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. 2021 Aug 30;22(17):9411.
doi: 10.3390/ijms22179411.

A Multiplex CRISPR-Screen Identifies PLA2G4A as Prognostic Marker and Druggable Target for HOXA9 and MEIS1 Dependent AML

Jacob Jalil Hassan  1 , Anna Lieske  1   2 , Nicole Dörpmund  1   2 , Denise Klatt  1 , Dirk Hoffmann  1 , Marc-Jens Kleppa  1 , Olga S Kustikova  1 , Maike Stahlhut  1 , Adrian Schwarzer  1   3 , Axel Schambach  1   4 , Tobias Maetzig  1   2
Affiliations

A Multiplex CRISPR-Screen Identifies PLA2G4A as Prognostic Marker and Druggable Target for HOXA9 and MEIS1 Dependent AML

Jacob Jalil Hassan et al. Int J Mol Sci. .

Abstract

HOXA9 and MEIS1 are frequently upregulated in acute myeloid leukemia (AML), including those with MLL-rearrangement. Because of their pivotal role in hemostasis, HOXA9 and MEIS1 appear non-druggable. We, thus, interrogated gene expression data of pre-leukemic (overexpressing Hoxa9) and leukemogenic (overexpressing Hoxa9 and Meis1; H9M) murine cell lines to identify cancer vulnerabilities. Through gene expression analysis and gene set enrichment analyses, we compiled a list of 15 candidates for functional validation. Using a novel lentiviral multiplexing approach, we selected and tested highly active sgRNAs to knockout candidate genes by CRISPR/Cas9, and subsequently identified a H9M cell growth dependency on the cytosolic phospholipase A2 (PLA2G4A). Similar results were obtained by shRNA-mediated suppression of Pla2g4a. Remarkably, pharmacologic inhibition of PLA2G4A with arachidonyl trifluoromethyl ketone (AACOCF3) accelerated the loss of H9M cells in bulk cultures. Additionally, AACOCF3 treatment of H9M cells reduced colony numbers and colony sizes in methylcellulose. Moreover, AACOCF3 was highly active in human AML with MLL rearrangement, in which PLA2G4A was significantly higher expressed than in AML patients without MLL rearrangement, and is sufficient as an independent prognostic marker. Our work, thus, identifies PLA2G4A as a prognostic marker and potential therapeutic target for H9M-dependent AML with MLL-rearrangement.

