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. Author manuscript; available in PMC: 2024 May 15.
Published in final edited form as: Cancer Res. 2023 Nov 15;83(22):3813–3826. doi: 10.1158/0008-5472.CAN-23-0401

SETD2 Deficiency Confers Sensitivity to Dual Inhibition of DNA Methylation and PARP in Kidney Cancer

Xinyi Zhou 1,2, Yohei Sekino 1,4, Hong-Tao Li 1, Guanghou Fu 1,3, Zhi Yang 5, Shuqing Zhao 5, Hemant Gujar 1, Xiongbing Zu 2, Daniel J Weisenberger 6, Inderbir S Gill 1, Varsha Tulpule 7, Anishka D’souza 7, David I Quinn 7, Bo Han 5,*, Gangning Liang 1,*
PMCID: PMC10843145  NIHMSID: NIHMS1931819  PMID: 37695044

Abstract

SETD2 deficiency alters the epigenetic landscape by causing depletion of H3K36me3 and plays an important role in diverse forms of cancer, most notably in aggressive and metastatic clear cell renal cell carcinomas (ccRCC). Development of an effective treatment scheme targeting SETD2-compromised cancer is urgently needed. Considering that SETD2 is involved in DNA methylation and DNA repair, a combination treatment approach using DNA hypomethylating agents (HMA) and PARP inhibitors (PARPi) could have strong anti-tumor activity in SETD2-deficient kidney cancer. We tested the effects of the DNA HMA 5-aza-2’-dexoxydytidine (DAC), the PARPi talazoparib (BMN-673), and both in combination in human ccRCC models with or without SETD2 deficiency. The combination treatment of DAC and BMN-673 synergistically increased cytotoxicity in vitro in SETD2-deficient ccRCC cell lines but not in SETD2-proficient cell lines. DAC and BMN-673 led to apoptotic induction, increased DNA damage, insufficient DNA damage repair, and increased genomic instability. Furthermore, the combination treatment elevated immune responses, upregulated STING, and enhanced viral mimicry by activating transposable elements. Finally, the combination effectively suppressed the growth of SETD2-deficient ccRCC in in vivo mouse models. Together, these findings indicate that combining HMA and PARPi is a promising potential therapeutic strategy for treating SETD2-compromised ccRCC.

Keywords: Renal cell carcinoma, SETD2, DNA hypomethylating agent, PARP inhibitor

Introduction

The relative 5-year survival rate of clear cell renal cell carcinoma (ccRCC) patients drops from 91 to 11% once the primary tumor has metastasized or become aggressive (1). SETD2, encoding a histone H3 lysine 36 (H3K36) trimethylase, plays an important role in diverse forms of cancer due to its somatic mutations or down-regulated expression, most notably in RCC (2,3), and is associated with poor RCC patient prognosis (4,5).

SETD2 is involved in various non-chromatin and chromatin-related cell biological activities including spindle integrity and genomic stability, STAT1 activity for interferon antiviral activity, activation of p53, homologous recombination (HR) and mismatch repair (MMR), maintenance of gene body DNA methylation, and recruitment of RNA splicing machinery (6). As a result of the extensive diversity and novel functional roles of SETD2, together with its strong connection with ccRCC tumor aggressiveness, there is an urgent need to develop novel treatments to target SETD2-compromised cancer cells.

Genomic instability due to aberrant DNA methylation is a hallmark of human cancers and DNA demethylating agents have shown clinical anti-tumor efficacy (7,8). Results from our group and others demonstrated that DNA hypomethylating agents (HMAs) have anti-neoplastic effects including: 1) reactivation of tumor suppressor genes (9), 2) down-regulation of overexpressed oncogenes with methylated DNA gene bodies prior to treatment (10), 3) reactivation of DNA methylation-silenced endogenous retroviruses (ERVs) via viral mimicry to stimulate immune responses (11,12) and induce cell necrosis and death (13), and 4) durable antitumor effects in transient low doses (10,14).

Recent studies including a study from our group (15) have also demonstrated that kidney cancer cells with SETD2 mutations or downregulated SETD2 expression are sensitive to HMAs both in vitro and in vivo (15). This was also shown from a completed clinical trial for acute myeloid leukemia (AML) (16). Interestingly, combination treatments comprised of an HMA with a poly(ADP-ribose) polymerase inhibitor (PARPi) (HMA + PARPi) also showed dramatic cell growth inhibition by enhancing DNA damage and immune signals, most notably in DNA repair deficient cancer cells, such as BRCA-mutated breast cancers (17,18). PARPis are novel drugs currently used in treating patients with ovarian cancer, breast cancer and other solid tumors (19–21). PARP1 is involved in HR related to double strand break (DSB) repair by allowing cancer cells to survive ongoing DNA damage, while PARPis block the catalytic activity of PARP1, resulting in the accumulation of cytotoxic DSBs, thereby leading to cell death (22,23). SETD2 loss may also result in increased DNA damage because of its role in HR and DSB repair, therefore, SETD2 is thought to be a therapeutic target of PARPi (24,25). We hypothesized that cancer cells with impaired or low SETD2 expression show increased sensitivity to the HMA + PARPi combination treatment due to aberrant DNA methylation and DNA repair deficiency in SETD2-compromised cancer cells.

In this study, we have demonstrated that the combination of the HMA 5-Aza-2’-deoxycytidine (decitabine, DAC) and the PARPi Talazoparib/BMN-673 improves anti-tumor modulation in SETD2-deficient RCC cell lines in both in vitro and in vivo settings. The synergistic anti-tumor effects are dependent on the accumulation of DNA damage, an insufficient DNA damage repair response, upregulation of immune responses including activation of transposable elements (TEs) (viral mimicry) and the STING1 pathway, as well as the loss of genomic stability, in SETD2-compromised RCC cells. The combination of HMA + PARPi is a potential promising therapy for SETD2-compromised RCCs and provides strong support for further clinical interrogation in a precision-based approach for patients with aggressive ccRCC.

