| Literature DB >> 35671062 |
Daniel C Ferguson1,2, J Robert McCorkle1,2, Kelly R Barnett1,2, Erik J Bonten1,2, Brennan P Bergeron1,2,3, Kashi Raj Bhattarai1,2, Wenjian Yang1,2, Colton Smith1,2, Baranda S Hansen4, Richa Bajpai4, Qian Dong1,2, Robert J Autry1,2, Yoshihiro Gocho1,2, Jonathan D Diedrich1,2, Kristine R Crews1,2, Shondra M Pruett-Miller4, Kathryn G Roberts1,5, Wendy Stock6, Charles G Mullighan1,5,7, Hiroto Inaba1,7, Sima Jeha1,7, Ching-Hon Pui1,5,7, Jun J Yang1,2,7, Mary V Relling1,2, William E Evans1,2, Daniel Savic1,2.
Abstract
Understanding the genomic and epigenetic mechanisms of drug resistance in pediatric acute lymphoblastic leukemia (ALL) is critical for further improvements in treatment outcomes. The role of transcriptomic response in conferring resistance to l-asparaginase (LASP) is poorly understood beyond asparagine synthetase (ASNS). We defined reproducible LASP response genes in LASP-resistant and LASP-sensitive ALL cell lines as well as primary leukemia samples from newly diagnosed patients. Defining target genes of the amino acid stress response-related transcription factor activating transcription factor 4 (ATF4) in ALL cell lines using chromatin immunoprecipitation sequencing (ChIP-seq) revealed 45% of genes that changed expression after LASP treatment were direct targets of the ATF4 transcription factor, and 34% of these genes harbored LASP-responsive ATF4 promoter binding events. SLC7A11 was found to be a response gene in cell lines and patient samples as well as a direct target of ATF4. SLC7A11 was also one of only 2.4% of LASP response genes with basal level gene expression that also correlated with LASP ex vivo resistance in primary leukemia cells. Experiments using chemical inhibition of SLC7A11 with sulfasalazine, gene overexpression, and partial gene knockout recapitulated LASP resistance or sensitivity in ALL cell lines. These findings show the importance of assessing changes in gene expression following treatment with an antileukemic agent for its association with drug resistance and highlight that many response genes may not differ in their basal expression in drug-resistant leukemia cells.Entities:
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Year: 2022 PMID: 35671062 PMCID: PMC9198938 DOI: 10.1182/bloodadvances.2022006965
Source DB: PubMed Journal: Blood Adv ISSN: 2473-9529
Figure 1.Distribution of de novo LASP LC50 values in primary ALL cells and descriptive genomic features. (A) Frequency distribution of de novo LASP LC50 values in patients (n = 212). (B) Subtype specific differences in LASP LC50 (n = 212). The mean LC50 for each subtype is depicted as a red bar. Green shading represents the concentration range associated with drug sensitivity, while red shading represents the concertation range associated with drug resistance. (C) Frequency of MRD+ patients at day 15 or 42 of therapy. Green (in A) or blue (in B) bars represent patients found to be LASP sensitive, while red shading represents patients found to be intermediate or resistant to LASP. Comparisons between positivity rate and LASP sensitivity class for each time point were performed with Fisher’s Exact test (P < .05).
Figure 2.Correlations between basal gene expression or DNA methylation and LASP sensitivity. (A) Gene expression heatmap of genes (n = 535) discriminate LASP LC50. Patients are denoted at the top of the heatmap as sensitive (green), intermediate (gray), or resistant (red). Expression is denoted as log10(FPKM+1). (B) Basal gene expression [as log10(FPKM+1)] correlation with ex vivo LASP sensitivity by group (S, sensitive; I, intermediate; R, resistant). Box and whisker plots depict the interquartile ranges (IQRs) and tenth to ninetieth percentiles. The linear regression P value for discovery and validations cohorts is shown for each gene (D, FDR <0.05; V, P < .05). (C) DNA methylation heatmap of CpG sites (n = 246) associated with LASP LC50. For each heatmap, the significance of clustering patients by LASP sensitivity was determined by Fisher’s Exact test (P < .05). (D) Basal DNA methylation (β value) correlated with ex vivo LASP sensitivity by group (S, sensitive; I, intermediate; R, resistant). The Kruskal-Wallis test P value for discovery and validation cohorts is shown for each probe (D, FDR <0.1; V, P < .1). Box and whisker plots depict the IQRs and tenth to ninetieth percentiles. (E) Correlation between basal gene expression and DNA methylation. DNA methylation is depicted as hypo-, hemi-, and hyper-methylation (Kruskal-Wallis test; P < .05; n = 136). Box and whisker plots depict the IQRs and tenth to ninetieth percentiles. (F) DNA methylation pattern of the ASNS promoter across 7 probes by drug sensitivity group. Each CpG displayed a significant difference between S, I, and R groups (Kruskal-Wallis test; P < .05).