Keywords: Hoxa9; Meis1; Pla2g4a; acute myeloid leukemia; fluorescent genetic barcoding; lentiviral vector; leukemic stem cell; multiplexing; shRNA.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Gene expression analysis of Hoxa9 (H9) vs. Hoxa9/Meis1 (H9M) cells to identify leukemia-essential gene candidates. (A) Non-hierarchical clustering of genes selected for functional characterization. (B) Summary table of differentially expressed genes between H9M and H9 cells. (C) Gene set enrichment analyses. Based on the upregulated genes and those that cluster in the leading edge of the queried gene sets, a candidate gene panel was built for further evaluation.
Figure 2
Figure 2
Multiplex sgRNA screen. (A) Schematic design of the lentiviral 24xFGB multiplexing vector platform for functional interrogation of sgRNAs. The vector carries a bidirectional design, where a spleen focus-forming virus (SFFV) promoter expresses a fluorescent marker cassette in antisense orientation. The minimal CMV (mCMV) promoter drives the expression of a chimeric antigen array (CAAR) surface marker cassette. The CAAR is made up of a Thy1.1 membrane anchor, which additionally carries permutations of binding and non-binding (X) HA and cMyc epitope tags on its extracellular domain for antibody-mediated detection. The sgRNAs are embedded between the U6 promoter and the inverse polyadenylation signal (pA). (B) Schematic design of a fluorescent reporter for the assessment of sgRNA activity. A fusion construct consisting of the translated sgRNA target sites and a superfolder enhanced blue fluorescent protein (sfEBFP2) was cloned between the SFFV promoter and an internal ribosome entry site (IRES)-dependent puromycin resistance gene. (C) Schematic experimental design for the assessment of sgRNA activity. 32D cells stably expressing Cas9 were transduced with the sgRNA-sfEBFP2 lentiviral reporter construct (B), selected with puromycin and, afterwards, transduced with 18 sgRNA-expressing FGB vectors in independent wells. Transduced cells were assessed for reporter cleavage by flow cytometric analysis of individual wells (singleplex) or of mixes of 18xFGB (multiplex) samples, respectively. (D) Comparative recombination efficiency of the sgRNA reporter in singleplex as well as 18xFGB multiplex samples (mean ± SD, n = 3) 7 days post transduction. Linear regression analysis revealed a high correlation between singleplex and multiplex measurements (R2 = 0.98, Pearson’s r = 0.99). (E) Comparison of recombination rates assessed 4 and 12 days post transduction in singleplex experiments (mean ± SD, n = 3). Linear regression analysis showed a stable frequency of recombination between both time points (R2 = 0.99, Pearson’s r = 0.99). (F) Schematic vector design of the 6xFGB platform for the assessment of sgRNA activity. The U6 promoter drives the sgRNA expression. Likewise, the SFFV promoter drives the expression of a fluorescent marker cassette, and each of the color codes (CC) carries a unique DNA barcode (BC). (G) Comparison of gene editing efficiencies in 32D cells measured by flow cytometry versus H9M-Cas9 cells based on TIDE analysis (mean ± SD, TIDE n = 1, flow cytometry n = 3). ∆U3, self-inactivating long terminal repeat; PPT, polypurine tract; hmAG3, human codon-optimized Azami Green fluorescent protein variant; YFP, yellow fluorescent protein; mChEY, monomeric mCherry fluorescent protein variant; PRE*, posttranscriptional regulatory element; BC, DNA barcode.
Figure 3
Figure 3
sgRNA screen in H9M cells reveals a growth requirement for PLA2G4A. (A) Experimental timeline. After purification of gene marked sgRNA-expressing cells, cell mixes of six different samples (5 sgRNAs + 1 control) were created and subsequently analyzed by flow cytometry for population sizes. A representative gating strategy for the assessment of population sizes is shown on the right. (B) Heatmap representing relative population sizes of sgRNA-transduced H9M cells in 6xFGB mixes over time (n = 3). After 7 weeks, the Pla2g4a knockout population showed a decreased median population size of 63.68% compared to the initial measurement, while the control remained stable at 91.23%. (C) RT-qPCR analysis of Pla2g4a expression of independently transduced Hoxa9 (H9) and Hoxa9/Meis1 (H9M) cell lines (scatter dot plot, mean ± SD). Pla2g4a was significantly upregulated in H9M cells (Student’s t-test, p = 0.0011, mean = 2.61; ** = p < 0.005).
Figure 4
Figure 4