Materials and Methods

Cell Culture and Drugs

Human RCC cell lines 786–0 [786-O] (ATCC® CRL-1932™) and 769-P (ATCC® CRL-1933™) were cultured in RPMI1640 + L-Glutamine (Corning) and 10% Fetal Bovine Serum (FBS, Corning) and 1% penicillin-streptomycin (pen-strep, Genesee Scientific); ACHN (ATCC® CRL-1611™) and A-498 (ATCC® HTB-44™) cells were cultured in Minimum Essential Medium (MEM) + Earle’s Salts + L-glutamine (GenClone, Cat.: 25–504) with 10% FBS and 1% pen-strep; Caki-2 (ATCC® HTB-47™) was cultured in McCoy’s 5A Medium + 5 mM L-glutamine + 2200 mg/L sodium bicarbonate (ATCC® 30–2007™) with 10% FBS and 1% pen-strep.

DAC (5-Aza-CdR, MedChemExpress, Cat.: HY-A0004) was prepared at 60μM in PBS. The PARPi Talazoparib/BMN-673 (MedChemExpress, Cat.: HY-16106) was prepared at 50 mM stock in DMSO and diluted in PBS to the indicated concentrations before use.

CRISPR/Cas9-Mediated SETD2 knockout

To generate 786–0 SETD2 knockout cells, an sgRNA targeting SETD2 (ACT CTG ATC GTC GCT ACC AT) was cloned into LentiCRISPR vector as previously reported (26). To make Lentivirus, the LentiCRISPR_sgRNA was co-transfected into HEK293T cells with the packaging plasmids pVSVg (RRID: Addgene_8454) and psPAX2 (RRID: Addgene_12260) using Lipofectamine 2000 Transfection Reagent (ThermoFisher Scientific). Empty LentiCRISPR vector (EV) was used as a no-target control. Virus particles were collected 48 hours after transfection as described in (27). 786–0 cells were infected with lentivirus to generate stable SETD2 knockout cells followed by 1 μg/ml puromycin selection for 7 days. Single-cell clones were picked from the surviving cells for downstream verification of SETD2 ablation. SETD2 knockout clones were identified by western blot using a primary antibody against H3K36me3.

Cell Survival Assay

786–0 (3×104), ACHN (1.5×105), A-498 (3×104), Caki-2 (1×105) and 769-P (4×104) cells were seeded into 6-well tissue culture plates, treated with the indicated compounds or vehicle control, and were harvested, re-suspended, and counted using a coulter counter analyzer (Beckman Coulter, Inc.) as indicated in Figure 1. The synergistic effect of DAC and BMN-673 was evaluated using CompuSyn software (https://www.combosyn.com) (Supplemental Table 1). Combination index (CI)<1 indicates a synergistic effect, CI=1 indicates an additive effect and CI>1 indicates antagonistic effect.

Figure 1. Combination treatment of an HMA (DAC) with a PARPi (BMN-673) synergistically inhibits cell growth and induces apoptosis in SETD2-deficient RCC cell lines.

Figure 1.

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A-C: Western blot of H3K36me3 (left panel) and cell proliferation assay (right panel, 5 days after the indicated treatments; NT: non-treated; 25, 50, 100nM DAC; 10nM BMN-673; combination treatments: 25nM DAC + 10nM BMN-673: 50nM DAC + 10nM BMN-673; 100nM DAC + 10nM BMN-673) in ACHN and A498 (A), Caki-2 and 769-P (B) and 786–0 SETD2-WT/KO (C) cell lines. D-F: Cell cycle arrest analysis (5 days post indicated treatments; concentration: NT: non-treated; 100nM DAC; 10nM BMN-673; combination treatment: 100nM DAC 100nM + 10nM BMN-673 in ACHN and A498 (D), Caki-2 and 769-P (E) and 786–0 SETD2-WT/KO (F) cell lines. Bar graphs represent the percentage of cells in G0/G1 (gray), S (red) and G2/M (blue) phases. G-I: Flow cytometry apoptosis analysis (7 days post indicated treatments; NT: non-treated; 100nM DAC; 10nM BMN-673; combination treatment: 100nM DAC + 10nM BMN-673) in ACHN and A498 (G), Caki-2 and 769-P (H) and 786–0 SETD2-WT/KO (I) cell lines. Bar graphs represent the percentage of cells in early apoptosis (red), late apoptosis (black), and necrotic (green) stages. Values are presented as mean ± SEM of three independent experiments. Two-tailed unpaired t-test was used to calculate statistical significance. n.s.: non-significant, * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001.

Colony Formation Assay

786–0 (SETD2-WT: 1×103, SETD2-KO: 1.3×103), ACHN (1.2×104), A-498 (3×103), Caki-2 (1×104) and 769-P (3×103) cells were seeded into 6-well tissue culture plates and treated with the indicated compounds. After culturing for 10 – 13 days, colonies were washed twice with PBS and fixed with methanol for 15 min. Fixed colonies were stained with 2% crystal violet (Sigma-Aldrich #61135) for 15 min at room temperature. Colonies were washed with deionized H2O and air dried in dark overnight. Original images were scanned by an HP Scanjet 8200 Digital Flatbed Scanner. Integrated density was measured using National Institutes of Health (NIH) ImageJ software.

