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Sequential Administration of XPO1 and ATR Inhibitors Enhances Therapeutic Response in TP53-mutated Colorectal Cancer

Open AccessPublished:March 18, 2021DOI:https://doi.org/10.1053/j.gastro.2021.03.022

      Background & Aims

      Understanding the mechanisms by which tumors adapt to therapy is critical for developing effective combination therapeutic approaches to improve clinical outcomes for patients with cancer.

      Methods

      To identify promising and clinically actionable targets for managing colorectal cancer (CRC), we conducted a patient-centered functional genomics platform that includes approximately 200 genes and paired this with a high-throughput drug screen that includes 262 compounds in four patient-derived xenografts (PDXs) from patients with CRC.

      Results

      Both screening methods identified exportin 1 (XPO1) inhibitors as drivers of DNA damage-induced lethality in CRC. Molecular characterization of the cellular response to XPO1 inhibition uncovered an adaptive mechanism that limited the duration of response in TP53-mutated, but not in TP53-wild-type CRC models. Comprehensive proteomic and transcriptomic characterization revealed that the ATM/ATR-CHK1/2 axes were selectively engaged in TP53-mutant CRC cells upon XPO1 inhibitor treatment and that this response was required for adapting to therapy and escaping cell death. Administration of KPT-8602, an XPO1 inhibitor, followed by AZD-6738, an ATR inhibitor, resulted in dramatic antitumor effects and prolonged survival in TP53-mutant models of CRC.

      Conclusions

      Our findings anticipate tremendous therapeutic benefit and support the further evaluation of XPO1 inhibitors, especially in combination with DNA damage checkpoint inhibitors, to elicit an enduring clinical response in patients with CRC harboring TP53 mutations.

      Graphical abstract

      Keywords

      Abbreviations used in this paper:

      ATM (ataxia telangiectasia mutated), ATR (ataxia telangiectasia and Rad3-related), AUCn (area under curve normalized), Chk1/2 (checkpoint kinase 1 and 2), CDK4/6 (cyclin dependent kinase 4/6), CRC (colorectal cancer), DDR (DNA damage response), dMMR (deficient DNA mismatch repair), EGFR (epidermal growth factor receptor), fa (fraction affected), FBS (fetal bovine serum), FDAome (Food and Drug Administration-approved drug targets), G (growth), ICB (immune checkpoint blockade), M (mitosis), MSE (mean-squared error), p (phosphorylated), PDX (patient-derived xenograft), RSA (redundant shRNA activity), S (synthesis), shRNA (short hairpin RNA), TGI (tumor growth inhibition), TSPs (tumor suppressor proteins), XPO1 (exportin 1)
      See Covering the Cover synopsis on page 1; See editorial on page 31.

       Background and Context

      Approved targeted therapies to achieve enduring therapeutic responses in patients with colorectal cancer (CRC) are limited (eg, epidermal growth factor receptor inhibitors in KRAS–wild-type tumors).

       New Findings

      Sequential treatment with an exportin 1 (XPO1) inhibitor, followed by an ataxia telangiectasia and Rad3-related (ATR) inhibitor, induces massive DNA damage in CRCs harboring TP53 mutations, thereby shrinking tumor burden and prolonging survival in preclinical models.

       Limitations

      Lack of experiments assessing the effects of XPO1-ATR combination treatment in an immunocompetent system limits the characterization of the therapeutic response as well as the evaluation of potential interactive effects with immunotherapy.

       Impact

      These successful results with XPO1 and ATR inhibitors, which have known safety profiles, should provide the foundation for initiating clinical trials for patients with CRC with genomically defined TP53 mutations.
      Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality.
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      Cancer statistics, 2021.
      Tumor molecular profiling initiatives, including The Cancer Genome Atlas and International Cancer Genome Consortium efforts, through advanced sequencing technologies and data analyses, have identified clinically actionable alterations in genes and pathways in a broad range of cancer types, including CRC.
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      Yet, the functional implications of these genetic lesions in CRC are incompletely understood, complicating the clinical positioning of available targeted agents. For instance, a recent trial failed to demonstrate clinical benefit of a BRAF inhibitor in CRC patients with BRAFV600E-mutant tumors.
      • Kopetz S.
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      Phase II pilot study of vemurafenib in patients with metastatic BRAF-mutated colorectal cancer.
      Similarly, comprehensive functional genomics screens conducted both in vitro and in vivo have identified numerous potential drug targets
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      • et al.
      In vivo genetic screens of patient-derived tumors revealed unexpected frailty of the transformed phenotype.
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      A functional cancer genomics screen identifies a druggable synthetic lethal interaction between MSH3 and PRKDC.
      • Carugo A.
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      In vivo functional platform targeting patient-derived xenografts identifies WDR5-Myc association as a critical determinant of pancreatic cancer.
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      • et al.
      In vivo loss-of-function screens identify KPNB1 as a new druggable oncogene in epithelial ovarian cancer.
      ; however, the translation of screening outputs to robustly validated targets and the development of clinical therapeutics remains slow and resource intensive. To accelerate the identification of clinically actionable therapeutic opportunities in CRC, we combined in vivo functional genomics with in vitro drug screening in matched patient-derived tumor cell cultures and xenografts.
      We identified exportin 1 (XPO1), a eukaryotic nuclear-cytoplasmic exporter and a validated drug target in multiple cancer indications,
      • Kau T.R.
      • Way J.C.
      • Silver P.A.
      Nuclear transport and cancer: from mechanism to intervention.
      • Kim J.
      • McMillan E.
      • Kim H.S.
      • et al.
      XPO1-dependent nuclear export is a druggable vulnerability in KRAS-mutant lung cancer.
      • Lapalombella R.
      • Sun Q.
      • Williams K.
      • et al.
      Selective inhibitors of nuclear export show that CRM1/XPO1 is a target in chronic lymphocytic leukemia.
      as a novel therapeutic target in CRC. Recent preclinical and clinical studies with XPO1 inhibitors, KPT-330 and KPT-8602, have confirmed their potent activity in different cancer types.
      • Conforti F.
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      • et al.
      Therapeutic effects of XPO1 inhibition in thymic epithelial tumors.
      • Vercruysse T.
      • De Bie J.
      • Neggers J.E.
      • et al.
      The second-generation exportin-1 inhibitor KPT-8602 demonstrates potent activity against acute lymphoblastic leukemia.
      • Chen Y.
      • Camacho S.C.
      • Silvers T.R.
      • et al.
      Inhibition of the nuclear export receptor XPO1 as a therapeutic target for platinum-resistant ovarian cancer.
      • Abdul Razak A.R.
      • Mau-Soerensen M.
      • Gabrail N.Y.
      • et al.
      First-in-class, first-in-human phase I study of selinexor, a selective inhibitor of nuclear export, in patients with advanced solid tumors.
      KPT-330 is now approved for treatment of multiple myeloma and, more recently, diffuse large B-cell lymphoma.
      XPO1 inhibitor approved for multiple myeloma.
      Tumor plasticity and adaptation to targeted therapies contribute substantially to disease relapse/progression.
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      Evolution of the cancer genome.
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      Tumor adaptation and resistance to RAF inhibitors.
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      Cancer cell adaptation to chemotherapy.
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      • Liotta L.
      • et al.
      Mechanism of cell adaptation: when and how do cancer cells develop chemoresistance?.
      • Chandarlapaty S.
      Negative feedback and adaptive resistance to the targeted therapy of cancer.
      Our characterization of tumor response to XPO1 inhibitor-induced DNA damage uncovered that TP53 wild-type tumor cells recovered from XPO1 inhibitor treatment, likely due to arrest in the growth (G)1/synthesis (S) phase of the cell division cycle that facilitated DNA repair. In contrast, TP53-mutant tumors, which have a defective G1 checkpoint, experienced severe DNA damage accumulation and relied on activation of the G2/mitosis (M) DNA damage checkpoint via the ataxia telangiectasia mutated (ATM)/ataxia telangiectasia and Rad3-related (ATR)- checkpoint kinase 1 and 2 (Chk1/2) axes. Consistently, sequential administration of KPT-8602, followed by the ATR inhibitor, AZD-6738, yielded a synergistic survival benefit in CRC patient-derived xenograft (PDX) models harboring TP53 mutations. Moreover, sequential treatment of XPO1 inhibitor-treated tumors with the cyclin dependent kinase 4/6 (CDK4/6) inhibitor, palbociclib, resulted in robust antitumor effects independent of TP53 mutational status.
      Together, our data support the study of XPO1 inhibitor therapy alone and in combination with other DNA damage response (DDR)- and cell cycle-targeting drugs in subpopulations of patients with CRC.