Pla2g4a knockdown impairs H9M cell growth. (A) Schematic representation of (top) a lentiviral vector co-expressing Pla2g4 and GFP via an internal ribosome entry site (IRES) and (bottom) an shRNA expression vector co-expressing dTomato and a mir-N embedded hairpin against Pla2g4a under control of the SFFV promoter. (B) Representative flow cytometric analysis plots of two shRNAs against Pla2g4a, which downregulate the signal of a PLA2G4A-GFP reporter. Transduction with an empty shRNA vector (stuffer) does not cause loss of Pla2g4a reporter expression. (C) Calculation of the knockdown efficiency of two shRNAs as well as of the “stuffer” control vector based on data from the reporter assay from (B). (D) Validation of Pla2g4a knockdown efficiency by RT-qPCR in three different H9M lines (Rep1, Rep2, and Rep3), in comparison to a non-targeting (stuffer) miR-N backbone. (E) Depletion of shRNA-α-Pla2g4a transduced H9M cells over time. Data shown from one exemplary experiment with three data points per vector. Data were normalized to the gene marking rate at the first measurement (d0) seven days after the initial transduction.
Figure 5
Figure 5
Pharmacologic inhibition of PLA2G4A specifically impairs H9M cell growth. (A) Determination of the IC50 of the PLA2G4A inhibitor AACOCF3 (44.7 µM) and the SYK inhibitor R406 (2.2 µM) based upon viability of H9M cells determined with the resazurin-based alamarBlue assay. Viability was normalized to H9M cells treated with DMSO or EtOH as a vehicle control (dose response curve, n = 7). (B) alamarBlue viability assay of H9M and H9 cells after 24 h exposure with AACOCF3 (44.7 µM) and R406 (2.2 µM), respectively. Viability was normalized to H9M/ H9 cells treated with a vehicle control (DMSO/ EtOH). Both inhibitors showed a significant loss of viability of H9M cells compared to H9 cells (Scatter dot plot, Student’s t-test, mean ± SD: AACOCF: mean relative viability H9 = 100.8% (n = 12), H9M = 42.66% (n =24), p = <0.0001; R406: H9 = 79.44% (n = 3), H9M = 56.74% (n = 6), p = 0.0003). (C) Determination of the colony-forming potential (CFP) IC50 of AACOCF3 (19.6 µM) and R406 (1.1 µM) in H9M cells using the methylcellulose colony-forming assay (CFA). Colony-forming potential was normalized to H9M cells treated with DMSO or EtOH as a vehicle control (dose response curve). (D) 500 H9M cells were seeded in a CFA with R406 (1.1 µM), AACOCF3 (19.6 µM) or a vehicle control (DMSO/ EtOH). Experiments were performed in duplicates of three independently generated H9M lines. Both inhibitors caused a significant reduction in colonies (mean ± SD, n = 3, Student’s t-test: AACOCF3: p = 0.0045, R406: p= 0.0071) and absolute cell numbers (mean ± SD, n = 3, Student’s t-test, AACOCF3: p < 0.0001, R406: p = 0.0001) compared to the vehicle control. ** = p < 0.005; *** = p < 0.0005; **** = p < 0.0001.
Figure 6
Figure 6
Characterization of PLA2G4A in human AML. (A) Left: expression levels of HOXA9, MEIS1, and PLA2G4A within MOLM13, THP1, Kasumi-1, OCI-AML3, MV-4-11, NOMO-1, and K562 cells based on RNA sequencing data from the Cancer Cell Line Repository. Right: alamarBlue viability assay of MOLM13, THP1, Kasumi-1, OCI-AML3, MV-4-11, NOMO-1, and K562 cells after 24 h exposure to 45 µM AACOCF3 normalized to vehicle control-treated cells. The AML MLLr cell lines (MOLM13, MLL-AF9; THP1, MLL-AF9; MV4-11, MLL-AF4; and NOMO-1, MLL-AF9) showed a significant reduction in viability compared to the control K562 blast phase chronic myeloid leukemia cell line. Unrelated AML lines OCI-AML3 (wt. TP53 and NPM1c) and Kasumi-1 ((RUNX1/AML1-RUNX1T1/ETO) were not negatively impacted by the treatment. ****, p < 0.0001 with one-way ANOVA, Dunnett’s multiple comparison test. (B) Co-expression of PLA2G4A with HOXA9 (left) and MEIS1 (right), respectively, in AML samples from the TCGA-LAML data set. PLA2G4A expression significantly correlates with HOXA9 (p < 0.0001, Pearson‘s r = 0.55) and MEIS1 (p < 0.0001, Pearson‘s r = 0.64) (linear regression analysis). (C) Kaplan–Meier survival curve of overall survival (OS) and disease-free survival (DFS) in AML patients with above median PLA2G4A expression (n = 61) compared to patients with below median PLA2G4A expression (n = 60). The high PLA2G4A expression group had significantly lower OS (Mantel–Cox test: p < 0.0001, median OS = 12.2 months vs. 46.7 months) and DFS (Mantel–Cox test: p < 0.0001, median DFS = 9.6 vs. 32.3 months) compared to the control group. (D) PLA2G4A gene expression in patient samples with different AML subtypes and HSC of healthy individuals (scatter dot plot, mean ± SD: mean log2 PLA2G4A expression: AML t(15;17) = 3.0, AML inv[1 6]/t(16;16) = 4.2, AML t(8;21) = 4.2, AML complex = 5.0, AML t(11q23)/MLL = 5.3, HSC = 6.2). (E) Box plot of PLA2G4A expression in MLLr or non MLLr AML patient samples. The upper, center, and lower limit of each box denotes the upper quartile, median, and lower quartile, respectively. Whiskers representing min and max expression samples. PLA2G4A is significantly upregulated in AML patient samples with MLLr (n = 30) compared to those without (n = 142) (Welch‘s t-test: p = 0.0015, mean log2 PLA2G4A expression: MLL-AML = 16.34, non-MLL-AML = 15.67. TPM, transcripts per kilobase million. ** = p < 0.005; **** = p < 0.0001.
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