Western Blot

Cell total protein extracts were prepared by cell lysis with RIPA buffer (Thermo Scientific™, Cat.: 89900), Micrococcal Nuclease, Micrococcal Nuclease Buffer (NEW ENGLAND BioLabs, # M0247S and #B0247S) and Protease and Phosphatase Inhibitor (Thermo Scientific™ Halt™, Cat.: 78442). Total cell protein was mixed with NuPAGE™ LDS Sample Buffer (4X, Thermo Scientific™, Cat.: NP0007) and NuPAGE™ Sample Reducing Agent (10X, Thermo Scientific™, Cat.: NP0009) and boiled at 98°C for 5 min. Equal amounts of protein extracts were resolved by 4–15% precast polyacrylamide gel electrophoresis (BIO-RAD Mini-PROTEAN® TGX™) and transferred to a nitrocellulose membrane (BIO-RAD, #1704270). Immunoblotting was performed with primary antibodies against the following proteins: H3K36me3 (CST, #4909), histone H3 (ab1791), histone H1.3 (ab24174), histone H1.5 (ab24175), γH2A.X (Phospho S139) (ab81299), CtIP (CST, #9201), RAD51 (CST, #8875), RPA32 (CST, #35869), KU70 (CST, #4588), STING (CST, #13647), β-actin (Sigma-Aldrich #A2228) and secondary antibodies: Goat anti Rabbit IgG (Fc):HRP (BIO-RAD, STAR121P), m-IgGκ BP-HRP (Santa Cruz, sc-516102). Bands were quantified using Image Lab V5.1.

Comet Assay

DNA damage in SETD2-WT or KO ccRCC cells were detected by alkaline comet assay using the OxiSelect™ Comet Assay Kit (Cell Biolabs, STA-351) according to the manufacturer’s instructions. A Zeiss Axio Scope A1 (Carl Zeiss) microscope equipped with a 10× objective was used to visualize cells. The extent of DNA damage was estimated by measuring the fluorescence of the comet’s head and tail using the ImageJ software (OpenComet plug-in). Each experimental group had 70–200 randomly chosen cells detected.

Flow Cytometry

Apoptosis:

After administration of the indicated compounds or vehicle, 2×105 cells were re-suspended in binding buffer and incubated for 15 min at room temperature with FITC-labelled annexin V and/or propidium iodide (PI) using the MEBCYTO Apoptosis Kit (MBL, #4700). Positive control cells were incubated in 5mM H2O2 for 20 min followed by clean fresh medium incubation for 40 min.

Cell cycle analysis:

The G0/G1 phase cells have the DNA content of diploid cells, while the G2/M phase has the DNA content of tetraploid cells, and the S phase has the DNA content of cells in between diploid and tetraploid cells. After administration of the indicated compounds or vehicle, 1×106 cells were re-suspended in PBS and fixed in 70% cold ethanol overnight. Fixed cells were incubated for 30 min at room temperature with FxCycle™ Violet stain (Invitrogen™ #F10347).

Cells were analyzed by a LSRII Cell Analyzer and Fortessa X-20 Cell Analyzer (BD Biosciences, San Jose, CA) and the results were parsed with FlowJo_v10.8 (BD Biosciences) and ModFit LT 5.0.9. The statistical analyses were obtained from three independent experiments (n = 3).

Total RNA Extraction and RNA-seq Analyses

Total RNA from 786–0 cells after indicated treatment was extracted using RNeasy Mini Kit (Qiagen, Cat.:74106) followed by on-column DNase I digestion according to the manufacturer’s protocol. For total RNA-seq with ribosomal RNA (rRNA) reduction and strand specificity retained, libraries were prepared using KAPA RNA HyperPrep Kit with RiboErase (HMR) Globin (Roche, Cat.: KK8563) and sequenced on Illumina NovaSeq 6000 as PE 150 bp paired-ends. RNA-seq reads were trimmed for adapter sequences by Trimmomatic and aligned to the hg38 genome by Partek Flow (v9.0) and featureCounts with proper capture of RNA strand orientation. Data analyses were performed by R studio with EdgeR, org.Hs.eg.db, clusterProfiler, ComplexHeatmap, topGO and other R packages. GSEA analysis was performed by GSEA software (v4.1.0, Broad Institute, Inc.)

Xenograft Models

Male mice (Athymic Nude, 6–8 weeks old) were used for 786–0 WT and KO xenograft studies. Exponentially growing cells (3×106) were mixed with 100μL Matrigel and injected subcutaneously above the left and right hind legs of the mice. One week after injection, volumes were externally measured in two dimensions using electronic calipers [(length×width2)/2]. When tumors reached 250–300 mm3, mice were sorted into eight groups (n = 6 in each group) so that the mean tumor volume between groups was similar. Mice were observed daily, weighed three times per week, and tumor volume was measured twice per week. Mice were treated with BMN-673 (0.3mg/kg), DAC (0.5mg/kg), both in combination or vehicle control. DAC was prepared in PBS at 0.15 mg/mL and stored in −80°C in the dark. BMN-673 was prepared in 1% DMSO at 9 mg/mL and stored in −80°C in the dark and diluted in PBS to 0.09 mg/mL before use. DAC and BMN-673 were administered by intraperitoneal (i.p.) injection 3 days per week. Mice were euthanized when tumors reached 1,500 mm3 or showed necrosis. All mice were housed in a 12-hr. light/dark cycle with access to food and water ad libitum. Studies were performed with Institutional Animal Care and Use Committee approval.

Hematoxylin-eosin (H&E) and Immunohistochemistry (IHC) Staining

Fresh mouse subcutaneous tumors were fixed in 4% paraformaldehyde (PFA) and embedded with paraffin for histological examinations. Sections with 5-μm thickness were cut and stained with hematoxylin-eosin. For IHC, mouse tumor tissue sections were deparaffinized and sequentially hydrate in xylene, 100% and 95% ethanol. Antigen unmasking was performed in sodium citrate buffer (pH≈6.0) at sub-boiling temperature (95–98°C) for 10 min. Endogenous peroxidase was blocked with 3% hydrogen peroxide (Sigma-Aldrich #H1009) for 10 min, followed by 1-hour incubation with TBST/5% normal goat serum (Sigma-Aldrich #G9023) to block non-specific binding. The slides were then incubated overnight at 4 °C with primary antibodies, anti-H3K36me3 (1:200) or anti-Ki67 (ab16667, 1:200). After washing, the tissue sections were treated with SignalStain® Boost IHC Detection Reagent (HRP, Rabbit, CST #8114) for 30 min at room temperature. After treatment with SignalStain® diaminobenzidine (DAB) Substrate Kit (CST #8059), the stained slides were counterstained with hematoxylin and mounted. Three tumor samples were randomly chosen from each experimental group, four microscopic fields at 100× magnification were randomly selected from each sample. In total, microscopic fields (33–37/group) at 400× magnification per group were evaluated with the immunoreactivity. The integrated optical density (IOD) of each microscopic fields were measured using Image-Pro Plus.