      Materials and Methods

       In Vivo Short Hairpin RNA Screens

      A custom library targeting 196 gene targets of United States Food and Drug Administration-approved targeted therapies was constructed using chip-based oligonucleotide synthesis and cloned into the pRSI16 lentiviral vector as a pool (Cellecta, Mountain View, CA) PDX1 cells were infected using a multiplicity of infection = 0.3 total transducing units/cell. For the human PDX experiments, injections consisted of 3 × 106 cells to ensure coverage of 1500 cells/barcode. Genomic DNA extraction, barcode amplification, and preparation of sequencing libraries were performed according to our previously published protocol.
      • Carugo A.
      • Genovese G.
      • Seth S.
      • et al.
      In vivo functional platform targeting patient-derived xenografts identifies WDR5-Myc association as a critical determinant of pancreatic cancer.

       Short Hairpin RNA Screen Hit Analysis

      Illumina-generated sequences (Illumina, San Diego, CA) were processed using CASAVA 1.8.2 (Illumina), and resulting reads were processed using our in-house pipeline, as previously described.
      • Carugo A.
      • Genovese G.
      • Seth S.
      • et al.
      In vivo functional platform targeting patient-derived xenografts identifies WDR5-Myc association as a critical determinant of pancreatic cancer.
      The log2 fold-change for each sample was calculated by comparing tumors to the reference pellet. A summary measure per condition was derived using median of quantile transformed log2 fold-change across replicates. Thereafter, a modified version of the redundant short hairpin RNA (shRNA) activity algorithm was used to derive a gene-level summary measure per condition.
      • Birmingham A.
      • Selfors L.M.
      • Forster T.
      • et al.
      Statistical methods for analysis of high-throughput RNA interference screens.

       High-Throughput Compound Screens

      Screening of 262 drugs was accomplished at Texas A&M Health Science Center, Institute of Bioscience and Technology, Gulf Coast Consortia (GCC) Screening Core. This library consisted of 150 custom clinical drugs and 112 National Cancer Institute Approved Oncology drugs (NCI_AOD5). The process is explained in details in the Supplementary Methods and on their website in detail (https://ibt.tamu.edu/cores/high-throughput/index.html).
      • Kalu N.N.
      • Mazumdar T.
      • Peng S.
      • et al.
      Comprehensive pharmacogenomic profiling of human papillomavirus-positive and -negative squamous cell carcinoma identifies sensitivity to aurora kinase inhibition in KMT2D mutants.
      All 4 CRC PDX lines were screened after optimization.

       High-Throughput Dose-Response

      Dose-response curves were based on a fraction affected (fa) calculation: fa = 1 − Ti/C; where Ti is the cell count (or biochemical viability measurement) in the drug test well, and C is the cell count (or biochemical viability measurement) for vehicle-treated controls, with both measurements taken at the end of the assay.
      After the drug concentration values have been transformed to their base-10 logarithm values, a 4-parameter logistic (Hill) equation is fit to the data, and the following parameters are estimated:
      • 1.
        E0—the lowest value of fa, indicating the minimum effect of the drug.
      • 2.
        Emax—the highest value of fa, indicating the maximum effect of the drug.
      • 3.
        Log(EC50)—the base-10 logarithm of the 50% effective concentration at which an effect of (Emax − E0)/2 is seen.
      • 4.
        Slope—The slope of the transition region of the dose/response curve. Higher values indicate drugs that transition from having little effect to having a significant effect over a shorter range of doses (ie, a steeper slope).
      The area under the fitted curve (AUC) was calculated using numerical integration then normalized to a value between 0 and 1 (AUCn). The mean-squared error (MSE) of all points relative to the fitted curve was also calculated. Classification of drug responses was defined as:
      • Class 1: AUCn ≥0.7, MSE <0.01
      • Class 2: AUCn ≥0.4, MSE < 0.025
      • Class 3: AUCn >0.1, MSE <0.05
      • Class 4: All other drugs that fail to pass the criteria for class 1 through 3

       Human Colon Cell Lines and Culture Conditions

      All cell lines were kept at 37°C in a humidified atmosphere with 5% carbon dioxide. SNU-C5 cells were cultured in RPMI-1640 (Thermo Fisher Scientific, Waltham, MA) with 10% fetal bovine serum (FBS) (Sigma-Aldrich, St. Louis, MO). SNU-61 cells were cultured in RPMI-1640 with HEPES supplemented with 10% heat-inactivated FBS (Thermo Fisher Scientific, Waltham, MA). Human colon cell lines and all other colon cancer cell lines were cultured in Dulbecco’s modified Eagle medium/F12 (Thermo Fisher Scientific, Waltham, MA) supplemented with 10% FBS. All cell lines were tested for mycoplasma contamination and fingerprinted. Mutation profiles for CRC-relevant cancer genes (http://www.cancer-genes.org/; false discovery rate <0.01) were obtained from the Cancer Cell Line Encyclopedia (CCLE) (Supplementary Table 1). Mutations for WiDr and COLO320DM are not reported because they are derivatives of HT29 and COLO320, respectively.

       In Vitro Treatments

       Dose-Response Studies

      Cell viability was assessed by measuring adenosine 5ʹ-triphosphate content using the CellTiter-Glo luminescent assay (Promega, Madison, WI) in cells plated in black 96-well plates for 96 hours, with or without drug treatment. The 50% effective concentration values were calculated with Prism (GraphPad Software, San Diego, CA) by means of a 4-parameter, nonlinear regression analysis. Cytotoxicity was determined at the different time points and in the different cell lines to match cytotoxicity measurements with a given assay

       Wash-Out/Drug Combination Studies

      Cells were exposed to dimethyl sulfoxide or KPT-330 100 nmol/L for 48 hours. Cells were collected and replated on 10-cm or 24-well plates with fresh medium and kept in culture for 300 hours. For drug combination studies, cells previously treated with XPO1 inhibitor were replated on 96-well plates and treated with palbociclib or AZD-6738 at different doses for 96 hours.

       Tumor Engraftment

      All PDX models were generated and obtained from the laboratory of Dr Scott Kopetz at University of Texas MD Anderson Cancer Center.
      • Katsiampoura A.
      • Raghav K.
      • Jiang Z.Q.
      • et al.
      Modeling of patient-derived xenografts in colorectal cancer.
      Rodent care and housing were in accordance with institutional guidelines and regulations and with protocols approved by the Institutional Animal Care and Use Committee.
      For PDX-derived cell implantation, cells in log phase were trypsinized and resuspended as 2.0 × 107 cells/mL in 1:1 PBS/Matrigel (BD Biosciences, San Jose, CA). For PDX preclinical studies, small tumor fragments (∼0.1 cm3) were collected from first- or second-generation PDXs and transplanted into the right flank of recipient NSG mice. Animals were randomized to treatment based on tumor volume, and tumor samples were collected when they reached 1500 mm3 or when the tumor reached protocol limits with respect to ulceration.

