Structural Biology of STAT3 and Its Implications for Anticancer Therapies Development.

Transcription factors are proteins able to bind DNA and induce the transcription of specific genes. Consequently, they play a pivotal role in multiple cellular pathways and are frequently over-expressed or dysregulated in cancer. Here, we will focus on a specific "signal transducer and activator of transcription" (STAT3) factor that is involved in several pathologies, including cancer. For long time, the mechanism by which STAT3 exerts its cellular functions has been summarized by a three steps process: (1) Protein phosphorylation by specific kinases, (2) dimerization promoted by phosphorylation, (3) activation of gene expression by the phosphorylated dimer. Consequently, most of the inhibitors reported in literature aimed at blocking phosphorylation and dimerization. However, recent observations reopened the debate and the entire functional mechanism has been revisited stimulating the scientific community to pursue new inhibition strategies. In particular, the dimerization of the unphosphorylated species has been experimentally demonstrated and specific roles proposed also for these dimers. Despite difficulties in the expression and purification of the full length STAT3, structural biology investigations allowed the determination of atomistic structures of STAT3 dimers and several protein domains. Starting from this information, computational methods have been used both to improve the understanding of the STAT3 functional mechanism and to design new inhibitors to be used as anticancer drugs. In this review, we will focus on the contribution of structural biology to understand the roles of STAT3, to design new inhibitors and to suggest new strategies of pharmacological intervention.

Machine learning analyses of antibody somatic mutations predict immunoglobulin light chain toxicity.

In systemic light chain amyloidosis (AL), pathogenic monoclonal immunoglobulin light chains (LC) form toxic aggregates and amyloid fibrils in target organs. Prompt diagnosis is crucial to avoid permanent organ damage, but delayed diagnosis is common because symptoms usually appear only after strong organ involvement. Here we present LICTOR, a machine learning approach predicting LC toxicity in AL, based on the distribution of somatic mutations acquired during clonal selection. LICTOR achieves a specificity and a sensitivity of 0.82 and 0.76, respectively, with an area under the receiver operating characteristic curve (AUC) of 0.87. Tested on an independent set of 12 LCs sequences with known clinical phenotypes, LICTOR achieves a prediction accuracy of 83%. Furthermore, we are able to abolish the toxic phenotype of an LC by in silico reverting two germline-specific somatic mutations identified by LICTOR, and by experimentally assessing the loss of in vivo toxicity in a Caenorhabditis elegans model. Therefore, LICTOR represents a promising strategy for AL diagnosis and reducing high mortality rates in AL.

Systematic Development of Peptide Inhibitors Targeting the CXCL12/HMGB1 Interaction.

During inflammatory reactions, the production and release of chemotactic factors guide the recruitment of selective leukocyte subpopulations. The alarmin HMGB1 and the chemokine CXCL12, both released in the microenvironment, can form a heterocomplex, which exclusively acts on the chemokine receptor CXCR4, enhancing cell migration, and in some pathological conditions such as rheumatoid arthritis exacerbates the immune response. An excessive cell influx at the inflammatory site can be diminished by disrupting the heterocomplex. Here, we report the computationally driven identification of the first peptide (HBP08) binding HMGB1 and selectively inhibiting the activity of the CXCL12/HMGB1 heterocomplex. Furthermore, HBP08 binds HMGB1 with the highest affinity reported so far (Kd of 0.8 ± 0.4 µM). The identification of this peptide represents an important step toward the development of innovative pharmacological tools for the treatment of severe chronic inflammatory conditions characterized by an uncontrolled immune response.

Management of transthyretin amyloidosis.

Transthyretin amyloidosis (ATTR amyloidosis) is a disease caused by deposition of transthyretin fibrils in organs and tissues, which causes their dysfunction. The clinical heterogeneity of ATTR amyloidosis and the variable presentation of symptoms at early disease stages, historically meant treatment delays. Diagnostic tools and therapy options of ATTR amyloidosis have markedly improved in recent years. The first Swiss Amyloidosis Network (SAN) meeting (Zurich, Switzerland, January 2020) aimed to define a consensus statement regarding the diagnostic work-up and treatment for systemic amyloidosis, tailored to the Swiss healthcare system. A consortium of 45 clinicians and researchers from all Swiss regions and universities was selected by the SAN committee to represent all sub-specialty groups involved in care of patients with amyloidosis. A steering committee conducted the literature search and analysis, wrote the critical synthesis and elaborated a list of statements that were evaluated by all the participants. These recommendations will improve outcomes and quality of life for patients with ATTR amyloidosis. A global review of these guidelines is planned every 3 years with a formal meeting of all the involved experts.

Expert recommendation from the Swiss Amyloidosis Network (SAN) for systemic AL-amyloidosis.

Systemic amyloidosis is a heterogeneous group of diseases associated with protein misfolding into insoluble beta-sheet rich structures that deposit extracellularly in different organs, eventually compromising their function. There are more than 30 different proteins, known to be amyloidogenic with “light chain” (AL)-amyloidosis being the most common type, followed by transthyretin (ATTR)-, and amyloid protein A (AA)-amyloidosis. Systemic amyloidosis is a rare disease with an incidence of around 10 patients in 1 million inhabitants. Recently several new therapeutic options have been developed for subgroups of amyloidosis patients, and the introduction of novel therapies for plasma cell myeloma has led to an increase in the therapeutic armamentarium for plasma cell disorders, including AL amyloidosis. Among them, proteasome inhibitors, immunomodulatory agents (-imids), and monoclonal antibodies have been successfully introduced into clinical practice. Still, high-quality data from randomised controlled trials regarding the benefit of these cost-intensive drugs in AL amyloidosis are widely lacking, and due to the rarity of the disease many physicians will not gain routine experience in the management of these frail patients. The diagnosis of AL amyloidosis relies on a close collaboration between clinicians, pathologists, imaging experts, and sometimes geneticists. Diagnosis and treatment options in this complex disorder should be discussed in dedicated multidisciplinary boards. In January 2020, the first meeting of the Swiss Amyloidosis Network took place in Zurich, Switzerland. One aim of this meeting was to establish a consensus guideline regarding the diagnostic work-up and the treatment recommendations for systemic amyloidosis tailored to the Swiss health care system. Forty-five participants from different fields in medicine discussed many aspects of amyloidosis. These are the Swiss Amyloidosis Network recommendations which focus on diagnostic work-up and treatment of AL-amyloidosis.

Oxidation State Dependent Conformational Changes of HMGB1 Regulate the Formation of the CXCL12/HMGB1 Heterocomplex.

High-mobility Group Box 1 (HMGB1) is an abundant protein present in all mammalian cells and involved in several processes. During inflammation or tissue damage, HMGB1 is released in the extracellular space and, depending on its redox state, can form a heterocomplex with CXCL12. The heterocomplex acts exclusively via the chemokine receptor CXCR4 enhancing leukocyte recruitment. Here, we used multi-microsecond molecular dynamics (MD) simulations to elucidate the effect of the disulfide bond on the structure and dynamics of HMGB1. The results of the MD simulations show that the presence or lack of the disulfide bond between Cys23 and Cys45 modulates the conformational space explored by HMGB1, making the reduced protein more suitable to form a complex with CXCL12.