Statistical Analysis

Statistical analyses for biological assays were performed using the two-tailed unpaired t-test (GraphPad Prism v9, San Diego, CA, USA) to calculate statistical significance. Statistical significance was considered at p < 0.05. Values are presented as mean ± SEM.

Data and Material Availability

The RNA sequencing data generated in this study is publicly available in Gene Expression Omnibus (GEO) at accession number GSE223893. The code used for the analysis of this study is provided in Github: https://github.com/XinyiZhouViv/ccRCC_SETD2_DAC_BMN.git. All other raw data are available upon request from the corresponding author. In addition, the publicly available data analyzed in this study was obtained from cBioPortal at https://www.cbioportal.org/study/summary?id=kirc_tcga_pan_can_atlas_2018.

Results

Combination treatment of HMA (DAC) with PARPi (BMN-673) synergistically inhibits cell growth and induces apoptosis in SETD2-deficient RCC cell lines

We used DAC as an HMA and BMN-673 as a PARPi to test whether human RCC cells harboring SETD2 deficiencies are sensitive to HMA + PARPi combination treatment as other studies have demonstrated for BRCA1-mutated cancer cells (17). DAC incorporation into genomic DNA is dependent on cell replication and PARPi activity also depends on cell proliferation to trap PARP proteins as they bind to DSBs (28,29). Therefore, we then organized DAC and PARPi treatment schema into three paired groups based on similar cell population doubling times: 1) ACHN (SETD2 wild-type (WT)) and A498 (SETD2 mutant) (Figure 1A left panel), 2) Caki-2 (SETD2 WT) and 769-P (SETD2 down-regulated) (Figure 1B left panel), and 3) 786–0 (SETD2 WT) and 786–0 (SETD2 knock-out (KO)) (Figure 1C left panel). The synergistic effect of DAC and BMN-673 was also confirmed by CompuSyn software (https://www.combosyn.com) in all cell lines but in different doses and is shown in Supplemental Table 1. It should be noted that 786–0 cells exhibit substantial DAC resistance based on previous studies (15). To determine whether SETD2 is the main determinant for cell inhibition, we established CRISPR-Cas9 SETD2 Knock-out (KO) in 786–0 cells (15).

ACHN (SETD2 WT), A498 (SETD2 mutant), Caki-2 (SETD2 WT) and 769-P (SETD2 down-regulated) cells were treated with the indicated drug combinations for 48 hours, while 786–0 SETD2 WT and 786–0 SETD2 KO cells were treated for 24 hours to ensure at least one cell doubling cycle before drug removal. Cell growth inhibition occurred after single DAC doses (25–100nM) and dramatically increased after combining with BMN-673 (10nM) (Figure 1A–C right panel, Supplemental Figure 1A–C). Low dose, single BMN-673 treatment resulted in reduced cell division regardless of SETD2 status, except for ACHN and 786–0 WT cells (Figure 1A and 1C right panel, Supplemental Figure 1A and 1C). Interestingly, besides SETD2 down-regulation, 769-P is known to have a BRCA1-associated protein-1 (BAP1) mutation that may lead to cytotoxicity upon BMN-673 single treatment (30). Importantly, we detected exacerbated sensitivity after combination treatments of DAC + BMN-673 in SETD2 deficient cells (769-P, A498, and 786–0 SETD2-KO) when compared to the SETD2-WT cell lines (Figure 1A–C).

Cell inhibition rate can be influenced by cell proliferation speed and cell population survival rate. Therefore, we performed cell cycle arrest analysis at the indicated time points spanning two cell doubling cycles to allow for full impact of the drug treatments. The combination treatments of DAC + BMN-673 increased S phase or G2/M phase cell arrest in all cell lines regardless of SETD2 status but with only limited changes after single treatments (Figure 1D–F, Supplemental Figure 1D). However, since arrested cells are capable of restoring normal DNA preparation functions, including repairing damaged DNA and correctly aligning chromosomes, arrested cells may pass checkpoints and return to their normal cell proliferation cycle (31). With this in mind, we performed apoptotic analyses and noted that cell growth inhibition was correlated with increased early and late apoptosis, as determined by Annexin V-FITC measurements using flow cytometry (Figure 1G–I, Supplemental Figure 1E). Consistent with cell growth inhibition (Figure 1A–C), SETD2 deficient cells (A498, 769-P, and 786–0 with SETD2 KO) showed a significantly increased apoptotic cell population of 44–88% compared to 18–33% of WT cells (ACHN, Caki-2, and 786–0 SETD2 WT) upon combination treatment (Figure 1G–I, Supplemental Figure 1E). Based on these results, we conclude that the combination treatment of DAC + BMN-673 additively or synergistically inhibits cell growth by inducing apoptosis in SETD2-altered RCC cell lines.