       In Vivo Drug Treatments

      Mice were dosed orally once daily with dimethyl sulfoxide (vehicle), KPT-8602, AZD-6738, or with palbociclib for 5 days on/2 days off cycles. Drug dose was scaled to body weights of individual animals for final dosing volumes for KPT-8602 of 5, 10, and 15 mL/kg, for AZD-6738 of 50 mL/kg, and for palbociclib of 100 mL/kg. 5-Fluorouracil was dosed intraperitoneally twice weekly scaled to a volume of 25 mL/kg. For serial combination studies, mice were treated with each compound for 2 weeks. Mice were provided water and LabDiet 5053 chow (LabDiet, St. Louis, MO) ad libitum.

       Statistical Analysis

      Data are presented as the mean ± standard deviation of biological replicates. Statistical analyses were performed using a 2-tailed Student t test. Survival experiments were analyzed with a log-rank (Mantel-Cox) test and are expressed as Kaplan-Meier survival curves.

      Results

       Integrated Genetic and Drug Screening Platforms Identify Targeted Therapies for Colorectal Cancer

      To identify therapeutic targets in CRC, we integrated functional genomics and drug screens in matched patient-derived tumor cells and PDXs (Figure 1A). In vivo screens in PDX tumors were conducted using an shRNA library targeting 196 genes known to encode targets of drugs approved by the United States Food and Drug Administration (FDA) or under clinical investigation (FDAome; 10 independent shRNAs/gene) (Figure 1A and Supplementary Table 2). Concurrently and using the same models, we screened a custom clinical drug library composed of 262 clinically available compounds in vitro in 2-dimensional (2D) array format (CellTiter-Glo) (Figure 1A and Supplementary Table 3). These orthogonal approaches identified genetic drivers essential for in vivo tumor maintenance with high translational potential in clinically relevant models.
      Figure thumbnail gr1
      Figure 1Integrated genomic and pharmacologic screening using CRC PDX models to identify therapeutic opportunities. (A) Schematic of orthogonal screening platform: in vivo shRNA screens in CRC PDXs using a pooled genetic library targeting products of 196 FDA-approved or under clinical investigation genes was combined with in vitro high-throughput (HT) compound screens using a Custom Clinical National Cancer Institute (NCI) library including 262 compounds. (B) Genetic landscape of 4 CRC PDXs in the in vitro and in vivo screening pipeline. Of the 4 models, 3 displayed KRAS mutations (C0999, B1011, and C1047), and 1 harbored a BRAF/PIK3CA mutation (B1003). (C) Density distribution of barcodes (shRNA) for transduced PDX cells (references) and 3 in vivo tumor replicates (Tx 1, 2, and 3) from 4 CRC PDXs infected with the FDAome shRNA lentiviral library. (D) Fraction of scoring genes in the library. Gene-rank analysis highlighting behavior of EGFR, AKT1, mTOR, and PIK3CA hits in the FDAome in vivo screens executed in 4 independent CRC PDX models: C0999, B1003, B1011, and C1047 (RSA, redundant shRNA activity, logP). (E) Schematic of the HT drug screen workflow and heat map of the 30 most potent compounds and their AUCs for the 4 PDX models’ responses to drug exposure in vitro. Results were classified into 4 groups calculated by the AUCn (class 1: AUCn ≥0.7; class 2: AUCn ≥0.4; class 3: AUCn >0.1; class 4: AUCn <0.1). (F) Top-scoring genes and corresponding compounds were prioritized for investigation by integrating the orthogonal screening results with currently available clinical trial information in CRC.
      Screens were conducted in 4 CRC PDX models and PDX-derived cell cultures (3 KRAS mutants: C0999, B1011 and C1047; 1 BRAF mutant: B1003) (Figure 1B and Supplementary Figure 1A) were expanded for a maximum of 3 passages from excision. Each sample was molecularly and histologically characterized to confirm similarity with the tumors of origin.
      In vivo screens used our previously described 2-step method for in vivo loss-of-function pooled shRNA screening. Briefly, to determine the engraftment efficiency of each CRC PDX to ensure adequate coverage of the molecular complexity of the library,
      • Bossi D.
      • Cicalese A.
      • Dellino G.I.
      • et al.
      In vivo genetic screens of patient-derived tumors revealed unexpected frailty of the transformed phenotype.
      • Dietlein F.
      • Thelen L.
      • Jokic M.
      • et al.
      A functional cancer genomics screen identifies a druggable synthetic lethal interaction between MSH3 and PRKDC.
      • Carugo A.
      • Genovese G.
      • Seth S.
      • et al.
      In vivo functional platform targeting patient-derived xenografts identifies WDR5-Myc association as a critical determinant of pancreatic cancer.
      early-passage cultures were transduced with a nontargeting 2.7K molecular barcode library (Empty BC) to “tag” individual cells. Barcode representation was then analyzed by deep sequencing and compared between transduced reference cells (PDX1 cells) and the barcoded cell population of tumors established in NSG mice (PDX2 tumors). Three models for which we confirmed statistically comparable barcode representation between reference PDX1 cells and PDX2 tumors, as well as among PDX2 tumor replicates (Supplementary Figure 1B), were selected for screening. These findings support that complex libraries can be maintained in vivo in our CRC PDX models.
      Again following our previously described protocol, the selected PDX models were screened using the FDAome library. Deep sequencing analysis identified barcodes depleted in the tumor vs the reference cell population, indicating the associated shRNAs conferred a selective growth disadvantage (Figure 1C and Supplementary Figure 1C). In all models, positive (PSMA1 and RPL30) and negative (luciferase) controls displayed significant separation, confirming the high quality of the screens (Supplementary Figure 1D).
      Next, we leveraged a modified redundant shRNA activity analysis to identify “hits” (top-scoring genes)
      • Birmingham A.
      • Selfors L.M.
      • Forster T.
      • et al.
      Statistical methods for analysis of high-throughput RNA interference screens.
      (Figure 1D and Supplementary Table 4). Epidermal growth factor receptor (EGFR) emerged as a top hit in the wild-type KRAS B1003 model but not in mutant KRAS models (C0999, B11011, C1047), consistent with clinical findings where KRAS mutation is a negative predictor of response to EGFR blockade in CRCs. PIK3CA, AKT1, and mTOR emerged as top hits only in the PIK3CA-mutant model (B1003), but not in the PIK3CA wild-type context. Our results demonstrate strong correlation between model genotypes and functional phenotypes, supporting the robustness of in vivo screening to uncover genetic drivers.
      To prioritize the genetic results with the highest chances of clinical impact, we conducted a high-throughput in vitro screening of drug compounds (Figure 1E). Tumor model response to drug exposure was classified into 4 groups defined by the AUCn (class 1: AUCn ≥0.7; class 2: AUCn ≥0.4; class 3: AUCn >0.1; class 4: AUCn <0.1). Unsurprisingly, the most effective drugs (class 1) were classical cytotoxic agents, which were similarly efficacious across all models (Figure 1E and Supplementary Table 5). Among targeted therapies, inhibitors targeting the proteasome, PLK1, HDAC, XPO1, CDK4/6, and mTOR scored as the most effective. In vitro drug screening results correlated well with the genetic screening, in which PSMD1, PLK1, HDAC2/3, XPO1, CDK4/6, and mTOR were identified as top-scoring hits in at least 2 of the 4 CRC models (Figure 1F). Excluding XPO1, each of these is a well-known target in CRC currently under clinical investigation,
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      Phase II pharmacodynamic trial of palbociclib in patients with KRAS mutant colorectal cancer.
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      A phase I, dose-escalation study of the novel polo-like kinase inhibitor volasertib (BI 6727) in patients with advanced solid tumours.
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      demonstrating that our dual-screening strategy successfully captured essential, clinically relevant targets in CRC. XPO1 was prioritized for further study as a potentially novel therapeutic target in CRC.

