Figure 2.
Validation of CRISPRi screen hits as functionally affecting daratumumab efficacy. (A) Knockdown of HEXIM1 and TLE3 with 2 independent sgRNAs per gene (AMO1 myeloma cells, n = 3) followed by flow cytometry shows significant surface CD38 increase with TLE3_i2 sgRNA and trend toward increased CD38 with HEXIM1_i1 sgRNA. (B) Results from ADCC assays with AMO1 cells stably expressing the noted sgRNAs and incubated with the indicated concentration of daratumumab or isotype control antibody (1:20 myeloma:NK ratio; 20 hours; n = 2). The percent lysis by ADCC was calculated using the following formula: % lysis = (signal in presence of daratumumab – signal in presence of IgG1 control antibody) ×100/signal in presence of IgG1 control antibody. At 10 μM daratumumab, both HEXIM1 and TLE3 knockdown led to significant increase in ADCC. (C) Similar to panel A, sgRNA knockdown of NFKB1, NFKB2, and SPI1 with fold-change in CD38 by flow cytometry (RPMI-8226 cells, n = 3). (D) Similar to panel B, knockdown with the most effective sgRNA for each gene show significant decreases in NK-cell ADCC at 10 μM daratumumab in the RMPI-8266 cells (n = 3). (E) In vivo validation of SPI1 knockdown driving daratumumab resistance. NOD scid gamma mice were IV implanted with CRISPRi RPMI-8226 cells stably expressing both luciferase and noted sgRNA, then treated with 200 μg daratumumab on the noted schedule. Bioluminescence imaging measurement of tumor burden demonstrates significantly increased fold-change in tumor burden (normalized to predaratumumab intensity) with either CD38 or SPI1 knockdown compared with scramble sgRNA. (A-E) ∗P < .05; ∗∗P < .01, by 2-tailed t test. conc, concentration; I.P., intraperitoneal; MFI, mean fluorescence intensity; NSG, NOD scid gamma; Scri, nontargeting control sgRNA.

Validation of CRISPRi screen hits as functionally affecting daratumumab efficacy. (A) Knockdown of HEXIM1 and TLE3 with 2 independent sgRNAs per gene (AMO1 myeloma cells, n = 3) followed by flow cytometry shows significant surface CD38 increase with TLE3_i2 sgRNA and trend toward increased CD38 with HEXIM1_i1 sgRNA. (B) Results from ADCC assays with AMO1 cells stably expressing the noted sgRNAs and incubated with the indicated concentration of daratumumab or isotype control antibody (1:20 myeloma:NK ratio; 20 hours; n = 2). The percent lysis by ADCC was calculated using the following formula: % lysis = (signal in presence of daratumumab – signal in presence of IgG1 control antibody) ×100/signal in presence of IgG1 control antibody. At 10 μM daratumumab, both HEXIM1 and TLE3 knockdown led to significant increase in ADCC. (C) Similar to panel A, sgRNA knockdown of NFKB1, NFKB2, and SPI1 with fold-change in CD38 by flow cytometry (RPMI-8226 cells, n = 3). (D) Similar to panel B, knockdown with the most effective sgRNA for each gene show significant decreases in NK-cell ADCC at 10 μM daratumumab in the RMPI-8266 cells (n = 3). (E) In vivo validation of SPI1 knockdown driving daratumumab resistance. NOD scid gamma mice were IV implanted with CRISPRi RPMI-8226 cells stably expressing both luciferase and noted sgRNA, then treated with 200 μg daratumumab on the noted schedule. Bioluminescence imaging measurement of tumor burden demonstrates significantly increased fold-change in tumor burden (normalized to predaratumumab intensity) with either CD38 or SPI1 knockdown compared with scramble sgRNA. (A-E) ∗P < .05; ∗∗P < .01, by 2-tailed t test. conc, concentration; I.P., intraperitoneal; MFI, mean fluorescence intensity; NSG, NOD scid gamma; Scri, nontargeting control sgRNA.

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