SETD2-deficent RCC cell lines generate increased DNA damage but fail to initiate sufficient DNA damage repair upon combination treatment

Given the roles of SETD2 in Homologous Recombination (HR) and DSB repair and the synthetic lethality of PARPi when administered to cancer cells that harbor defects in DNA repair pathway genes (32), we hypothesized that the higher rates of cell growth inhibition and apoptosis in SETD2 deficient cell lines upon combination treatment of DAC + BMN-673 are mechanistically linked to DNA damage and repair mechanisms. We performed Western blot analysis for the DSB marker γ-H2A.X to measure the levels of DNA damage after drug treatments. Please note, the antibody we used targets H2A.X phosphorylated at serine 139, which is directly involved in binding to DSBs (33). We found increased global γ-H2A.X protein levels in SETD2 deficient cell lines after comparing ACHN with A498 cells (Figure 2A, 2B) and 786–0 WT with 786–0 SETD2 KO cells (Figure 2C, 2D). Quantitative analyses also indicated 4–15-fold increased DNA damage in SETD2-deficient cell lines comparing to 1.5–6-fold increase in SETD2 WT cells after combination treatment (Figure 2C, 2D). However, γ-H2A.X levels in SETD2-downregulated 769-P cells were not dramatically higher than SETD2-WT Caki-2 cells (Figure 2E, 2F). We subsequently performed single-cell gel electrophoresis comet assay for direct evidence of DNA damage and found that SETD2 deficient cell lines generated longer and more pronounced DNA fragment tails upon combination drug treatments (p < 0.05) (Figure 2G, 2H, 2I).

Figure 2. SETD2-deficent RCC cell lines generate more DNA damage but fail to initiate sufficient DNA damage repair upon combination treatment.

Figure 2.

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A-B: Western blot of γ-H2A.X (96h post indicated treatments) (A) and bar graphs of γ-H2A.X/H3 relative ratio to NT groups (B) in ACHN and A498 cell lines. C-D: Western blot of γ-H2A.X (96h post indicated treatments) (C) and bar graphs of γ-H2A.X/H3 relative ratio to NT groups (D) in 786–0 SETD2-WT/KO cell lines. E-F: Western blot of γ-H2A.X (96h post indicated treatments) (E) and bar graphs of γ-H2A.X/H3 relative ratio to NT groups (F) in Caki-2 and 769-P cell lines. G-I: Comet assay olive moments relative to NT groups in ACHN and A498 cell lines (G), 786–0 SETD2-WT/KO cell lines (H), Caki-2 and 769-P cell lines(I). J-K: Western blot (J) and fold change bar graphs (K) of HR and NHEJ repair pathway proteins (CtIP, RPA32, RAD51 for HR and Ku70 for NHEJ) in 786–0 SETD2-WT/KO cell lines (96h post indicated treatments). Bar graph values are presented as mean ± SEM of three independent experiments. Comet assay has 70–200 randomly chosen cells detected per treatment group. Two-tailed unpaired t-test was used to calculate statistical significance. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001.

DNA damage is repaired by multiple mechanisms, including two major pathways for DSBs: homologous (HR) and non-homologous DNA end joining (NHEJ) repair (34). Unrepaired DSBs caused by defects in these pathways may not only cause cell cycle arrest and apoptosis, but also lead to impaired genome integrity and cell death (35,36). HR repair response is mainly driven by the RAD51 recombinase (37), the single-stranded DNA-binding protein RPA32 (38) and CtIP, which facilitates the transitions from DSB sensing to processing and then to trigger HR repair activity (39,40). NHEJ repair response mainly involves the Ku70/Ku80 heterodimer, which tethers DSB ends and protects ends from resection (41,42).

We performed western blot analyses to measure expression of HR (RAD51, RPA32 and CtIP) and NHEJ (Ku70) repair proteins after DAC + PARPi combination drug treatments in 786–0 WT and 786–0 SETD2-KO cells (Figure 2J). We noted substantial increased expression of HR and NHEJ repair proteins induced by the DAC + BMN-673 combination treatment, however, CtIP levels were not dramatically changed after drug treatments. This is consistent with the positive trend of γ-H2A.X protein expression in SETD2-WT cell lines after combination drug treatments, however, the HR/NHEJ component protein expression changes (Figure 2K) did not match the more substantial changes in γ-H2A.X expression levels or DNA damage (Figure 2H) in SETD2 deficient cell lines. This finding suggests that SETD2-altered RCC cell lines are more sensitive to DAC + BMN-673 combination therapy by exacerbating DNA damage but with less efficient DNA DBS repair.

Combination treatment activates immune response and SETD2 loss further promotes TE expression

We performed bulk RNA-seq analysis to explore the transcriptional profile changes of 786–0 WT and 786–0 SETD2-KO cells before and after drug treatments. DAC and other DNA hypomethylating agents exhibit anti-tumor effects through viral mimicry and interferon response by activating the cGAS-STING pathway and transposable elements (TEs), including endogenous retroviruses (ERVs) (11,12,43). The cGAS-STING pathway stands out not only because of its role in the regulation of intrinsic anti-tumor immunity, but also as being at the crossroads between inflammation and DNA repair (43,44). Indeed, we observed dramatic STING protein upregulation upon DAC or DAC + BMN-673 treatments, most notably in 786–0 SETD2-KO cells (Figure 3A–B). In addition, we recently demonstrated that SETD2 loss is associated with interferon response and TE activation upon DAC treatment (15).

Figure 3. Combination treatment activates immune response and loss of SETD2 enhanced the promotion of TE expression.

Figure 3.

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A-B: Western blot (A) and fold change bar graphs (B) of STING expression in 786–0 SETD2-WT/KO cell lines (96h post indicated treatments). C: Normalized enrichment score (NES) heatmap of the top 20 up-regulated GSEA gene ontology (GO) Biological Process (BP) pathways in 786–0 SETD2-WT/KO cells on days 5, 16 and 26 after combination treatment with 100nM DAC and/or 10nM BMN-673. D-E: Activated transposable element (TE) number (D) and Z-score heatmap representation (logFC>1 compared to NT groups) (E) in 786–0 SETD2-WT/KO cells on day 5, 16 and 26 after combination treatment with 100nM DAC 100nM and 10nM BMN-673).

We performed RNA-seq GSEA Gene Ontology pathway analysis that showed the top upregulated pathways after DAC or DAC + BMN-673 treatments are majorly associated with innate and adaptive immune response (Figure 3C) but not PARP inhibitor alone (Supplemental Figure 2A). In addition, immune response upregulation is associated with TE upregulation in both number and scope, especially after DAC + BMN-673 combination treatments (Figure 3D–E), suggesting that DAC and/or DAC + BMN-673 combination treatments enhance viral mimicry and immune response to increase the anti-neoplastic function in SETD2-aberrant RCC tumors.

