RESUMO
Patients with myelodysplastic syndromes (MDS) or acute myeloid leukemia (AML) are generally older and have more comorbidities. Therefore, identifying personalized treatment options for each patient early and accurately is essential. To address this, we developed a computational biology modeling (CBM) and digital drug simulation platform that relies on somatic gene mutations and gene CNVs found in malignant cells of individual patients. Drug treatment simulations based on unique patient-specific disease networks were used to generate treatment predictions. To evaluate the accuracy of the genomics-informed computational platform, we conducted a pilot prospective clinical study (NCT02435550) enrolling confirmed MDS and AML patients. Blinded to the empirically prescribed treatment regimen for each patient, genomic data from 50 evaluable patients were analyzed by CBM to predict patient-specific treatment responses. CBM accurately predicted treatment responses in 55 of 61 (90%) simulations, with 33 of 61 true positives, 22 of 61 true negatives, 3 of 61 false positives, and 3 of 61 false negatives, resulting in a sensitivity of 94%, a specificity of 88%, and an accuracy of 90%. Laboratory validation further confirmed the accuracy of CBM-predicted activated protein networks in 17 of 19 (89%) samples from 11 patients. Somatic mutations in the TET2, IDH1/2, ASXL1, and EZH2 genes were discovered to be highly informative of MDS response to hypomethylating agents. In sum, analyses of patient cancer genomics using the CBM platform can be used to predict precision treatment responses in MDS and AML patients.
Assuntos
Biologia Computacional/métodos , Genômica/instrumentação , Leucemia Mieloide Aguda/genética , Síndromes Mielodisplásicas/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Biologia Computacional/estatística & dados numéricos , Variações do Número de Cópias de DNA/genética , Metilação de DNA/efeitos dos fármacos , Proteínas de Ligação a DNA/genética , Dioxigenases , Proteína Potenciadora do Homólogo 2 de Zeste/genética , Feminino , Humanos , Isocitrato Desidrogenase/genética , Leucemia Mieloide Aguda/terapia , Masculino , Pessoa de Meia-Idade , Mutação , Síndromes Mielodisplásicas/terapia , Ensaios Clínicos Controlados não Aleatórios como Assunto , Medicina de Precisão/instrumentação , Valor Preditivo dos Testes , Estudos Prospectivos , Proteínas Proto-Oncogênicas/genética , Proteínas Repressoras/genética , Sensibilidade e Especificidade , Fatores de Transcrição/genética , Resultado do TratamentoRESUMO
Human ß defensin DEFB103 acts as both a stimulant and an attenuator of chemokine and cytokine responses: a dichotomy that is not entirely understood. Our predicted results using an in silico simulation model of dendritic cells and our observed results in human myeloid dendritic cells, show that DEFB103 significantly (p < 0.05) enhanced 6 responses, attenuated 7 responses, and both enhanced/attenuated the CXCL1 and TNF responses to Porphyromonas gingivalis hemagglutinin B (HagB). In murine JAWSII dendritic cells, DEFB103 significantly attenuated, yet rarely enhanced, the Cxcl2, Il6, and Csf3 responses to HagB; and in C57/BL6 mice, DEFB103 significantly enhanced, yet rarely attenuated, the Cxcl1, Csf1, and Csf3 responses. Thus, DEFB103 influences pro-inflammatory activities with the concentration of DEFB103 and order of timing of DEFB103 exposure to dendritic cells, with respect to microbial antigen exposure to cells, being paramount in orchestrating the onset, magnitude, and composition of the chemokine and cytokine response.