| Literature DB >> 27063598 |
V Madan1, P Shyamsunder1, L Han1,2, A Mayakonda1, Y Nagata3, J Sundaresan1, D Kanojia1, K Yoshida3, S Ganesan4, N Hattori1, N Fulton5, K-T Tan1, T Alpermann6, M-C Kuo7, S Rostami8, J Matthews9, M Sanada3, L-Z Liu1, Y Shiraishi10, S Miyano10, E Chendamarai4, H-A Hou11, G Malnassy5, T Ma12, M Garg1, L-W Ding1, Q-Y Sun1, W Chien1, T Ikezoe13, M Lill14, A Biondi15, R A Larson16, B L Powell17, M Lübbert12, W J Chng1,2,18, H-F Tien11, M Heuser19, A Ganser19, M Koren-Michowitz20,21, S M Kornblau9, H M Kantarjian9, D Nowak22, W-K Hofmann22, H Yang1, W Stock5, A Ghavamzadeh8, K Alimoghaddam8, T Haferlach6, S Ogawa3, L-Y Shih7, V Mathews4, H P Koeffler1,14,18.
Abstract
Acute promyelocytic leukemia (APL) is a subtype of myeloid leukemia characterized by differentiation block at the promyelocyte stage. Besides the presence of chromosomal rearrangement t(15;17), leading to the formation of PML-RARA (promyelocytic leukemia-retinoic acid receptor alpha) fusion, other genetic alterations have also been implicated in APL. Here, we performed comprehensive mutational analysis of primary and relapse APL to identify somatic alterations, which cooperate with PML-RARA in the pathogenesis of APL. We explored the mutational landscape using whole-exome (n=12) and subsequent targeted sequencing of 398 genes in 153 primary and 69 relapse APL. Both primary and relapse APL harbored an average of eight non-silent somatic mutations per exome. We observed recurrent alterations of FLT3, WT1, NRAS and KRAS in the newly diagnosed APL, whereas mutations in other genes commonly mutated in myeloid leukemia were rarely detected. The molecular signature of APL relapse was characterized by emergence of frequent mutations in PML and RARA genes. Our sequencing data also demonstrates incidence of loss-of-function mutations in previously unidentified genes, ARID1B and ARID1A, both of which encode for key components of the SWI/SNF complex. We show that knockdown of ARID1B in APL cell line, NB4, results in large-scale activation of gene expression and reduced in vitro differentiation potential.Entities:
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Year: 2016 PMID: 27063598 PMCID: PMC4972641 DOI: 10.1038/leu.2016.69
Source DB: PubMed Journal: Leukemia ISSN: 0887-6924 Impact factor: 11.528
Dx and Rel APL samples sequenced in this study
| Dx | 165 (147) | ||
| Rel | 77 (40) | ||
| Total | 242 (187) | ||
| Discovery cohort (whole exome) | 8 (8) | 4 (4) | 0 |
| Frequency cohort (targeted exome) | 22 (14) | 131 (121) | 47 (18) |
| Total | 30 (22) | 135 (125) | 47 (18) |
| ATRA | 33 | ||
| ATO | 41 | ||
| Information unavailable | 3 | ||
| Median | 37 years | ||
| Range | 4-69 years | ||
| Male | 56.7% | ||
| Female | 43.3% | ||
Abbreviations: APL, acute promyelocytic leukemia; Dx, newly diagnosed; Rel, relapse.
Numbers within parentheses represent the number of samples with matched germline control.
Figure 1Characteristics of somatic mutations detected at primary and relapse APL. (a) Comparison of mutational load between primary and relapse APL. Boxplots depict median and range for numbers of nonsynonymous and synonymous variants identified per exome. Difference between average number of variants between two groups was estimated using two-tailed Student's t-test. (b) Clustering analysis using variant allele frequencies (VAFs) of all somatic variants (VAF ⩾0.08) observed at primary and relapse APL. DS2 and DS6 are shown as two representative cases, which harbor common or exclusive somatic mutations, respectively, at initial diagnosis and relapse.