Genomic stability related pathways and H1 linker genes are down-regulated in SETD2-KO 786–0 cells upon DAC + PARPi combination treatment

Although the importance of chromatin organization in maintaining genomic stability and DNA damage repair is underscored, we noticed that heterochromatin and nucleosome organization pathways are down-regulated in 786–0 SETD2 KO cells upon DAC + BMN-673 combination treatment (Figure 4A) but not PARPi alone (Supplemental Figure 2B). To confirm this finding, we also performed additional pathway analyses of not only differentially expressed genes (DEGs), but also the most significantly down-regulated pathways associated with genomic stability: nucleosome assembly (GO:0006334), nucleosome organization (GO:0034728), DNA replication-dependent chromatin organization (GO:0034723) and chromatin assembly (GO:0031497) (Figure 4B, Supplemental Table 2).

Figure 4. Genomic stability related pathways and H1 linker genes are specifically down-regulated in SETD2-KO 786–0 cells after combination treatment.

Figure 4.

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A: Normalized enrichment score (NES) heatmap of the top 20 down-regulated GSEA gene ontology (GO) Biological Process (BP) pathways of 786–0 SETD2-WT/KO cell lines on days 5, 16 and 26 after the indicated treatments (100nM DAC and/or 10nM BMN-673). B: GSEA plots of down-regulated pathways, nucleosome assembly (GO:0006334, blue), nucleosome organization (GO:0034728, purple), DNA replication-dependent chromatin organization (GO:0034723, green) and chromatin assembly (GO:0031497, red), of 786–0 SETD2-WT/KO cells on day 5 after a one-time combination treatment of 100nM DAC + 10nM BMN-673. C: Volcano plots of genes involved in down-regulated pathway, nucleosome assembly (GO:0006334), of 786–0 SETD2-WT/KO cell lines on day 5 after a one time indicated treatment of 100nM DAC 100nM and 10nM BMN-673.

Among genes that are involved in these genomic stability related pathways, we found that histone related components (H1, H2, H3, and H4), most notably histone H1, were dramatically down-regulated in SETD2 KO 786–0 cells following DAC + BMN-673 combination treatment (Figure 4C, Supplemental Figure 2C). Furthermore, the H1 variants H1.3 and H1.5 were down-regulated by Western Blot analysis (Supplemental Figure 2D). Taken together, the loss of chromatin integrity after DAC + BMN-673 combination treatment supports our previous findings of DSB accumulation with insufficient DNA damage repair and the promotion of aberrant TE expression after drug treatment (Figures 2 and 3). Moreover, these data indicate that disturbing genomic stability positively correlates with increased DAC + BMN-673 combination drug sensitivity in SETD2 altered RCC cells.

Identification of target genes of combination treatment in primary ccRCC tumors

Clinically, tumors with SETD2 mutations or down-regulated SETD2 expression are associated with decreased recurrence-free survival, advanced tumor stage, grade and tumor invasiveness in ccRCC (5,45). Thus, it is necessary to test whether the DAC + BMN-673 combination treatment can partially reverse the ccRCC-specific gene expression profiles as a function of SETD2 deficiency, since this information may yield important applications for clinical trials in ccRCC patients. Based on the Kidney Renal Clear Cell Carcinoma TCGA PanCancer RNA-seq data (2), we compared DEGs in tumors with high SETD2 expression (SETD2-high, top 25% of all samples) or tumors with mutated or low SETD2 expression (SETD2-low/mut, bottom 25% of all samples) to data from adjacent-normal kidney tissues and intersected with gene expression profiles of 786–0 WT and 786–0 SETD2-KO cells after treatment with DAC, BMN-673 or both in combination (Supplemental Figure 3A).

We identified 3,001 up-regulated genes in SETD2-low/mut patients by comparing adjacent-normal tissue, among which 35–175 genes overlap with those up-regulated in SETD2-low/mut patients and those that are down-regulated in 786–0 SETD2-KO cells after drug treatments (BMN-673: 35/124, DAC: 87/398, DAC+BMN: 175/795, in which the first number indicates the number of genes that overlap with those down-regulated in 786–0 SETD2-KO cells and the second number indicates the genes that overlap with those that are up-regulated in SETD2-low/mut patients. Figure 5A and 5B, Supplemental Figure 3B).

Figure 5. Identification of target genes after DAC and BMN-673 combination treatment in primary ccRCC tumors.

Figure 5.

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A: Bar graph of up- and down-regulated genes in low/mut-SETD2 patients from TCGA ccRCC data. B: Dot-plots (left panel) and bar graphs (right panel) of the genes up-regulated in low/mut-SETD2 patients but are reversely expressed in 786–0 SETD2 KO cells at day 5 after treatment with 100nM DAC 100nM and/or 10nM BMN-673. C: Dot-plots (left panel) and bar graphs (right panel) of the genes down-regulated in low/mut-SETD2 patients but are reversely expressed in 786–0 SETD2 KO cells at day 5 after the indicated treatments (100nM DAC 100nM and/or 10nM BMN-673). D: Bar graphs of up- and down-regulated genes in high-SETD2 patients from the TCGA database. E: Dot-plots (left panel) and bar graphs (right panel) of the genes up-regulated in SETD2-high patients that display reverse expression in 786–0 SETD2 WT cells at day 5 after the treatments with 100nM DAC 100nM and/or 10nM BMN-673. F: Dot-plots (left panel) and bar graphs (right panel) of the genes down-regulated in SETD2-high patients but display reverse expression in 786–0 SETD2 WT cells at day 5 after treatment with 100nM DAC 100nM and/or 10nM BMN-673.