Figure 3.Genes responding to LASP treatment in ALL cell lines. (A-B) Venn diagrams of overlap between LASP response genes between sensitive (S, green) and resistant (R, red) ALL cell lines (n = 3 independent experiments per cell line and timepoint). Reproducibly upregulated LASP response genes are provided in (A), and reproducibly downregulated LASP response genes are provided in (B). Overlapping (common) LASP response genes between sensitive and resistant cells are listed. (C) Average gene expression (in transcripts per million) across sensitive (S, green) and resistant (R, red) ALL cell lines before (0h) and after 4 hours (4h) of LASP treatment (1 IU/mL) for reproducibly-induced response genes. Data for ASNS (resistant only), SLC7A11 (common), DDIT3 (common), and ATF3 (sensitive) (n = 4 resistant cells and n = 3 sensitive cells; mean ± SEM). (D) Fold-enrichment in significantly biological pathways from gene ontology analysis of reproducible inducible response genes from resistant and shared (resistant + sensitive) cell lines (FDR <0.05). (E) Significantly enriched TF motifs observed in LASP response genes reproducibly upregulated in resistant-only and shared (resistant + sensitive) cell lines as identified by HOMER (P < .05).
Figure 4.ATF4 induction and target genes following LASP treatment in ALL cell lines. (A) Relative expression of ATF4 protein in ALL cell lines following LASP treatment (n = 3 independent experiments; mean ± SEM). (B) Number of ChIP-seq ATF4 sites (FDR <0.05; n = 2 independent experiments per cell line and timepoint) in Nalm6 (red) and SUPB15 (blue) cells at basal conditions (Ctrl) or after 2 hours of LASP treatment (1 IU/mL; LASP). Dark red and dark blue denote strong peaks (>fivefold ChIP enrichment), whereas light red and light blue denote weaker peaks (
Figure 5.Modulation of SLC7A11 alters ALL cell line sensitivity to LASP. (A-B) Rescue of LASP-mediated cell death by sulfasalazine in Nalm6 (A) and SUPB15 (B) cells. Each cell line was treated with sulfasalazine (SAS; 500 µM or 1 mM), LASP (0.001 IU/mL, 1 IU/mL, and 10 IU/mL), or both drugs for 12 hours before assessment of cell viability (t test; P ≤ .05; n = 4 independent experiments; mean ± SEM). (C) Relative SLC7A11 overexpression in 697 cells (n = 3 independent experiments). (D) Dose–response (left) after 24 hours of LASP treatment following transient overexpression of SLC7A11 in 697 cells and changes in area under the curve (AUC) (right, P < .05; n = 3 independent experiments; mean ± SEM). (E) Change in cell viability between control and SLC7A11 overexpressing 697 cells as fold change relative to control cells is shown after 1 IU/mL (left) and 10 IU/mL (right) of LASP treatment for 24 hours (P < .01; n = 12 independent experiments; mean ± SEM). (F) Depiction of the edited region of SLC7A11 gene sequence in exon 2 in Nalm6 cells. WT = SLC7A11 wildtype, INS = SLC7A11 insertion. (G) Dose–response (left) after 72 hours of LASP treatment and changes in AUC (right) in Nalm6 SLC7A11-disrupted cells (SLC7A11wt/ins) compared with wildtype Nalm6 cells (SLC7A11wt/wt; P < .05; n = 3 independent experiments; mean ± SEM). (H) Change in cell viability between SLC7A11wt/wt and SLC7A11wt/ins Nalm6 cells as fold change relative to wild-type cells is shown after 0.0001 IU/mL (left) and 0.0006 IU/mL (right) of LASP treatment for 72 hours (P < .01; n = 18 independent experiments; mean ± SEM).