Gene Expression Analysis of CML Patients across the Age Spectrum

Chronic myeloid leukemia (CML) accounts for 2-9% of leukemias in children and adolescents, and occurs with much greater frequency in adults. Compared to adults, children with CML tend to present with higher white blood cell counts and larger spleens, suggesting that the biology of pediatric CML is different from adult CML. We hypothesize that the differences in clinical presentation of pediatric CML are due to unique molecular characteristics that differ from adult CML. To test this hypothesis, we compared the transcriptomic signature of pediatric and adult CML CD34+ cells and healthy age-matched CD34+ cells. CD34+ cells were isolated by FACS from pediatric CML (n=9), adult CML (n=10), pediatric healthy (n=10), and adult healthy (n=10) bone marrow samples. Prepared libraries were sequenced on the Illumina HiSeq 4000 instrument. Raw sequences were trimmed and aligned to the hg38 reference genome with STAR/2.5.1b aligner. Gene level counts were determined with STAR -quantMode option using gene annotations from GENCODE (p5). Differential gene expression and pathway analysis were conducted with R/3.5.3. Counts were normalized with trimmed mean of M-values from the EdgeR/ 3.24.3 package and further transformed with VOOM from the Limma/ 3.38.3 package. A linear model using the empirical Bayes analysis pipeline also from Limma was then used to obtain p-values, adjusted p-values and log-fold changes. Four comparisons were performed: (1) pediatric CML vs pediatric healthy, (2) adult CML vs adult healthy, (3) pediatric CML vs adult CML, and (4) pediatric healthy vs adult healthy. A False Discovery Rate of ≤ .05 and absolute log2 fold-change > 1 was used to define differentially expressed genes (DEGs) in each comparison. To identify potentially unique pathways based on DEG, pathway over-representation was calculated with either goana from the limma package or clueGO. At diagnosis, pediatric patients had higher platelet counts (p=0.001) and larger spleen sizes (p=0.010) than adult patients. Median WBC counts were 273,000 and 143,000 in pediatric and adult patients respectively. A total of 1352 genes were differentially expressed in either adult or pediatric CML CD34+ cells compared to healthy CD34+ cells, 174 of which were expressed similarly in pediatric and adult CML CD34+ cells (54 up- and 120 down-regulated). There were 746 differentially expressed genes (325 up- and 421 down-regulated) in adult CML CD34+ cells compared to adult healthy CD34+ cells, and 432 differentially expressed genes (156 up- and 276 down-regulated) in pediatric CML CD34+ cells compared to pediatric healthy CD34+ cells. In direct comparison of pediatric and adult CML CD34+ cells, 446 genes (270 up and 176 down) were dysregulated in pediatric CML CD34+ cells. Pathway analysis showed that Rho signaling pathway was downregulated in pediatric CML CD34+ cells and several genes in Rho pathway were uniquely dysregulated. ARHGAP27 and VAV2 were significantly upregulated in adult CML CD34+ cells by 3.7-fold (p=0.0453) and 11-fold (p=0.0072), respectively, compared to pediatric CML CD34+ cells. In addition, several genes involved in the NADPH oxidase pathway, one of the best-characterized Rho GTPase-regulated systems, were differently expressed in CML. NCF1, CYBB, and S100A8 were significantly upregulated in adult CML CD34+ cells by 4-fold (p=0.0045), 3.26-fold (p<0.0001), and 3.09-fold (p<0.0001), respectively, compared to pediatric CML CD34+ cells. Furthermore, DLC1, which is known as a negative regulator of Rho pathway, was significantly upregulated in pediatric CML CD34+ cells by 2.47-fold (p=0.0493) compared to adult CML CD34+ cells. These results demonstrate unique molecular characteristics of pediatric CML that may contribute to the clinical differences at presentation between adult and pediatric disease. A better understanding of the molecular biology of CML across the ages will provide new insights into the pathogenesis of pediatric CML and potentially inform future treatment decisions. Disclosures Davis: Jazz Pharmaceuticals: Research Funding; Novartis Pharmaceuticals: Honoraria. Hijiya: Novartis: Consultancy; Stemline Therapeutics: Consultancy.