We also identified 2,082 down-regulated genes in SETD2-low/mut patients, among which up to 349 genes are up-regulated in 786–0 KO cells after drug treatments: 4/47 (BMN-673), 277/1,554 (DAC), and 349/1,980 (DAC+BMN-673). (Figure 5A, 5C, Supplemental Figure 3C, in which the first and second numbers indicate the number of overlapping genes up-regulated in 786–0 SETD2-KO cells and down-regulated in SETD2-low/mut patients, respectively). In separate analyses we identified 2,492 up-regulated genes in SETD2-high ccRCC patients, among which 40/129 and 79/465 genes are down-regulated in 786–0 WT cells after DAC and DAC + BMN-673 treatments, respectively (Figure 5D–E, Supplemental Figure 3D in which the first and second numbers indicate the number of genes that overlap with those that are down-regulated in 786–0 SETD2-WT cells and up-regulated in SETD2-high patients, respectively).

In SETD2-high patients, we identified 1,613 down-regulated genes, among which 215/1,396 and 266/1,848 genes are up-regulated in 786–0 WT cells after DAC and DAC + BMN-673 treatments, respectively (Figure 5D, 5F, Supplemental Figure 3E in which the first and second numbers indicate the number of genes that overlap with those that are up-regulated in 786–0 SETD2-WT cells and down-regulated in SETD2-high patients, respectively). These findings suggest that the combination treatments reverse the proportion of tumor gene expression profiles (3.2%−16.8%) back to those in normal-like tissues. Interestingly, the genes reversed by the combination treatment are involved in pathways correlated with organ differentiation and development (Supplemental Figure 3F–G), indicating that DAC + BMN-673 combination treatments can potentially reverse the clinical tumor features, especially in patients with SETD2 mutations or low SETD2 expression. Although we observed expression reversal after treatment, we also observed that DEGs were more substantially up-regulated than down-regulated in the up-regulated groups (Figure 5A and 5D), and fewer genes were down-regulated than up-regulated in the down-regulated groups (Figure 5A and 5D, Supplemental Figure 3H and I).

SETD2 loss sensitizes RCC tumors to DAC and BMN-673 combination therapy in vivo

In order to confirm the in vitro preclinical data, we established in vivo RCC models in immune-deficient nude mice by implanting SETD2 WT/KO 786–0 cells (Figure 6A). We grafted two subcutaneous tumors per mouse with 3 × 106 of SETD2-WT/SE2-WT or SETD2-KO/Setd2-KO cells. Mice were randomized to the following treatment groups: 1) untreated control with PBS, 2) 5-Aza-CdR (DAC, 0.5mg/kg, three times per week by intraperitoneal injection (i.p.)), 3) Talazoparib (BMN-673, 0.3mg/kg) three times per week, i.p.), and 4) combination of DAC+BMN-673 three times per week for 3–4 weeks (Figure 6A). In all treatment groups, mice tolerated DAC or BMN-673 monotherapies as well as the combination DAC + BMN-673 therapy as evidenced by stable body weights in all treatment groups (Figure 6B). In support of this, we did not detect any individual cases of acute or chronic death due to drug toxicity during the experiment.

Figure 6. SETD2 loss sensitizes RCC tumors to DAC and BMN-673 combination therapy in vivo.

Figure 6.

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A: Experimental design of DAC (0.5mg/kg, 3 times/wk, i.p.) and BMN-673 (0.3mg/kg, 3 times/wk, i.p.) treatment of 786–0 SETD2-WT/KO tumors in nude mice. B: Percentage of body weight change of mice in each group from the start of treatment. C: Original tumor images of xenografts at treatment endpoint. D: Relative tumor sizes (compared to NT groups) of 786–0 SETD2-WT/KO xenografts upon indicated drug treatments. E: Representative immunohistochemistry (IHC) images (left panel) and bar graph of Ki67 expression (right panel) in 786–0 SETD2-WT/KO xenografts. Bar graph values are presented as mean ± SEM. A two-tailed unpaired t-test was used to calculate statistical significance. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001.

Compared to the non-treated group, neither DAC (0.5mg/kg) nor BMN-673 (0.3mg/kg) monotherapy, nor DAC + BMN-673 combination therapy, resulted in significant anti-tumor effects in mice harboring 786–0 SETD2-WT tumors (Figure 6C, 6D). However, in 786–0 SETD2-KO tumors, treatment with DAC alone or in combination with BMN-673, yielded a significant tumor burden reduction (p =0.0057, and p = 0.0013) compared to the control group (Figure 6C, 6D). While the mice carried tumor burden, low SETD2 expression was maintained inSETD2 KO tumors during the experiment (Supplemental Figure 4). Although we did not identify significant tumor size differences between DAC alone and DAC + BMN-673 combination treatment in SETD2-KO mice (p = 0.1361), immunohistochemistry (IHC) of Ki67, a marker for cell proliferation activity, showed that SETD2-KO tumor cell proliferation was significantly (p=0.0003) inhibited by the combination treatment when compared SETD2-WT tumors and DAC treated SETD2-KO tumors (Figure 6E). In conclusion, we confirmed that SETD2 loss sensitizes RCC tumors to DAC + BMN-673 combination therapy in vitro and in vivo.

Discussion

Impaired H3K36me3 occupancy due to SETD2 mutations or down-regulated SETD2 expression is highly associated with cancer aggressiveness (4,46–48), as SETD2 mutation is a key driver event in ccRCC metastasis (49). In this study, we continued our previous work (15) and showed that SETD2 deficiency may be a therapeutic target of combination treatment of HMA + PARPi for aggressive RCC patients. The combination treatment of HMA (5-Aza-CdR, DAC) + PARPi (Talazoparib, BMN-673) synergistically inhibits cell growth in SETD2-deficient RCC cells in vitro and in vivo. This depends on a series of mechanisms including the accumulation of DNA damage, insufficient DNA damage repair, upregulation of immune responses including activation of TEs (viral mimicry) and the STING1 pathway, as well as loss of genomic stability.