       Selective XPO1 Inhibition Induces DNA Damage-Dependent Lethality in Colorectal Cancer

      Exportin 1 (XPO1/CRM1) is a major nuclear-cytoplasmic exporter in eukaryotes that transports proteins and RNAs from the nucleus to the cytoplasm. Upregulation of XPO1 expression has been identified in some cancers, resulting in dysregulation of cargo proteins in the nuclear and cytoplasmic compartments.
      • Kau T.R.
      • Way J.C.
      • Silver P.A.
      Nuclear transport and cancer: from mechanism to intervention.
      ,
      • Turner J.G.
      • Dawson J.
      • Sullivan D.M.
      Nuclear export of proteins and drug resistance in cancer.
      In The Cancer Genome Atlas data set, XPO1 expression is upregulated in CRC vs normal tissue, and high expression of XPO1 correlated with poor prognosis (Supplementary Figure 2A and B; GSE17536).
      • Cancer Genome Atlas N.
      Comprehensive molecular characterization of human colon and rectal cancer.
      ,
      GTEx Consortium
      The Genotype-Tissue Expression (GTEx) project.
      Consistently, expression of XPO1 in all 4 CRC PDX models used in our screens and in established human CRC cell lines from the American Type Culture Collection was elevated compared with normal colon epithelial cells (Figure 2A).
      Figure thumbnail gr2
      Figure 2Selective XPO1 inhibition drives DNA damage-dependent lethality in CRC.
      (A) XPO1 expression level across CRC models (black; cell lines and PDX-derived primary cultures) and colon epithelial cells (light blue). (B) Knockdown efficiency of XPO1 using 2 independent shRNAs in the B1011 PDX-derived cell line compared with 2 short hairpin nontargeting (shNT) RNA controls. (C) Colony formation assay in C0999, B1003, and B1011 cells expressing shNT or XPO1-targeting shRNA. (D) Sensitivity to KPT-330 across a panel of CRC models (cell lines and PDX-derived primary cultures) and colon epithelial cells (light blue) based on adenosine 5ʹ-triphosphate viability assay (96 hours). (E) Expression of indicated proteins in CRC (black) or normal colon epithelial (light blue) cells treated with KPT-330 at indicated doses for 24 hours. c-, cleaved p-, phospho. (F) Nuclear fraction of protein expression in B1011 PDX-derived cells treated with KPT-330 at the indicated dose for 24 hours. 5-Fluorouracil (FU) serves as the positive control. (G) Immunofluorescence staining of p-H2A.X and 4′,6-diamidino-2-phenylindole (DAPI) in B1011 PDX-derived primary cells treated with dimethyl sulfoxide (DMSO) or KPT-330 at indicated doses for 24 hours. (H) Fluorescence-activated cell sorter analysis for cell-cycle (bromodeoxyuridine [BrdU] incorporation) and DNA damage accumulation (p-H2A.X). β-Actin and histone H3 serve as loading controls in Western blot analyses. Representative image from 3 independent experiments is shown. All data are mean ± standard deviation of biological replicates (n = 3 each). All experiments were repeated 3 times.
      KPT-330 (selinexor) and KPT-8602 (eltanexor) are potent and specific XPO1 inhibitors that induce apoptosis upon accumulation of cargo proteins in the nucleus.
      • Kau T.R.
      • Way J.C.
      • Silver P.A.
      Nuclear transport and cancer: from mechanism to intervention.
      ,
      • Kim J.
      • McMillan E.
      • Kim H.S.
      • et al.
      XPO1-dependent nuclear export is a druggable vulnerability in KRAS-mutant lung cancer.
      ,
      • Vercruysse T.
      • De Bie J.
      • Neggers J.E.
      • et al.
      The second-generation exportin-1 inhibitor KPT-8602 demonstrates potent activity against acute lymphoblastic leukemia.
      In a recent early-phase clinical trial of KPT-330 in advanced solid tumors, biological response was observed at tolerated doses.
      • Abdul Razak A.R.
      • Mau-Soerensen M.
      • Gabrail N.Y.
      • et al.
      First-in-class, first-in-human phase I study of selinexor, a selective inhibitor of nuclear export, in patients with advanced solid tumors.
      Here we aim to evaluate the efficacy of XPO1 inhibitor therapy in CRC and identify strategies to optimize clinical benefit.
      Based on the Project DRIVE (deep RNAi interrogation of viability effects in cancer) data set, XPO1 is an essential gene in ∼80% of cancer cell lines (Supplementary Figure 2C).
      • McDonald 3rd, E.R.
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      • Schlabach M.R.
      • et al.
      Project DRIVE: a compendium of cancer dependencies and synthetic lethal relationships uncovered by large-scale, deep RNAi screening.
      We confirmed that genetic or pharmacologic XPO1 inhibition impaired cell growth in 2D colony formation and 3D assays CRC PDX-derived cell cultures and established cell line models, and we observed markedly attenuated effects in normal colon epithelial cell lines (Figure 2B–E and Supplementary Figure 2D). In PDX-derived cultures, increasing KPT-330 concentration correlated with increased p53 protein levels in the nucleus, whereas XPO1 as well as DNA damage repair proteins RAD51 and RAD50 decreased (Figure 2F and G and Supplementary Figure 2E–G). Consistently, phosphorylated (p)-H2A.X levels, indicative of DNA damage, increased in a dose-dependent manner, leading to accumulation of cells in sub-G0/G1 and a reduced number of cells in G2/M (Figure 2H and Supplementary Figure 2H). The abundance of MSH and MLH, which are frequently dysregulated in CRC, was not affected by XPO1 inhibition, suggesting that XPO1 inhibition affects only a subset of DDR genes (Supplementary Figure 2E). These data indicate that XPO1 inhibition affects expression of specific DDR genes in CRC, leading to cell cycle arrest and DNA damage accumulation.

       XPO1 Inhibition Induces TP53-Independent DNA Damage, While Drug Recovery Depends on TP53 Mutational Status

