available at https://github.com/skr1/Imagene.git.