Genomic retargeting of p53 and CTCF is associated with transcriptional changes during oncogenic HRas-induced transformation

Epithelial recognition and elimination against aberrant cells

Epithelial cells, which are non-immune cells, not only function as a physical defence barrier but also continuously monitor and eliminate aberrant epithelial cells in their vicinity. In other words, it has become evident that epithelial cells possess immune cell-like functions. In fact, recent research has revealed that epithelial cells recognise the Major Histocompatibility Complex I (MHC-I) of aberrant cells as a mechanism for surveillance. This cellular defence mechanism of epithelial cells probably detects aberrant cells more promptly than the conventional immune response, making it a novel and primary biological defence. Furthermore, there is the potential for this new immune-like biological defence mechanism to establish innovative treatment for disease prevention, leading to increasing anticipation for its future medical applications. In this review, we aim to summarise the recognition and attack mechanisms of aberrant cells by epithelial cells in mammals, with a particular focus on the field of cancer. Additionally, we discuss the potential therapeutic applications of epithelial cell-based defence against cancer, including novel prophylactic treatment methods based on molecular mechanisms.

Epithelial cells remove precancerous cells by cell competition via MHC class I-LILRB3 interaction

Epithelial cells have an ability termed 'cell competition', which is an immune surveillance-like function that extrudes precancerous cells from the epithelial layer, leading to apoptosis and clearance. However, it remains unclear how epithelial cells recognize and extrude transformed cells. Here, we discovered that a PirB family protein, leukocyte immunoglobulin-like receptor B3 (LILRB3), which is expressed on non-transformed epithelial cells, recognizes major histocompatibility complex class I (MHC class I) that is highly expressed on transformed cells. MHC class I interaction with LILRB3 expressed on normal epithelial cells triggers an SHP2-ROCK2 pathway that generates a mechanical force to extrude transformed cells. Removal of transformed cells occurs independently of natural killer (NK) cell or CD8⁺ cytotoxic T cell-mediated activity. This is a new mechanism in that the immunological ligand-receptor system generates a mechanical force in non-immune epithelial cells to extrude precancerous cells in the same epithelial layer.

A systematic view of computational methods for identifying driver genes based on somatic mutation data

Abnormal changes of driver genes are serious for human health and biomedical research. Identifying driver genes, exactly from enormous genes with mutations, promotes accurate diagnosis and treatment of cancer. A lot of works about uncovering driver genes have been developed over the past decades. By analyzing previous works, we find that computational methods are more efficient than traditional biological experiments when distinguishing driver genes from massive data. In this study, we summarize eight common computational algorithms only using somatic mutation data. We first group these methods into three categories according to mutation features they apply. Then, we conclude a general process of nominating candidate cancer driver genes. Finally, we evaluate three representative methods on 10 kinds of cancer derived from The Cancer Genome Atlas Program and five Chinese projects from the International Cancer Genome Consortium. In addition, we compare results of methods with various parameters. Evaluation is performed from four perspectives, including CGC, OG/TSG, Q-value and QQQuantile-Quantileplot. To sum up, we present algorithms using somatic mutation data in order to offer a systematic view of various mutation features and lay the foundation of methods based on integration of mutation information and other types of data.