Targeting DHX9 Triggers Tumor-Intrinsic Interferon Response and Replication Stress in Small Cell Lung Cancer

Abstract

Activating innate immunity in cancer cells through cytoplasmic nucleic acid sensing pathways, a phenomenon known as "viral mimicry," has emerged as an effective strategy to convert immunologically "cold" tumors into "hot." Through a curated CRISPR-based screen of RNA helicases, we identified DExD/H-box helicase 9 (DHX9) as a potent repressor of double-stranded RNA (dsRNA) in small cell lung cancers (SCLC). Depletion of DHX9 induced accumulation of cytoplasmic dsRNA and triggered tumor-intrinsic innate immunity. Intriguingly, ablating DHX9 also induced aberrant accumulation of R-loops, which resulted in an increase of DNA damage-derived cytoplasmic DNA and replication stress in SCLCs. In vivo, DHX9 deletion promoted a decrease in tumor growth while inducing a more immunogenic tumor microenvironment, invigorating responsiveness to immune-checkpoint blockade. These findings suggest that DHX9 is a crucial repressor of tumor-intrinsic innate immunity and replication stress, representing a promising target for SCLC and other "cold" tumors in which genomic instability contributes to pathology.

Significance: One promising strategy to trigger an immune response within tumors and enhance immunotherapy efficacy is by inducing endogenous "virus-mimetic" nucleic acid accumulation. Here, we identify DHX9 as a viral-mimicry-inducing factor involved in the suppression of double-stranded RNAs and R-loops and propose DHX9 as a novel target to enhance antitumor immunity. See related commentary by Chiappinelli, p. 389. This article is featured in Selected Articles from This Issue, p. 384.

Figure 1.

DHX9 suppresses double-stranded RNA (dsRNA) accumulation in SCLCs. A, Schematic of the screen to identify critical regulators of dsRNA. Created with BioRender.com. B, Result of the dsRNA regulator screen. Relative mean fluorescence intensity (MFI) of dsRNA level in H446 cells depleted of RNA helicase genes was compared. C, DHX9 mRNA expression was profiled in 28 cancer types. The expression data of cancer cell lines (CCLE) were downloaded from cBioPortal, and the cell lines were subgrouped based on the information from the Depmap database (sample_info.csv, “Subtype”). In case “Subtype” information is not available, “primary_disease” was used for subgrouping. D, Analysis of DHX9 expression in indicated lung cancer (patient tumor) subtypes and normal lung. Data were downloaded from the GEO database (GSE30219). Normal lung tissue (N = 14), LUAD (N = 85), LUSC (N = 61), LCNE (N = 56), SCLC (N = 20). Bars indicate the min and max values. E, Survival curve analysis of lung tumor patients. Data were downloaded from the GEO database (GSE30219). F, Immunoblot (IB) of DHX9 protein in Scramble, sgDHX9, and sgDHX9 #2 H446 cells. G, Immunofluorescence images of dsRNA (red) staining of Scramble or sgDHX9 cells (treated w/wo RNase III). Nuclei were counterstained with DAPI. Scale bar = 10 μm. H, Schematic (left) and result (right) of J2-RIP-seq analysis. Expression levels of specific retrotransposon classes (SINE, LINE, LTR) in Scramble or sgDHX9 cells are summarized (n = 3). CPM, counts per million. I, Result of RIP-qRT-PCR analysis of the indicated retrotransposon elements (n = 3). 36B4 was used as a reference. J, RNA amounts that were pulled down with Flag antibody were compared among Flag-GFP-, Flag-MDA5-, and Flag-RIG-I-expressing cells. K, Schematic (left) and result (right) of sequencing analysis of RNA pulled down with Flag antibody. Expression levels of specific retrotransposon classes (SINE, LINE, LTR) are summarized (n = 3). CPM: counts per million. L, Relative RNA amounts that were pulled down with Flag antibody were compared between 3xFlag-DHX9-WT- and 3xFlag-DHX9-K417R-expressing cells. M, Sequencing analysis of RNA pulled down with Flag antibody. Expression levels of specific retrotransposon classes (SINE, LINE, LTR) are summarized (n = 3). CPM: counts per million. N, Heat map of Flag-RIP-seq results comparing DHX9, MDA5, and RIG-I bound RNA species (n = 3). rRNA: ribosomal RNA, srpRNA: signal recognition particle RNA, scRNA: small conditional RNA, snRNA: small nuclear RNA, tRNA: transfer RNA, RC: rolling circle, RNA: other RNA repeats, DNA: DNA repeat elements. Data represent mean ± SEM. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001 by unpaired Student t test (D, H, K, and L), log-rank test (E), one-way ANOVA (J), two-way ANOVA followed by the Tukey multiple comparisons test (I).