Despite the evidence showing that HMA + PARPi combination treatments can induce cytotoxicity by increasing complex retention on DNA DSBs and down-regulating DNA repair protein genes (17), our study demonstrated that combination treatments in SETD2-altered RCCs are not only related to DNA damage and repair, but also related to TE-induced enhancement that promotes viral mimicry. Although the importance of chromatin organization in maintaining genomic stability and DNA damage repair is not well studied, the dysregulation of heterochromatin organization and nucleosome assembly may affect the open chromatin structure and the unique array of heterochromatin binding proteins, thereby increasing susceptibility to DNA damage and influencing the recruitment of specific repair proteins (50–52).

The loss of genomic structural stability and down-regulation of histone H1 variants in SETD2 KO tumors upon combination treatment further links the mechanisms of DNA damage, genomic instability and immune response signaling (53). A recent study revealed that strong H1 depletion can cause de-repression of repetitive sequences such as LINE-1 and ERVs (54). H1 and DNA methylation also jointly maintain transcriptional homeostasis by silencing TEs and aberrant intragenic transcripts (55). As a critical regulator of genome stability and integrity, H1 deletion associates with compromised DNA damage repair (56,57). These studies also provided a direct support to our findings: accumulation of DSBs with insufficient DNA damage repair and the promotion of TE expression for up-regulation of immune responses in SETD2-defficient cells after drug treatments.

When exploring the relationship between cell inhibition with cell cycle arrest and apoptosis, we found that the combination treatment increased tumor cell S and/or G2/M phase arrest. This result is consistent with the observation that PARP activity mainly targets cells in S and G2 phases (58). PARP1 is necessary for primase activity and replication-coupled repair in S-phase, and PARP1 depletion leads to G2/M arrest upon genotoxic stress (59). In S and G2/M phases, long-term cell arrest mainly results in an irreversible exit from the cell cycle through senescence or apoptosis (31).

Although SETD2 is crucial for HR repair, our study found that 10nM BMN-673 alone was not sufficient to induce a dramatic synergistic lethal effect in SETD2-deficient RCC tumors, however, our data show that multiple defects in DNA repair genes may increase PARPi sensitivity, such as the 769-P cell line that harbors both SETD2 down-regulation and BAP1 mutation. We previously reported that a single 300nM DAC treatment caused significant cytotoxicity differences between SETD2 WT and SETD2-altered RCCs (15). However, a reduced dose of 100nM DAC is efficacious when combined with a low (10 nM) PARPi dose, resulting in a stabilizing role on tumor inhibition, a beneficial clinical strategy to maintain heightened anti-tumor effects and reduced cytotoxic side effects.

Even though only limited numbers of RCC cell lines were tested in this study and SETD2 KO was only performed in 786–0 cells, anti-tumor effects due to combination treatments in SETD2 deficient cell lines were shown at the molecular level both in vitro and in vivo settings. Considering our findings are consistent with previous studies regarding SETD2 function, we confirm that SETD2 is a determinant that plays a decisive role in drug sensitivity. During the in vivo experiments, we observed that blood vessels are more abundant in untreated (NT) and BMN-673 treated mouse tumors, while mice treated with DAC + BMN-673 lacked parlor. Future studies will confirm if DAC + BMN-673 combination treatments induce anti-tumor effects in vivo by decreasing abnormal tumor blood vessel generation.

Several clinical trials evaluating DAC/BMN-673, either alone or with other drugs, are under recruitment or in process, and a phase1 clinical trial of combination treatment of DAC + BMN-673 in untreated, relapsed, or refractory AML has just been completed (NCT02878785). These studies provide the foundation for our study, and we anticipate that this combination therapy will be tested in clinical trials to benefit clinical RCC patients. Although HMA treatments of solid tumors as a single agent have been inadequate, new DNA methylation inhibitors, such as GSK3685032, have been developed (60) and may show improved clinical efficacy and patient outcomes, especially combination treatment for patients with solid tumors (61).

Conclusions

RCC, especially metastatic ccRCC, has been characterized with frequent SETD2 mutations and/or down-regulated SETD2 expression. We have demonstrated that DAC and BMN-673 synergistically inhibit SETD2-deficient RCC tumors by inducing DNA damage, generating insufficient repair of DNA damage, strengthening viral mimicry, and disrupting genomic stability in vitro. This combination therapy also shows promising anti-tumor effects on SETD2-deficient RCC tumors in vivo. The extent that this combination therapy produces substantive anti-tumor effects for clinical patients requires further clinical trials and investigation.

Supplementary Material

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Significance:

SETD2 deficiency creates a vulnerable epigenetic status that is targetable using a DNA hypomethylating agent and PARP inhibitor combination to suppress renal cell carcinoma, identifying a precision medicine-based approach for SETD2-compromised cancers.

Acknowledgements

This study is supported by the Vicky Joseph Cancer Research Foundation (G.L), The Wright Foundation Trust (G.L, D.J.W., D.I.Q., and B.H.) and National Cancer Institute (R35 CA209859) (G.L.) and National Cancer Institute (P30 CA014089) (G.L., D.J.W.), the Department of Veterans Affairs (N.A.B).

Footnotes

Conflict of Interest:

G. L. is a consultant for PANGEA LABORATORY. I.S.G. is a consultant for STEBA. D. I. Quinn reports employment by Abbvie Research and Development and Honoraria for advisory board participation from Merck Sharp and Dohme, Genentech/Roche, Pfizer, EMD Serono, Astellas, Seagen and BMS. No potential conflicts of interest were disclosed by the other authors.

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Supplementary Materials

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NIHMS1931819-supplement-1.xlsx (14KB, xlsx)
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NIHMS1931819-supplement-2.xlsx (12.6KB, xlsx)
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NIHMS1931819-supplement-3.png (573.7KB, png)
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NIHMS1931819-supplement-5.png (281KB, png)
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NIHMS1931819-supplement-6.png (476.3KB, png)
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NIHMS1931819-supplement-7.docx (16.1KB, docx)

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