[Which anticoagulant or antiplatelet treatment for cancer patients with thrombocytopenia ?] / Quel anticoagulant ou antiagrégant chez le patient oncologique présentant une thrombocytopénie ?

Cancer patients have an increased thrombotic risk of arterial and venous thrombosis. Thrombocytopenia, particularly with anticoagulation, exposes the patient to an increased risk of bleeding but does not reduce the risk of recurrent thrombosis. When platelets are < 50 × 109/l, the strategy regarding anticoagulation must be reassessed. Based on the thrombotic and bleeding risks as well as the expected duration of thrombocytopenia, management options include full-dose treatment with platelet transfusion, reduced-dose anticoagulation or withholding antithrombotic therapy. Aspirin treatment appears to be a reasonable choice for thrombocytopenic (> 30 × 109/l) patients with acute coronary syndrome. This paper will review the guidelines on anticoagulation and antiplatelet therapy in thrombocytopenic cancer patients.

Les patients avec un cancer ont un risque thrombotique artériel et veineux accru. En cas de thrombocytopénie et traitement anticoagulant (ou antiagrégant), ils sont exposés à un risque hémorragique augmenté mais conservent un risque thrombotique élevé. L'évaluation de l'anticoagulation s'impose pour des thrombocytes < 50 × 109/l. En fonction des risques thrombotique et hémorragique et de la durée de la thrombocytopénie, les options sont la poursuite de l'anticoagulation, le recours aux transfusions plaquettaires, la réduction de la dose ou son interruption. Un traitement par aspirine en cas de syndrome coronarien aigu est raisonnable pour des thrombocytes > 30 × 109/l. Cet article propose une revue des recommandations concernant les traitements anticoagulants ou antiagrégants en cas de thrombocytopénie chez les patients oncologiques.

Kinome-wide identification of phosphorylation networks in eukaryotic proteomes.

Motivation: Signaling and metabolic pathways are finely regulated by a network of protein phosphorylation events. Unraveling the nature of this intricate network, composed of kinases, target proteins and their interactions, is therefore of crucial importance. Although thousands of kinase-specific phosphorylations (KsP) have been annotated in model organisms their kinase-target network is far from being complete, with less studied organisms lagging behind. Results: In this work, we achieved an automated and accurate identification of kinase domains, inferring the residues that most likely contribute to peptide specificity. We integrated this information with the target peptides of known human KsP to predict kinase-specific interactions in other eukaryotes through a deep neural network, outperforming similar methods. We analyzed the differential conservation of kinase specificity among eukaryotes revealing the high conservation of the specificity of tyrosine kinases. With this approach we discovered 1590 novel KsP of potential clinical relevance in the human proteome. Availability and implementation: http://akid.bio.uniroma2.it. Supplementary information: Supplementary data are available at Bioinformatics online.