TALAIA: a 3D visual dictionary for protein structures.

MOTIVATION: Graphical analysis of the molecular structure of proteins can be very complex. Full-atom representations retain most geometric information but are generally crowded, and key structural patterns can be challenging to identify. Non-full-atom representations could be more instructive on physicochemical aspects but be insufficiently detailed regarding shapes (e.g. entity beans-like models in coarse grain approaches) or simple properties of amino acids (e.g. representation of superficial electrostatic properties). In this work, we present TALAIA a visual dictionary that aims to provide another layer of structural representations.TALAIA offers a visual grammar that combines simple representations of amino acids while retaining their general geometry and physicochemical properties. It uses unique objects, with differentiated shapes and colors to represent amino acids. It makes easier to spot crucial molecular information, including patches of amino acids or key interactions between side chains. Most conventions used in TALAIA are standard in chemistry and biochemistry, so experimentalists and modelers can rapidly grasp the meaning of any TALAIA depiction. RESULTS: We propose TALAIA as a tool that renders protein structures and encodes structure and physicochemical aspects as a simple visual grammar. The approach is fast, highly informative, and intuitive, allowing the identification of possible interactions, hydrophobic patches, and other characteristic structural features at first glance. The first implementation of TALAIA can be found at https://github.com/insilichem/talaia.

RAGE/SNAIL1 signaling drives epithelial-mesenchymal plasticity in metastatic triple-negative breast cancer.

Epithelial/Mesenchymal (E/M) plasticity plays a fundamental role both in embryogenesis and during tumorigenesis. The receptor for advanced glycation end products (RAGE) is a driver of cell plasticity in fibrotic diseases; however, its role and molecular mechanism in triple-negative breast cancer (TNBC) remains unclear. Here, we demonstrate that RAGE signaling maintains the mesenchymal phenotype of aggressive TNBC cells by enforcing the expression of SNAIL1. Besides, we uncover a crosstalk mechanism between the TGF-ß and RAGE pathways that is required for the acquisition of mesenchymal traits in TNBC cells. Consistently, RAGE inhibition elicits epithelial features that block migration and invasion capacities. Next, since RAGE is a sensor of the tumor microenvironment, we modeled acute acidosis in TNBC cells and showed it promotes enhanced production of RAGE ligands and the activation of RAGE-dependent invasive properties. Furthermore, acute acidosis increases SNAIL1 levels and tumor cell invasion in a RAGE-dependent manner. Finally, we demonstrate that in vivo inhibition of RAGE reduces metastasis incidence and expands survival, consistent with molecular effects that support the relevance of RAGE signaling in E/M plasticity. These results uncover new molecular insights on the regulation of E/M phenotypes in cancer metastasis and provide rationale for pharmacological intervention of this signaling axis.

The target antigen determines the mechanism of acquired resistance to T cell-based therapies.

Despite the revolution of immunotherapy in cancer treatment, patients eventually progress due to the emergence of resistance. In this scenario, the selection of the tumor antigen can be decisive in the success of the clinical response. T cell bispecific antibodies (TCBs) are engineered molecules that include binding sites to the T cell receptor and to a tumor antigen. Using gastric CEA+/HER2+ MKN45 cells and TCBs directed against CEA or HER2, we show that the mechanism of resistance to a TCB is dependent on the tumor antigen. Acquired resistant models to a high-affinity-CEA-targeted TCB exhibit a reduction of CEA levels due to transcriptional silencing, which is reversible upon 5-AZA treatment. In contrast, a HER2-TCB resistant model maintains HER2 levels and exhibit a disruption of the interferon-gamma signaling. These results will help in the design of combinatorial strategies to increase the efficacy of cancer immunotherapies and to anticipate and overcome resistances.