Figure 2.

DHX9 depletion induces IFN response. A, Gene sets significantly upregulated and downregulated are shown, based on GSEA result. Immune response–related gene sets are in red, DNA damage–related gene sets are in pink, and DNA replication/cell-cycle–related gene sets are in blue. B, GSEA with C5 (ontology) gene sets based on RNA-seq results of sgDHX9 vs. Scramble cells. C, qRT-PCR analysis of the immune-related genes comparing Scramble and sgDHX9 H196 cells (n = 3). 36B4 was used as a reference. D, Immunoblot (IB) of the indicated proteins in Scramble and sgDHX9 H196 cells. E, ELISA of human IFNβ protein in conditioned medium from Scramble and sgDHX9 H196 cells. F, Log₂ fold change (FC) of cytokine/chemokine differences of sgDHX9 H196 compared with Scramble. The cytokine/chemokine levels were quantified with Proteome Profiler Human Cytokine Array Kit. G and H, Flow cytometry analysis of HLA-A.B.C (G) or PD-L1 (H) expression on the cell surface of Scramble and sgDHX9 H196 cells. Data are representative of three independent experiments (left). Mean fluorescence intensity (MFI) was quantified by FlowJo (right; n = 3). I, Schematic (top) and result (bottom) of qRT-PCR analysis of IFNB gene in H196 cells treated with cytoplasmic dsRNA (n = 3). 36B4 was used as a reference. Data represent mean ± SEM. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001 by unpaired Student t test (C, E, G, and H), one-way ANOVA (I).

Figure 3.

DHX9 depletion causes R-loop accumulation, DNA damage, and cGAS–STING pathway activation. A, GSEA with C2 (curated) gene sets, based on RNA-seq results of sgDHX9 vs. Scramble cells. B, qRT-PCR analysis of the direct irradiation response and replication-related genes comparing Scramble and sgDHX9 H196 cells (n = 3). 36B4 was used as a reference. C, Immunofluorescence images of p-H2AX (red) staining of Scramble and sgDHX9 H196 cells. Scale bar = 50 μm. D, Flow cytometry analysis of intracellular p-H2AX levels in Scramble and sgDHX9 H196 cells. Data are representative of three independent experiments (left). Mean fluorescence intensity (MFI) was quantified by FlowJo (right; n = 3). E, Immunofluorescence images of DNA/RNA hybrid (red) staining of Scramble and sgDHX9 H196 cells (left) and quantification of fluorescence intensity (right; 150 cells were counted per group, n = 3). Scale bar = 50 μm. F, Immunoblot (IB) of the indicated proteins in Scramble and sgDHX9 H196 cells. G, DNA fiber assay of Scramble and sgDHX9 H196 cells. The percentage of stalled forks over the total number of different replication structures was measured (>150 labeled forks were counted per group, n = 3). H, Immunofluorescence images of dsDNA (green) and cGAS (red) staining of Scramble and sgDHX9 H196 cells (left) and quantification of cells with cGAS⁺-micronuclei (150 cells were counted per group, n = 3). Scale bar = 25 μm. I, ELISA of human cGAMP protein in Scramble and sgDHX9 H196 cells. J, Schematic (left) and result (right) of qRT-PCR analysis of IFNB gene in H196 cells treated with cytoplasmic DNA (n = 3). 36B4 was used as a reference. Data represent mean ± SEM. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001 by unpaired Student t test (B, D, E, G, H, and I), one-way ANOVA (J).

Figure 4.

DHX9 loss triggers dsRNA and dsDNA antiviral sensing pathways and IFN signaling in SCLC cells. A, Growth curves of the indicated SCLC cell lines (n = 3). B, Flow cytometry analysis of apoptotic (annexin V⁺) cells in Scramble and sgDHX9 H196 and H446 cells. Data are representative of three independent experiments (left). Quantification of apoptotic cells is shown (right; n = 3). C, Growth curves of the indicated normal cell lines (n = 3). D, Flow cytometry analysis of apoptotic (annexin V⁺) cells in Scramble and sgDHX9 FC1010 and RPE cells. Data are representative of three independent experiments (left). Quantification of apoptotic cells is shown (right; n = 3). E, qRT-PCR analysis of the immune-related genes comparing Scramble and sgSTING + sgMAVS H196 cells transfected with siCtrl or siDHX9 (n = 3). 36B4 was used as a reference. F, ELISA of human IFNβ protein in conditioned medium from Scramble and sgSTING + sgMAVS H196 cells, transfected with siCtrl or siDHX9 (n = 3). SM: sgSTING + sgMAVS. G, Immunoblot (IB) of the indicated proteins in Scramble and sgSTING + sgMAVS H196 cells transfected with siCtrl or siDHX9. H, Growth curves of Scramble and sgSTING + sgMAVS H196 cells, transfected with siCtrl or siDHX9 (n = 3). Data represent mean ± SEM. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001 by unpaired Student t test (A, B, C, and D), two-way ANOVA followed by Tukey multiple comparisons tests (E, F, and H).

