The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data

BACKGROUND: Acute T-cell lymphoblastic leukaemia (T-ALL) is an aggressive disorder derived from immature thymocytes. The variability observed in clinical responses on this type of tumours to treatments, the high toxicity of current protocols and the poor prognosis of patients with relapse or refractory make it urgent to find less toxic and more effective therapies in the context of a personalized medicine of precision. METHODS: Whole exome sequencing and RNAseq were performed on DNA and RNA respectively, extracted of a bone marrow sample from a patient diagnosed with tumour primary T-ALL and double negative thymocytes from thymus control samples. We used PanDrugs, a computational resource to propose pharmacological therapies based on our experimental results, including lists of variants and genes. We extend the possible therapeutic options for the patient by taking into account multiple genomic events potentially sensitive to a treatment, the context of the pathway and the pharmacological evidence already known by large-scale experiments. RESULTS: As a proof-of-principle we used next-generation-sequencing technologies (Whole Exome Sequencing and RNA-Sequencing) in a case of diagnosed Pro-T acute lymphoblastic leukaemia. We identified 689 disease-causing mutations involving 308 genes, as well as multiple fusion transcript variants, alternative splicing, and 6652 genes with at least one principal isoform significantly deregulated. Only 12 genes, with 27 pathogenic gene variants, were among the most frequently mutated ones in this type of lymphoproliferative disorder. Among them, 5 variants detected in CTCF, FBXW7, JAK1, NOTCH1 and WT1 genes have not yet been reported in T-ALL pathogenesis. CONCLUSIONS: Personalized genomic medicine is a therapeutic approach involving the use of an individual's information data to tailor drug therapy. Implementing bioinformatics platform PanDrugs enables us to propose a prioritized list of anticancer drugs as the best theoretical therapeutic candidates to treat this patient has been the goal of this article. Of note, most of the proposed drugs are not being yet considered in the clinical practice of this type of cancer opening up the approach of new treatment possibilities.This research was made possible through funding by the Spanish Ministry of Science, Innovation and Universities (RTI2018–093330-B_100); Spanish Ministry of Economy and Competitiveness (SAF2015–70561-R); MINECO/FEDER, EU; BES-2013-065740); Ramón Areces Foundation (CIVP19S7917); the Autonomous Community of Madrid, Spain (B2017/BMD-3778; LINFOMAS-CM); the Spanish Association Against Cancer (AECC, 2018; PROYE18054PIRI); and the Institute of Health Carlos III, ISCIII (ACCI-CIBERER-17). Institutional grants from the Ramón Areces Foundation and the Santander Bank to the Severo Ochoa Molecular Biology Center (CBMSO) are also acknowledged. These projects only provide financial support for our experiments.S

Among classic myeloproliferative neoplasms, essential thrombocythemia is associated with the greatest risk of venous thromboembolism during COVID-19

In a multicenter European retrospective study including 162 patients with COVID-19 occurring in essential thrombocythemia (ET, n = 48), polycythemia vera (PV, n = 42), myelofibrosis (MF, n = 56), and prefibrotic myelofibrosis (pre-PMF, n = 16), 15 major thromboses (3 arterial and 12 venous) were registered in 14 patients, of whom all, but one, were receiving LMW-heparin prophylaxis. After adjustment for the competing risk of death, the cumulative incidence of arterial and venous thromboembolic events (VTE) reached 8.5% after 60 days follow-up. Of note, 8 of 12 VTE were seen in ET. Interestingly, at COVID-19 diagnosis, MPN patients had significantly lower platelet count (p < 0.0001) than in the pre-COVID last follow-up.This decline was remarkably higher in ET (−23.3%, p < 0.0001) than in PV (−16.4%, p = 0.1730) and was associated with higher mortality rate (p = 0.0010) for pneumonia. The effects of possible predictors of thrombosis, selected from those clinically relevant and statistically significant in univariate analysis, were examined in a multivariate model. Independent risk factors were transfer to ICU (SHR = 3.73, p = 0.029), neutrophil/lymphocyte ratio (SHR = 1.1, p = 0.001) and ET phenotype (SHR = 4.37, p = 0.006). The enhanced susceptibility to ET-associated VTE and the associated higher mortality for pneumonia may recognize a common biological plausibility and deserve to be delved to tailor new antithrombotic regimens including antiplatelet drugs