      TP53 mutations have been identified in 40% to 50% of sporadic CRCs, and TP53 mutational status is a relevant prognostic marker for patients with CRC.
      • Lopez I.
      • L PO
      • Tucci P.
      • et al.
      Different mutation profiles associated to P53 accumulation in colorectal cancer.
      • Baker S.J.
      • Fearon E.R.
      • Nigro J.M.
      • et al.
      Chromosome 17 deletions and p53 gene mutations in colorectal carcinomas.
      • Li X.L.
      • Zhou J.
      • Chen Z.R.
      • et al.
      P53 mutations in colorectal cancer-molecular pathogenesis and pharmacological reactivation.
      Based on our finding of increased DNA damage and cell cycle defects in XPO1-inhibited cell cultures, we hypothesized that dysregulation of p53 may sensitize CRC cells to XPO1 inhibition. To test this, we evaluated the response of TP53-null isogenic pairs of HCT116
      • Jallepalli P.V.
      • Lengauer C.
      • Vogelstein B.
      • et al.
      The Chk2 tumor suppressor is not required for p53 responses in human cancer cells.
      and RKO
      • Sur S.
      • Pagliarini R.
      • Bunz F.
      • et al.
      A panel of isogenic human cancer cells suggests a therapeutic approach for cancers with inactivated p53.
      cell lines to KPT-330 treatment. KPT-330 induced apoptosis and DNA damage independent of TP53 status (Figure 3A–C and Supplementary Figure 3A–B). Similarly, all tested CRC PDX-derived models showed acute sensitivity to XPO1 inhibition irrespective of their TP53 status (Figure 3D, Figure 2D, and Supplementary Figure 3C). To study recovery after KPT-330 treatment, 2 cell lines carrying mutant TP53 R273H (HT29 and WiDr) were exposed to KPT-330 for 48 hours and then allowed to recover until they reached confluence. Live-cell analysis revealed delayed recovery in TP53 wild-type models compared with vehicle-treated control cultures, whereas TP53-mutant cell lines exposed to KPT-330 recovered similarly to vehicle-treated controls (Figure 4A). Similar results were obtained in 2 additional CRC TP53 R248W cell lines (COLO320DM and SNU-C5) and the 1e TP53 R175H (SNU-61) cell line (Supplementary Figure 4A).
      Figure thumbnail gr3
      Figure 3Selective XPO1 inhibition induces DNA damage and apoptosis independent of TP53 status in CRC. (A) Sensitivity to KPT-330 in HCT116 (upper panel) and RKO (lower panel) TP53 isogenic pairs based on adenosine 5′ triphosphate (ATP) viability assay (96 hours). wt, wild-type. Protein expression in (B) HCT116 and (C) RKO TP53 isogenic pairs treated with KPT-330 at the indicated dose for 24 hours. c-, cleaved p-, phospho. (D) Four CRC PDX-derived cell lines were treated with KPT-330 or KPT-8602 at the indicated concentration for 96 hours, and viability was assessed based on ATP activity; 50% inhibitory concentration values are shown on the side. Vinculin serves as loading control in Western blot analyses. Representative image from 3 independent experiments is shown. All data are mean ± standard deviation of biological replicates (n = 3 each). All experiments were repeated 3 times.
      Figure thumbnail gr4
      Figure 4Differential TP53-dependent adaptation to XPO1 inhibition in CRC. (A) TP53 wild-type (wt; RKO and SW48) and mutant (mut; HT29 and WiDr) cells were treated with dimethyl sulfoxide (DMSO) or KPT-330 (100 nmol/L) for 48 hours. Then, drugs were washed out and cells reseeded onto 24-well plates. Confluence was monitored by Incucyte (Essen BioScience, Inc, Ann Arbor, MI) to evaluate the recovery dynamics. (B) TP53 wild-type (RKO and SW48) and mutant (HT29 and WiDr) cells were treated with DMSO or KPT-330 (100 nmol/L) for 48 hours. Then, drugs were washed out and protein expression analyzed by Western blotting at the time indicated after wash out (red box, DDR proteins; green box, Rb). c-, cleaved; p-, phospho. (C) Sensitivity to KPT-330, followed by AZD-6738 or palbociclib, in TP53 wild-type (RKO and SW48) and mutant (HT29 and WiDr) cells (n = 3). All of the cells were treated with KPT-330 (100 nmol/L) for 48 hours, followed by wash out and reseeding onto 24-well plates. Cells were then treated with DMSO, AZD-6738 (1 μmol/L) or palbociclib (1 μmol/L). Confluence was monitored by Incucyte to evaluate recovery dynamics during the second treatment. (D) Heat map of normalized confluence (mean of 3 replicates) at 144 hours for TP53 wild-type (RKO and SW48) and mutant (HT29, WiDr, COLO320DM, SNU-C5, SNU-61) CRC cells treated with KPT-330 (100 nmol/L), followed by DMSO, AZD-6738 (1 μmol/L), or palbociclib (1 μmol/L). Vinculin serves as loading control in Western blot analyses. A representative image from 3 independent experiments is shown. All data are mean ± standard deviation of biological replicates (n = 3 each). All experiments were repeated 3 times.
      Reverse-phase protein array analysis across a time course of recovery identified key cell cycle regulatory proteins, including PLK1, cyclin B1, CDK1, and WEE1, that were consistently upregulated in all cell lines after XPO1 inhibitor treatment (Supplementary Figure 3D and Supplementary Table 6), suggesting that all reentered the cell cycle. In contrast, DDR proteins were enriched more in TP53-mutant vs –wild-type cell lines after recovery (Supplementary Figure 3D and Supplementary Table 6). Immunoblot analysis confirmed increased phosphorylation of ATM, ATR, and activation of their downstream substrates CHK1, CHK2, and BRCA1 during recovery from XPO1 inhibition exclusively in TP53-mutant cell lines, suggesting that these cells activated the G2/M checkpoint to compensate for the defective G1 checkpoint (Figure 4B and Supplementary Figure 4B). A similar dependency was previously observed in G1 checkpoint-defective neuroblastoma cells.
      • Xu H.
      • Cheung I.Y.
      • Wei X.X.
      • et al.
      Checkpoint kinase inhibitor synergizes with DNA-damaging agents in G1 checkpoint-defective neuroblastoma.
      To test whether the enhanced activation of the G2/M checkpoint in TP53-mutant cell lines may be therapeutically exploited, we treated cells with KPT-330 for 48 hours, followed by wash out and treatment with the ATR inhibitor, AZD-6738. As anticipated, AZD-6738 profoundly inhibited recovery from KPT-330 treatment specifically in the TP53-mutant context, including in models harboring each of the 3 most frequent TP53 mutations in CRC (R273H, R248W, and R175H),
      • Li H.
      • Zhang J.
      • Tong J.H.M.
      • et al.
      Targeting the oncogenic p53 mutants in colorectal cancer and other solid tumors.
      with minimal impact observed in wild-type TP53 models (Figure 4C and D and Supplementary Figure 4C). Consistent with our reverse-phase protein array profiling data and mechanistic hypothesis, sequential treatment with KPT-330, followed by the CDK4/6 inhibitor, palbociclib, showed significant antitumor activity across all models, independent of TP53 status (Figure 4C and D and Supplementary Figure 4C).
      Our findings support that adaptation to XPO1 inhibition requires restart of the cell cycle machinery and that, exclusively in the TP53-mutant context, activation of ATM/ATR signaling is required to cope with accumulating DNA damage.

       Pharmacologic XPO1 Inhibition in Serial Combination With a Selective ATR Inhibitor Has Potent Antitumor Activity In Vivo