Figure 5.

CRISPR screen identifies modulators of sensitivity and resistance to DHX9 loss. A, Schematic of the genome-wide CRISPR screening method to reveal regulators of DHX9 loss-related cell death. Created with BioRender.com. B, Top-rated enriched and depleted sgRNAs from the genome-wide CRISPR screening are summarized. C and D, Gene ontology analysis of sgRNA targeted depleted (C) and enriched (D) genes in sgDHX9 population. E, Relative cell number of Scramble and sgDHX9 H82 cells treated with DMSO or 0.5 μmol/L BAY-1143572. Luminescence of CellTiter-Glo was detected on day 5 after seeding (n = 3). F, Immunoblot (IB) of the indicated proteins in Scramble and sgDHX9 H82 cells treated with DMSO or 0.5 μmol/L BAY-1143572. G, DNA fiber assay of Scramble and sgDHX9 H82 cells treated with DMSO or 0.5 μmol/L BAY-1143572. The percentage of stalled forks over the total number of different replication structures was measured (>150 labeled forks were counted per group, n = 3). H, Schematic model of growth rescue effect by CDK9 inhibition in DHX9-depleted cells. Created with BioRender.com. Data represent mean ± SEM. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001 by two-way ANOVA followed by Tukey multiple comparisons test (E and G).

Figure 6.

DHX9 depletion decreases tumor growth, induces immune cell infiltration, and enhances response to ICB therapy. A, Schematic of in vivo tumor growth assay. RPP cells, which were transduced with DOX-inducible shCtrl or shDhx9 vector, were transplanted into C57BL/6 mice. Created with BioRender.com. B and C, Immunoblot (IB; B) and qRT-PCR analysis (C) of DHX9 expression in shCtrl and shDhx9 RPP cells treated w/wo DOX. D, Tumor growth curves of shCtrl and shDhx9 RPP tumors (n = 6). E, Flow cytometry quantification of the indicated infiltrating immune cells in shCtrl and shDhx9 RPP tumors. Each population was analyzed by FlowJo (n = 4). F, Flow cytometry quantification of infiltrating CD8⁺ T cells and CD4⁺ T cells of CD45⁺CD3⁺ cells in shCtrl and shDhx9 RPP tumors (n = 6). G, Representative IHC images of indicated infiltrating immune cells in shCtrl and shDhx9 RPP tumors (left) and quantification (n = 6; right). Scale bar = 100 μm. H, Tumor growth curves of shCtrl and shDhx9 RPP tumors treated with isotype control or anti–PD-1 antibody (n = 9). I, Survival curves for mice in H. Data represent mean ± SEM. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001 by unpaired Student t test (C, D, E, F, and G), two-way ANOVA followed by Tukey multiple comparisons test (H) and log-rank test (I).

Figure 7.

DHX9 is associated with poor clinical outcomes in cancer patient data sets. A, Representative IHC images of DHX9 expression in SCLC tumors and normal lung tissue. B, Quantification of IHC images of DHX9 in A. Normal lung tissue (N = 10), stage I (N = 9), stage II (N = 23), stage III (N = 8). C, GSEA with H (hallmark) gene sets, based on RNA-seq results of 81 SCLC patient tumors (N = 40 DHX9^low vs. N = 41 DHX9^high). Data were downloaded from cBioPortal (U Cologne, Nature 2015; ref. 51). D, Gene ontology analysis of genes upregulated in DHX9^low lung patient tumors. Data were downloaded from TCGA. E, Correlation analysis between DHX9 expression level and z-scores of the indicated gene sets in different tumor types of TCGA (patient tumors). F, Boxplots of DHX9-depleted signature z-scores in nonresponder and responder of patients treated with ICB therapy to anticipate the potential clinical relevance of targeting DHX9 in immunotherapy settings. The DHX9-depleted gene signature was prepared based on genes upregulated in sgDHX9 SCLC cells when compared with Scramble and includes the two most prominent features of DHX9-depleted cells: DDR and immune response. G, Schematic model of antitumor effects caused by DHX9 inhibition. Created with BioRender.com. Data represent mean ± SEM. ns, not significant; *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001 by one-way ANOVA (B) and unpaired Student t test (F).