Non-small cell lung cancers (NSCLCs) harbor thousands of passenger events that hide genetic drivers. Even highly recurrent events in NSCLC, such as mutations in PTEN, EGFR, KRAS, and ALK, are only detected in, at most, 30% of patients. Thus, many unidentified low-penetrant events are causing a significant portion of lung cancers. To detect low-penetrance drivers of NSCLC a forward genetic screen was performed in mice using the Sleeping Beauty (SB) DNA transposon as a random mutagen to generate lung tumors in a Pten deficient background. SB mutations coupled with Pten deficiency were sufficient to produce lung tumors in 29% of mice. Pten deficiency alone, without SB mutations, resulted in lung tumors in 11% of mice, while the rate in control mice was ~3%. In addition, thyroid cancer and other carcinomas as well as the presence of bronchiolar and alveolar epithelialization in mice deficient for Pten were also identified. Analysis of common transposon insertion sites identified 76 candidate cancer driver genes. These genes are frequently dysregulated in human lung cancers and implicate several signaling pathways. Cullin3 (Cul3), a member of an ubiquitin ligase complex that plays a role in the oxidative stress response pathway, was identified in the screen and evidence demonstrates that Cul3 functions as a tumor suppressor.
Dentin sialophosphoprotein (DSPP) is one of the major non-collagenous proteins present in dentin, cementum and alveolar bone; it is also transiently expressed by ameloblasts. In humans many mutations have been found in DSPP and are associated with two autosomal-dominant genetic diseases — dentinogenesis imperfecta II (DGI-II) and dentin dysplasia (DD). Both disorders result in the development of hypomineralized and mechanically compromised teeth. The erupted mature molars of Dspp–/– mice have a severe hypomineralized dentin phenotype. Since dentin and enamel formations are interdependent, we decided to investigate the process of enamel onset mineralization in young Dspp–/– animals. We focused our analysis on the constantly erupting mouse incisor, to capture all of the stages of odontogenesis in one tooth, and the unerupted first molars. Using high-resolution microCT, we revealed that the onset of enamel matrix deposition occurs closer to the cervical loop and both secretion and maturation of enamel are accelerated in Dspp–/– incisors compared to the Dspp+/– control. Importantly, these differences did not translate into major phenotypic differences in mature enamel in terms of the structural organization, mineral density or hardness. The only observable difference was the reduction in thickness of the outer enamel layer, while the total enamel thickness remained unchanged. We also observed a compromised dentin-enamel junction, leading to delamination between the dentin and enamel layers. The odontoblast processes were widened and lacked branching near the DEJ. Finally, for the first time we demonstrate expression of Dspp mRNA in secretory ameloblasts. In summary, our data show that DSPP is important for normal mineralization of both dentin and enamel.
Solubility is a property of central importance for the use of proteins in research in molecular and cell biology and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are material intensive and time consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of solubility for large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the development of one such method to include in the predictions the effect of the pH on solubility. We illustrate the resulting pH-dependent predictions on a variety of antibodies and other proteins to demonstrate that these predictions achieve an accuracy comparable with that of experimental methods. We make this method publicly available at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolph, as the version 3.0 of CamSol.
Solubility is a property of central importance for the use of proteins in research and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are resource-intensive and time-consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the extension of one of such methods, CamSol, to include in the predictions the effect of the pH of the solubility. We illustrate the accuracy of the pH-dependent predictions on a variety of antibodies and other proteins.
Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs, as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) is potentially vast, experimental methods for measuring the developability properties of mAA-containing peptides are expensive and time consuming. To facilitate developability programs through computational methods, we present CamSol-PTM, a method that enables the fast and reliable sequence-based prediction of the solubility of mAA-containing peptides. From a computational screening of 50,000 mAA-containing variants of three peptides, we selected five different mAAs for a total number of 30 peptide variants for experimental validation. We demonstrate the accuracy of the predictions by comparing the calculated and experimental solubility values. Our results indicate that the computational screening of mAA-containing peptides can extend by over four orders of magnitude the ability to explore the solubility chemical space of peptides. This method is available as a web server athttps://www-cohsoftware.ch.cam.ac.uk/index.php/camsolptm.
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