      In anticipation of XPO1 inhibitor clinical studies in CRC, we selected KPT-8602 (eltanexor), a second-generation XPO1 inhibitor with diminished blood-brain barrier penetration and fewer adverse effects that might limit treatment at effective doses.
      • Hing Z.A.
      • Fung H.Y.
      • Ranganathan P.
      • et al.
      Next-generation XPO1 inhibitor shows improved efficacy and in vivo tolerability in hematological malignancies.
      ,
      • Etchin J.
      • Berezovskaya A.
      • Conway A.S.
      • et al.
      KPT-8602, a second-generation inhibitor of XPO1-mediated nuclear export, is well tolerated and highly active against AML blasts and leukemia-initiating cells.
      KPT-8602 behaved similarly to KPT-330 in CRC models and normal colon epithelial cells in vitro, with potent antiproliferative activity observed solely in tumor cells (Figure 3D and Supplementary Figure 3C). In mice bearing tumors derived from B1011 cells (TP53-mutant CRC PDX) KPT-8602 15 mg/kg dosed on a 5 days on/2 days off schedule
      • Vercruysse T.
      • De Bie J.
      • Neggers J.E.
      • et al.
      The second-generation exportin-1 inhibitor KPT-8602 demonstrates potent activity against acute lymphoblastic leukemia.
      for 2 weeks resulted in strong tumor growth inhibition (TGI), but the animals experienced >15% body weight loss (Supplementary Figure 5A and B). The better-tolerated doses of 5 and 10 mg/kg both induced superior TGI compared with 5-fluorouracil and with null or negligible body weight loss (Figure 5A and B). XPO1 target engagement, inhibition of proliferation (Ki67), as well as induction of apoptosis (cleaved-PARP) and DNA damage (p-H2A.X) were confirmed by immunohistochemistry in tumors treated with KPT-8602 vs vehicle (Figure 5C).
      Figure thumbnail gr5
      Figure 5Second-generation XPO1 inhibitor KPT-8602 shows potent anti-tumor activity in TP53-mutant CRC. (A and B) Animals harboring tumors derived from TP53-mutant B1011 PDX model were randomized to treatment with vehicle, 25 mg/kg (mpk) 5-fluorouracil (FU), or 5 or 10 mpk KPT-8602. The arrows indicate days of oral dosing for KPT-8602. (A) Tumor volumes and (B) body weight changes are shown. (C) Representative images and signal quantification of immunohistochemistry staining (hematoxylin and eosin [H&E], XPO1, Ki-67, cleaved (c)-PARP, p-H2A.X) for B1011 treated with vehicle or KPT-8602 at 10 mpk. (D) Animals harboring B1011-derived tumors were randomized to vehicle or 10 mpk KPT-8602 for 12 days. Tumors were collected during the drug recovery period at indicated times. (E) Top 10 enriched Reactome pathways (Fisher’s exact test) for differentially expressed genes during drug recovery period at indicated time points. (F) Representative images of immunohistochemistry staining (H&E, p-ATR/ATM, p-H2A.X) from tumors harvested from animals described in panel D at the indicated times during recovery. DAB, 3,3′-diaminobenzidine tetra hydrochloride. Bar = 100 μm. NS, not significant; ∗P < .05; ∗∗P < .01; ∗∗∗P < .001; ∗∗∗∗P < .0001 by unpaired two-tailed t test.
      To understand the molecular underpinnings of recovery from KPT-8602 treatment in vivo, we conducted RNA sequencing on tumors excised at 24 hours and 6 days after the end of treatment (Figure 5D). Interferon signaling, cell-cycle, and DNA replication emerged as the top transcriptionally deregulated pathways after KPT-8602 treatment, and they all reactivated during recovery, suggesting the existence of transcriptional programs that drive the entry of surviving cancer cells into the proliferative phase (Figure 5E and Supplementary Table 7). Immunohistochemical analysis detected upregulation of p-ATR/ATM and p-H2A.X during recovery, indicating posttranscriptional regulation of DDR proteins also contributes to adaptation to XPO1 inhibition in vivo in TP53-mutant CRC (Figure 5F).
      We next evaluated sequential therapy combinations in vivo. Animals with tumors derived from B1011 were randomized to receive treatment with KPT-8602, followed by AZD-6738 or palbociclib, a Cdk4/6 inhibitor in clinical trials in CRC (ClinicalTrials.gov: NCT02223923, NCT02668666).
      • Guichard S.M.
      • Brown E.
      • Odedra R.
      • et al.
      Abstract 3343: The pre-clinical in vitro and in vivo activity of AZD6738: A potent and selective inhibitor of ATR kinase.
      Consistent with in vitro data, the sequential treatment regimens both yielded robust TGI and prolonged survival compared with vehicle (Figure 6A–D). As expected, TGI induced by sequential combinations was comparable to prolonged KPT-8602 treatment, but sequential therapy was associated with improved tolerability (Supplementary Figure 5C and D). Moreover, combination therapy had superior TGI and survival benefit compared with either palbociclib or AZD-6738 alone (Figure 6A–D and Supplementary Figure 5E and F). Consistent with our mechanistic studies, the reverse therapy sequence was equally effective in the case of palbociclib, but inferior TGI was achieved when AZD-6738 was provided before KPT-8602 (Supplementary Figure 5E and F). These data confirm exquisite dependency of TP53-mutant CRC tumors on cell cycle and DDR machineries during recovery from XPO1 inhibition.
      Figure thumbnail gr6
      Figure 6Sequential dosing with KPT-8602 and palbociclib or AZD-6738 prolongs treatment response and survival in TP53-mutant CRCs. (A) Tumor growth and (B) Kaplan-Meier survival curves are shown for animals harboring tumors derived from the TP53-mutant B1011 model that were randomized to treatment with vehicle, palbociclib (100 mg/kg [mpk]), or KPT-8602 (10 mpk) for 2 weeks, followed by vehicle or palbociclib for 2 weeks. (C) Tumor growth and (D) Kaplan-Meier survival curves are shown for animals harboring tumors derived from B1011 that were randomized to treatment with vehicle, AZD-6738 (50 mpk), or KPT-8602 (10 mpk) for 2 weeks, followed by vehicle or AZD-6738 for 2 weeks. (E) End point tumor growth comparison (%) between treated groups—KPT-8602 (K) and KPT-8602+AZD-6738 (K+A)—and vehicle in 3 TP53–wild-type (wt) and 3 TP53-mutant (mut) CRC PDXs. End point tumor volumes were defined as the last measurements for each tumor when vehicle-treated tumors reached the ethical limit (see ). The horizontal line in the middle of each box indicates the median, and the top and bottom borders of the box mark the 75th and 25th percentiles, respectively. (F) Illustration of TP53-dependent adaption to DNA damage induced by XPO1 inhibition and the informed sequential combinations for patient-stratified clinical trial designs with CDK4/6 or ATR inhibitors in CRC. Data in A and C are presented as the mean ± standard deviation. Tumor growth analysis: NS, not significant; ∗P < .05, ∗∗P < .01, ∗∗∗P < .001, ∗∗∗∗P < .0001 by unpaired 2-tailed t test. Survival analysis: ∗P < .05, ∗∗P < .01, ∗∗∗P < .001, ∗∗∗∗P < .0001 by Mantel-Cox test.
      To validate TP53 as a patient stratification biomarker in CRC, we selected 3 wild-type and 3 mutant TP53 CRC PDX models. As anticipated, sequential treatment with KPT-8602 and AZD-6738 resulted in statistically significantly greater TGI vs KPT-8602 alone only in TP53-mutant models, whereas KPT-8602 alone resulted in similar TGI as combination therapy with AZD-6738 in TP53–wild-type models (Figure 6E and Supplementary Figure 6A–F). Our results validate TP53 mutational status as a valuable biomarker of ATM/ATR checkpoint dependency in CRC cells that survive XPO1 inhibition and support clinical evaluation of the sequential administration of XPO1 and ATR inhibitor drugs in TP53-mutated CRC (Figure 6F).

