Cell lines and reagents
Cell lines 786O, 769P, A498 were purchased from ATCC. SLR26, CAKI1, ACHN and RXF393 were kindly supplied by the Kaelin laboratory (Dana Farber Cancer Institute). Cell lines were grown in RPMI 1640 (Gibco) supplemented with 10% FBS (Gibco), incubated at 37 °C in 5% CO2, and regularly tested for Mycoplasma spp. contamination.
The NCI-H460 cell line was purchased from ATCC. The Alt-R™ CRISPR-Cas9 System (IDT Technologies) was used to delete ERCC4. Cas9 nuclease was purchased from Horizon Discovery. The crRNA was annealed with ATTO™ 550-tracrRNA, and ribonucleoparticles (RNPs) were then assembled by adding Cas9. RNPs were delivered into cells using electroporation-based nucleofection (Lonza system). Flow cytometry was utilized to sort ATTO-550 positive single cells 24 h following nucleofection. Next, single cells were expanded and clonal populations were screened by immunoblot to identify clones with complete loss of expression of the ERCC4 protein.
In vitro drug sensitivity assays
Exponentially growing cell lines were seeded in 96-well plates (3000 cells/well) and incubated for 24 h to facilitate cell attachment. Identical cell numbers of seeded parallel isogenic lines were verified by the Celigo Imaging Cytometer after attachment. Cells were exposed to Irofulven (Cayman Chemicals) for 72 h, and cell growth was determined by the addition of PrestoBlue (Invitrogen) and incubated for 2.5 h. Cell viability was determined by using the BioTek plate reader system. Fluorescence was recorded at 560 nm/590 nm, and values were calculated based on the fluorescence intensity. IC50 values were determined by using the AAT Bioquest IC50 calculator tool. P-values were calculated using student’s t-test. P-values < 0.05 were considered statistically significant.
PTGR1 knockdown
An siRNA against PTGR1 (ON-TARGETplus; Dharmacon), shown to induce > 90% reduction of PTGR1 transcript levels over 48–72 h, or an Alexa Flour non-targeting control siRNA were transfected at 25 nM into the HMLE cell line using Lipofectamine RNAiMAX (Thermo Scientific). Cells were seeded at 3000 cells per well into a 96-well plate during reverse transfection. Following 24 h, the cells were treated with either vehicle (0.01% EtOH) or irofulven at 300 nM and 600 nM doses. Cell viability was measured after 72 h using the CellTiterGlo reagent (Promega).
Immunoblotting
Freshly harvested cells were lysed in RIPA buffer. Protein concentrations were determined by Pierce BCA™ Protein Assay Kit (Pierce). Proteins were separated via Mini Protean TGX stain free gel 4–15% (BioRad) and transferred to polyvinylidene difluoride membrane by using iBlot 2 PVDF Regular Stacks (Invitrogen) and iBlot transfer system (LifeTechnologies).
Membranes were blocked in 5% BSA solution (Sigma). Primary antibodies were diluted following the manufacturer’s instructions: anti-beta Actin, [AC15] (HRP-conjugated) ab 49,900, Abcam (1:25,000) and antiPTGR1 [EPR13451-10], ab181131, Abcam (1:1000). Signals were developed using Clarity Western ECL Substrate (BioRad) and Image Quant LAS4000 System (GEHealthCare).
NER assay
Removal of 6–4 pyrimidine-pyrimidone photoproducts (6–4PP) as a function of NER was quantified using an immunofluorescent assay. Cells were seeded on coverslips in a 12 well plate. After overnight growing, cells were irradiated with 40 J/m2 under UV lamp directly with 254 nm wavelength. Cells were fixed in cold methanol for 10 min right after UV damage or after 7 h recovery. Then cells were triton extracted (0.5% Triton X-100 in PBS) for 4 min at room temperature followed by 2 M HCL/PBS incubation at 37 °C for 15 min. After washing twice with PBS, once with 1% BSA/PBS, once with PBS, cells were incubated with 6-4PP primary antibody (NM-DND-002, 1:2000) for 45 min at 37 °C followed by incubation with secondary antibody for 30 min at 37 °C. Coverslips were then washed twice with PBS and mounted using DAPI.