Figure 2Recurrently mutated genes in primary APL. Mutational topography of newly diagnosed APL is depicted. Top 20 mutated genes validated by Sanger sequencing are shown and are color-coded for various types of mutation. Genes are displayed according to decreasing mutational frequency from top to bottom. Samples are displayed as columns and arranged to emphasize mutual exclusivity. Samples in which either no driver mutation was detected in our analysis pipeline or do not harbor mutations of top 20 genes are not included in the matrix. Bars on the right side depict absolute number of mutations in each gene.
Figure 3Distinct mutational profile of newly diagnosed APL. (a) Bars represent mutational rates of genes mutated at significantly different frequencies (Fisher's exact test; P<0.05) between APL and other AML subtypes at initial diagnosis. Frequency of validated non-silent mutations in 165 newly diagnosed APL samples analyzed in this study was compared with 176 non-APL AML samples from the TCGA database. TTN, which is most frequently mutated in public exomes,[42] and MT-CYB, which was not included in our targeted sequencing, were excluded from this representation. (b and c) Schematic representation of protein domains of ARID1A (b) and ARID1B (c) was drawn with DOG 2.0 software (http://dog.biocuckoo.org) using domain information from NCBI Protein database (http://www.ncbi.nlm.nih.gov/protein). Location and type of all somatic mutations verified at primary and relapse APL are shown. Circles depicting individual mutations are color-coded for different types of mutations.
Figure 4Spectrum of somatic mutations at APL relapse. (a) Matrix displays top 15 genes recurrently mutated at relapsed APL. Each column represents a relapse sample. Genes are arranged according to decreasing mutational frequencies from top to bottom. Right panel illustrates the number of mutations for all genes. Only those relapse samples that harbor mutations of top 15 genes are included in the matrix. (b–d) Protein domains for RARA (b), PML (c) and RUNX1 (d) are drawn using the DOG 2.0 software (http://dog.biocuckoo.org), and type and location of validated mutations are illustrated. Information about protein domains was obtained from Human Protein Reference Database (http://www.hprd.org). All except one missense mutation (E699K) of PML were found in relapse samples. One frameshift deletion in PML transcript NM_033249 (NP_15025; S482fs) is not shown. All mutations of RARA were detected in relapse. Only one of the six mutations of RARA occurred in newly diagnosed samples.
Figure 5Silencing of ARID1B impairs ATRA-induced neutrophil differentiation of NB4 cells. (a and b) Generation of NB4 cells with stable knockdown of ARID1B. Cells transduced with ARID1B shRNA (sh2 or sh3) display significant suppression of ARID1B transcript (two primer pairs) (a) and protein levels (b) compared with the control transduced (con) cells. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) transcript levels were used to normalize for RNA in quantitative real time-PCR (qRT-PCR) analysis in (a) and bars represent mean±s.d. (c) Clonogenic ability of ARID1B knockdown NB4 cells compared with control cells. Cells were plated in methylcellulose media, and colonies were enumerated after 9 days. Bars represent mean±s.e.m. (d) ATRA-induced differentiation of control and ARID1B knockdown NB4 cells was determined by surface expression of CD11b. Cells were treated with 0.1, 1 or 10 μm ATRA, and the proportion of CD11b-expressing cells was determined by flow cytometry at indicated times. The difference in the percentage of CD11b+ cells obtained in ATRA- vs DMSO-treated cells at each time point is depicted. Data represent mean±s.e.m. of four to five experiments (*P<0.05; Student's t-test).
Figure 6Gene expression changes in ARID1B knockdown NB4 cells. (a) Volcano plot depicts differentially expressed genes between ARID1B knockdown (sh2 and sh3) and control transduced NB4 cells. Horizontal line denotes false discovery rate (FDR)=0.05. Blue dots represent genes involved in ‘immune system process' GO:0002376. (b) Functional enrichment analysis (gene ontology) of genes either upregulated or downregulated in ARID1B knockdown NB4 cells (FDR<0.05). (c) qRT-PCR analyses of selected genes identified as differentially expressed in RNA sequencing. GAPDH was used as an endogenous control to normalize for RNA quantity. Bars represent mean±s.e.m.