      Discussion

      Our study integrated in vivo functional genomics and high-throughput in vitro drug screening to identify rapidly translatable therapeutic strategies in CRC. Our screens were conducted in patient-derived CRC samples, which better recapitulate the genetic and functional heterogeneity of human tumors compared with established tumor cell lines. We selected shRNA-based gene suppression, rather than inactivation based on CRISPR (clustered regularly interspaced short palindromic repeats), to better mimic the biological activity of targeted drugs, which do not usually completely suppress gene function. To our knowledge, this is the first attempt to systematically combine PDX-centric functional genomics with in vitro high-throughput drug screens, and our data support this as a viable alternative approach to labor- and resource-intensive PDX preclinical trials
      • Gao H.
      • Korn J.M.
      • Ferretti S.
      • et al.
      High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.
      designed to inform drug repositioning.
      Our approach was adequate to captured clinically relevant, genetic context-specific dependencies in CRC, as demonstrated by the emergence of EGFR as a positive screening hit solely in wild-type KRAS models, consistent with published data and the established use of KRAS mutational status as a biomarker for EGFR inhibitor treatment in patients with CRC. One advantage of our strategy is that clinical safety and efficacy readouts are already available for the drugs/drug targets included in our screening platform. For XPO1, inhibitor drugs in clinical testing for other indications have generated promising data, and selinexor has been approved for treatment of advanced multiple myeloma and diffuse large B-cell lymphoma.
      XPO1 inhibitor approved for multiple myeloma.
      ,
      • Guichard S.M.
      • Brown E.
      • Odedra R.
      • et al.
      Abstract 3343: The pre-clinical in vitro and in vivo activity of AZD6738: A potent and selective inhibitor of ATR kinase.
      However, XPO1 targeting in CRC has not been adequately evaluated. We show that XPO1 expression is higher in CRC cells compared with normal colon epithelial cells and that XPO1 inhibition potently inhibits proliferation and induces apoptosis of malignant cells compared with normal cells. Mechanistically, our data suggest that XPO1 inhibition results in a toxic accumulation of DNA damage in CRC cells that is not detected in normal colon epithelial cells, indicating a tumor-specific functional dependency on XPO1.
      Multiple tumor suppressor proteins (TSPs) and transcription factors in the nucleus, such as p53, Rb, p27, and FOXO3a, protect cells by regulating cell growth, apoptosis, and DNA damage repair;
      • Kau T.R.
      • Way J.C.
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      Nuclear transport and cancer: from mechanism to intervention.
      ,
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      Colorectal cancer: genetics of development and metastasis.
      • Harris S.L.
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      The p53 pathway: positive and negative feedback loops.
      • Vogelstein B.
      • Lane D.
      • Levine A.J.
      Surfing the p53 network.
      thus, cytoplasmic mislocalization of TSPs can lead to tumor progression. One strategy to prevent localization of essential TSPs in the cytoplasm is to inhibit their nuclear export. XPO1 is the sole nuclear export receptor for multiple TSPs. Overexpression of XPO1 is reported in different cancers types and can correlate with poor prognosis.
      • Xu D.
      • Grishin N.V.
      • Chook Y.M.
      NESdb: a database of NES-containing CRM1 cargoes.
      ,
      • Yao Y.
      • Dong Y.
      • Lin F.
      • et al.
      The expression of CRM1 is associated with prognosis in human osteosarcoma.
      The XPO1 inhibitors, KPT-330 and KPT-8602, induce nuclear accumulation of TSPs and restore their tumor suppressor activity.
      • Lapalombella R.
      • Sun Q.
      • Williams K.
      • et al.
      Selective inhibitors of nuclear export show that CRM1/XPO1 is a target in chronic lymphocytic leukemia.
      ,
      • Vercruysse T.
      • De Bie J.
      • Neggers J.E.
      • et al.
      The second-generation exportin-1 inhibitor KPT-8602 demonstrates potent activity against acute lymphoblastic leukemia.
      ,
      • Chen Y.
      • Camacho S.C.
      • Silvers T.R.
      • et al.
      Inhibition of the nuclear export receptor XPO1 as a therapeutic target for platinum-resistant ovarian cancer.
      ,
      • Etchin J.
      • Berezovskaya A.
      • Conway A.S.
      • et al.
      KPT-8602, a second-generation inhibitor of XPO1-mediated nuclear export, is well tolerated and highly active against AML blasts and leukemia-initiating cells.
      Thus, XPO1 inhibition represents a unique therapeutic concept.
      A previous study indicated that p53 deficiency or loss significantly contributed to XPO1 inhibitor resistance in thymic epithelial tumors.
      • Conforti F.
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      • Rao G.
      • et al.
      Therapeutic effects of XPO1 inhibition in thymic epithelial tumors.
      In contrast, our data from CRC cell lines with varied TP53 mutational status uncovered a mechanism of DNA damage accumulation unrelated to p53 status upon XPO1 inhibition. In addition, we identified a direct association between TP53 mutational status and recovery dynamics after XPO1 inhibition. Our findings suggest that p53 inhibits adaptation to DNA damage induced by XPO1 inhibition and engages the G1/S checkpoint, while p53-defective cells lack this ability and are highly dependent on the ATM/ATR axis at the G2/M checkpoint. These results are consistent with previous studies showing that cancer cells harboring the TP53 loss-of-function mutation have a dysfunctional G1/S checkpoint and primarily rely on the G2/M checkpoint to arrest the cell cycle and execute DNA repair.
      • Koniaras K.
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      Inhibition of Chk1-dependent G2 DNA damage checkpoint radiosensitizes p53 mutant human cells.
      ,
      • Marechal A.
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      DNA damage sensing by the ATM and ATR kinases.
      That TP53-deficient cells depend on ATM and ATR-mediated checkpoint signaling through the p38 MAPK/MK2 pathway to repair DNA damage has been consistently demonstrated.
      • Reinhardt H.C.
      • Aslanian A.S.
      • Lees J.A.
      • et al.
      p53-deficient cells rely on ATM-and ATR-mediated checkpoint signaling through the p38MAPK/MK2 pathway for survival after DNA damage.
      We show that TP53-mutant CRC cells displayed higher sensitivity to sequential XPO1 inhibitor treatment, followed by ATR inhibition, compared with wild-type TP53 CRC cells in vitro and in vivo, which explicates a rational therapeutic approach. The consistency of these results across models carrying some of the most frequent TP53 mutations in CRC (R248W, R273H, and R175H)
      • Li H.
      • Zhang J.
      • Tong J.H.M.
      • et al.
      Targeting the oncogenic p53 mutants in colorectal cancer and other solid tumors.
      compels the clinical investigation of sequential XPO1-ATR inhibitor therapy in TP53-mutant CRC. TP53 mutation occurs in approximately 40% to 50% of sporadic CRCs,
      • Lopez I.
      • L PO
      • Tucci P.
      • et al.
      Different mutation profiles associated to P53 accumulation in colorectal cancer.
      • Baker S.J.
      • Fearon E.R.
      • Nigro J.M.
      • et al.
      Chromosome 17 deletions and p53 gene mutations in colorectal carcinomas.
      • Li X.L.
      • Zhou J.
      • Chen Z.R.
      • et al.
      P53 mutations in colorectal cancer-molecular pathogenesis and pharmacological reactivation.
      and KPT-330 and AZD6738 are in clinical trials in solid tumors, with data from the former showing clinical activity with an acceptable safety profile.
      • Abdul Razak A.R.
      • Mau-Soerensen M.
      • Gabrail N.Y.
      • et al.
      First-in-class, first-in-human phase I study of selinexor, a selective inhibitor of nuclear export, in patients with advanced solid tumors.
      We also demonstrated that palbociclib, which is approved for treatment of estrogen receptor-positive metastatic breast cancer
      • Dhillon S.
      Palbociclib: first global approval.
      and is in clinical development for additional indications, including CRC,
      • Kalu N.N.
      • Mazumdar T.
      • Peng S.
      • et al.
      Comprehensive pharmacogenomic profiling of human papillomavirus-positive and -negative squamous cell carcinoma identifies sensitivity to aurora kinase inhibition in KMT2D mutants.
      can retard recovery from XPO1 inhibitor treatment in CRC models with functional p53, illuminating another actionable clinical opportunity to evaluate targeted therapies in biomarker-defined CRC.
      The accumulation of DNA damage induced by XPO1 inhibition suggests that patients with CRC who receive this treatment may also benefit from immune checkpoint blockade (ICB). Recently, anti–PD-1 (nivolumab and pembrolizumab) and anti-CTLA4 (ipilimumab) therapies were approved for a subset of patients with advanced CRC characterized by deficient DNA mismatch repair (dMMR) or microsatellite instability-high.
      • Overman M.J.
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      • Leach J.L.
      • et al.
      Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study.
      ,
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      • et al.
      Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade.
      MMR is essential for DNA repair, and dMMR tumors harbor high mutational burdens associated with high neoantigen loads and T-cell infiltration, which in turn should elicit profound immunogenic responses by the host and in response to ICB therapy.
      • Le D.T.
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      Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade.
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      The vigorous immune microenvironment of microsatellite instable colon cancer is balanced by multiple counter-inhibitory checkpoints.
      • Schwitalle Y.
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      However, only 3% to 6% of patients with advanced-staged CRC have dMMR or microsatellite instability-high tumors that are likely to respond to ICB therapy.
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      To expand the application of ICB therapy, several clinical studies are evaluating ICB therapy combined with DNA damaging agents or DDR inhibitors, such as PARP inhibitors.
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      Based on our finding that coupling XPO1 with ATR inhibitor treatment results in massive accumulation of DNA damage, we conclude that combining XPO1 and ATR inhibitors, followed by ICB therapy to treat TP53-mutant CRC, may be beneficial. Further studies are needed to provide mechanistic insights regarding this triple combination as well as identify the combination sequence strategy and drug doses to optimize clinical benefit.
      Taken together, our findings suggest that administration of XPO1 inhibitors, especially in combination with ATR inhibitors, may be a novel therapeutic approach to treat patients with CRC. This mechanism-based combination strategy may prevent treatment adaptation to produce more durable responses in patients with this disease.