Patients and cell lines
This study evaluated 389 whole exome sequenced (WES) pretreatment samples of RCC patients from the TCGA-KIRC cohort. The normal, tumor bam and vcf files were retrieved from the TCGA data portal (https://portal.gdc.cancer.gov/) for the analysis. From the TCGA data portal the vcf files for the somatic mutations from the MuTect2 pipeline were used.
Variants were collected from the DepMap portal (https://depmap.org/portal/download/) for the cancer cell line samples (DepMap version 22Q2).
Mutation calling and filtering
The application of the MuTect2 default filters (FILTER = = ”PASS”) for filtering the called mutations ensured the high accuracy of germline and somatic changes reported. Utilizing additional stringent filters on somatic samples provided the high accuracy of reported variants: TLOD ≥ 6 and NLOD ≥ 3, NORMAL.DEPTH ≥ 15 and TUMOR.DEPTH ≥ 20, TUMOR.ALT ≥ 5 and NORMAL.ALT = 0 and TUMOR.AF ≥ 0.05. Additionally, samples with less than a total of 50 variants were removed, since mutational signature extraction is less reliable when the number of mutations is fewer than 50.
After applying these filters and keeping only one sample per patient (by removing the samples with whole genome amplification) and removing the FFPE samples and samples indicated having MSI (Microsatellite Instability) using the MANTIS tool8 289 samples were further analyzed.
Intervar (version 2.0.2) was utilized to classify the variants as “Benign,” “Likely Benign,” “Uncertain Significance,” “Likely Pathogenic,” and “Pathogenic.” Deleterious mutations were defined for exonic SNVs with “Pathogenic” or “Likely Pathogenic” labels, nonsense SNV-s and indels with “Pathogenic” or “Likely Pathogenic” labels. All the ERCC gene family mutants represented in the figures are deleterious mutations.
For genotyping of the cell line samples, variants were defined as deleterious if the column “isDeleterious” was indicated as “True” in the CCLE.mutations.csv data file.
Mutational signatures
Using techniques based on non-negative matrix factorization, Alexandrov et al.9 described single base substitutions (SBS) signatures, doublet base substitution (DBS) signatures and small insertion and deletion (ID) signatures. In this study we calculated the number of ID8 signatures since we previously found this signature most significantly associated with NER deficiency10. The identified matrix of ID signatures was downloaded from https://www.synapse.org/#!Synapse:syn12025148. ID mutations in each sample were classified into 83-dimensional indel catalog using the ICAMS R package11. The resulting matrices were used in a non-negative least-squares problem to estimate the matrix of exposures to mutational processes.
The ID8 signature extraction was performed the same way on the patient and cancer cell line samples.
RNA expression analysis
RNA expression data were downloaded from the TCGA data portal (https://portal.gdc.cancer.gov/) for the patient samples, and The Fragments Per Kilobase of Transcript per Million Mapped Reads (FPKM) technique was used to normalize the data, and the data were log2-transformed using a pseudo-count thereafter.
For the cancer cell line samples, the RNA expression data were obtained from the DepMap portal (https://depmap.org/portal/) and the TPM-normalized data were log2-transformed using a pseudo-count. For comparison with the TCGA-KIRC PTGR1 FPKM values, cell-line expression data in FPKM were downloaded from the CellMiner website (https://discover.nci.nih.gov/cellminer/).
Ethics approval
The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Translational relevance
DNA repair deficiencies can be therapeutically targeted by synthetic lethal–based strategies in cancer. However, clear cell renal cell carcinoma (ccRCC) has not benefitted from this therapeutic approach due to a lack of evidence for the presence of specific DNA repair pathway deficiencies. Here, we demonstrate that ccRCC harbors a therapeutically targetable DNA repair pathway aberration, nucleotide excision repair (NER) deficiency. ccRCC cell lines displayed robust signs of NER deficiency as determined by functional assays and some of these cell lines also displayed NER deficiency induced mutational signatures. These cell lines are also sensitive to irofulven, an abandoned anticancer agent that creates DNA lesions which can only be repaired by the NER pathway. We estimate that up to 10% of ccRCC cases may respond to NER-directed therapy with irofulven based on NER deficiency associated mutational signatures and PTGR1 expression levels, which is an enzyme required to activate irofulven.