RS1 gene is a novel prognostic biomarker for lung adenocarcinoma

Advances in understanding the molecular structure of retinoschisin while questions remain of biological function

Retinoschisin (RS1) is a secreted protein that is essential for maintaining integrity of the retina. Numerous mutations in RS1 cause X-linked retinoschisis (XLRS), a progressive degeneration of the retina that leads to vision loss in young males. A key manifestation of XLRS is the formation of cavities (cysts) in the retina and separation of the layers (schisis), disrupting synaptic transmission. There are currently no approved treatments for patients with XLRS. Strategies using adeno-associated viral (AAV) vectors to deliver functional copies of RS1 as a form of gene augmentation therapy, are under clinical evaluation. To improve therapeutic strategies for treating XLRS, it is critical to better understand the secretion of RS1 and its molecular function. Immunofluorescence and immunoelectron microscopy show that RS1 is located on the surfaces of the photoreceptor inner segments and bipolar cells. Sequence homology indicates a discoidin domain fold, similar to many other proteins with demonstrated adhesion functions. Recent structural studies revealed the tertiary structure of RS1 as two back-to-back octameric rings, each cross-linked by disulfides. The observation of higher order structures in vitro suggests the formation of an adhesive matrix spanning the distance between cells (∼100 nm). Several studies indicated that RS1 readily binds to other proteins such as the sodium-potassium ATPase (NaK-ATPase) and extracellular matrix proteins. Alternatively, RS1 may influence fluid regulation via interaction with membrane proteins such as the NaK-ATPase, largely inferred from the use of carbonic anhydrase inhibitors to shrink the typical intra-retinal cysts in XLRS. We discuss these models in light of RS1 structure and address the difficulty in understanding the function of RS1.

Using Single-Cell RNA Sequencing and MicroRNA Targeting Data to Improve Colorectal Cancer Survival Prediction

Colorectal cancer has proven to be difficult to treat as it is the second leading cause of cancer death for both men and women worldwide. Recent work has shown the importance of microRNA (miRNA) in the progression and metastasis of colorectal cancer. Here, we develop a metric based on miRNA-gene target interactions, previously validated to be associated with colorectal cancer. We use this metric with a regularized Cox model to produce a small set of top-performing genes related to colon cancer. We show that using the miRNA metric and a Cox model led to a meaningful improvement in colon cancer survival prediction and correct patient risk stratification. We show that our approach outperforms existing methods and that the top genes identified by our process are implicated in NOTCH3 signaling and general metabolism pathways, which are essential to colon cancer progression.