      Acknowledgments

      We wish to thank the members of Viale, Draetta, Genovese, and Carugo laboratories for discussions and reagents. Special thanks to Dr Maria Emilia Di Francesco, Dr Christopher Carroll, and the Institute for Applied Cancer Science (IACS) platform for advice and reagents. We thank the University of Texas MD Anderson Cancer Center (UTMDACC) Department of Veterinary Medicine, the UTMDACC Sequencing & Non-coding RNA Program, and the UTMDACC Flow Facility. Data are provided as supplementary tables.

      CRediT Authorship Contributions

      Akira Inoue, MD, PhD (Conceptualization: Lead; Data curation: Lead; Formal analysis: Lead; Investigation: Lead; Methodology: Lead; Project administration: Lead; Validation: Lead; Writing – original draft: Lead; Writing – review & editing: Lead).
      Frederick S. Robinson (Data curation: Lead; Formal analysis: Supporting; Investigation: Equal; Methodology: Lead; Project administration: Lead; Validation: Supporting; Writing – original draft: Supporting; Writing – review & editing: Supporting).
      Rosalba Minelli, PhD (Investigation: Equal).
      Hideo Tomihara, MD, PhD (Data curation: Supporting; Formal analysis: Supporting; Project administration: Supporting; Supervision: Supporting).
      Bahar Salimian Rizi, PhD (Conceptualization: Supporting; Data curation: Supporting; Project administration: Supporting; Supervision: Supporting).
      Johnathon L. Rose (Conceptualization: Supporting; Data curation: Supporting; Methodology: Supporting; Project administration: Supporting; Supervision: Supporting).
      Takahiro Kodama, MD PhD (Investigation: Supporting).
      Sanjana Srinivasan, Graduate Research Assistant (Data curation: Supporting; Methodology: Supporting; Visualization: Supporting).
      Angela L. Harris, (Data curation: Equal; Investigation: Equal; Project administration: Equal).
      Andy M. Zuniga (Data curation: Supporting; Formal analysis: Supporting; Methodology: Supporting; Project administration: Supporting).
      Robert A. Mullinax, PhD (Conceptualization: Supporting; Formal analysis: Supporting; Funding acquisition: Supporting).
      Xiaoyan Ma, PhD (Data curation: Supporting; Project administration: Supporting).
      Sahil Seth, PhD (Conceptualization: Equal; Data curation: Supporting; Formal analysis: Supporting; Investigation: Supporting; Methodology: Equal; Project administration: Supporting; Supervision: Supporting).
      Joseph R. Daniele, PhD (Investigation: Supporting).
      Michael D. Peoples (Methodology: Supporting; Project administration: Supporting).
      Sara Loponte, PhD (Data curation: Equal; Formal analysis: Equal; Funding acquisition: Supporting; Investigation: Supporting; Methodology: Supporting; Project. administration: Supporting).
      Kadir C. Akdemir, PhD (Conceptualization: Supporting; Data curation: Equal; Investigation: Equal; Project administration: Supporting).
      Tin Oo Khor, PhD (Data curation: Equal; Methodology: Supporting; Project administration: Supporting).
      Ningping Feng, PhD (Data curation: Equal; Investigation: Supporting; Project administration: Supporting).
      Jason Roszik, PhD (Conceptualization: Supporting; Data curation: Supporting; Investigation: Supporting; Methodology: Supporting).
      Mary M. Sobieski (Data curation: Supporting; Investigation: Supporting; Project administration: Supporting).
      David Brunell, PhD (Conceptualization: Supporting; Data curation: Equal; Methodology: Equal).
      Clifford Stephan, PhD (Data curation: Supporting; Funding acquisition: Supporting; Investigation: Supporting; Project administration: Supporting; Resources: Supporting; Writing – review & editing: Supporting).
      Virginia Giuliani, PhD (Conceptualization: Supporting; Data curation: Supporting; Funding acquisition: Supporting; Investigation: Supporting; Methodology: Supporting; Project administration: Supporting; Supervision: Supporting).
      Angela K. Deem, PhD (Conceptualization: Supporting; Funding acquisition: Supporting; Supervision: Supporting; Writing – original draft: Supporting; Writing – review & editing: Supporting).
      Takashi Shingu, MD, PhD (Data curation: Supporting; Formal analysis: Supporting; Methodology: Supporting).
      Yonathan Lissanu Deribe, MD, PhD (Conceptualization: Supporting; Supervision: Supporting).
      David G. Menter, PhD (Conceptualization: Supporting; Investigation: Supporting; Project administration: Supporting; Supervision: Supporting).
      Timothy P. Heffernan, PhD (Conceptualization: Lead; Data curation: Supporting; Funding acquisition: Lead; Investigation: Supporting; Supervision: Supporting; Visualization: Supporting).
      Andrea Viale, MD, PhD (Conceptualization: Supporting; Investigation: Supporting; Supervision: Supporting).
      Christopher A. Bristow, PhD (Conceptualization: Lead; Data curation: Supporting; Funding acquisition: Supporting; Investigation: Supporting; Methodology: Supporting; Supervision: Supporting; Validation: Supporting).
      Scott Kopetz, MD, PhD (Conceptualization: Supporting; Data curation: Equal; Funding acquisition: Supporting; Investigation: Supporting; Supervision: Supporting).
      Giulio F. Draetta, MD, PhD (Conceptualization: Lead; Funding acquisition: Lead; Investigation: Lead; Project administration: Supporting; Supervision: Equal; Validation: Equal).
      Giannicola Genovese, MD, PhD (Conceptualization: Supporting; Data curation: Supporting; Investigation: Supporting; Methodology: Supporting; Supervision: Supporting).
      Alessandro Carugo, PhD (Conceptualization: Supporting; Data curation: Supporting; Formal analysis: Supporting; Funding acquisition: Supporting; Investigation: Supporting; Methodology: Supporting; Project administration: Supporting; Supervision: Supporting; Validation: Supporting; Visualization: Supporting; Writing – original draft: Equal; Writing – review & editing: Supporting).

      Supplementary Material

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