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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 2018 Jan 29;115(7):E1570–E1577. doi: 10.1073/pnas.1719577115

Disruption of the anaphase-promoting complex confers resistance to TTK inhibitors in triple-negative breast cancer

K L Thu a,b, J Silvester a,b, M J Elliott a,b, W Ba-alawi b,c, M H Duncan a,b, A C Elia a,b, A S Mer b, P Smirnov b,c, Z Safikhani b, B Haibe-Kains b,c,d,e, T W Mak a,b,c,1, D W Cescon a,b,f,1
PMCID: PMC5816201  PMID: 29378962

Significance

Using functional genomic screens, we have identified resistance mechanisms to the clinical TTK protein kinase inhibitor (TTKi) CFI-402257 in breast cancer. As this and other TTKi are currently in clinical trials, understanding determinants of tumor drug response could permit rational selection of patients for treatment. We found that TTKi resistance is conferred by impairing anaphase-promoting complex/cyclosome (APC/C) function to minimize the lethal effects of mitotic segregation errors. Discovery of this mechanism in aneuploid cancer cells builds on previous reports indicating that weakening the APC/C promotes tolerance of chromosomal instability in diploid cells. Our work suggests that APC/C functional capacity may serve as a clinically useful biomarker of tumor response to TTKi that warrants investigation in ongoing clinical trials.

Keywords: TTK inhibitor, drug resistance, APC/C, CRISPR/Cas9, breast cancer

Abstract

TTK protein kinase (TTK), also known as Monopolar spindle 1 (MPS1), is a key regulator of the spindle assembly checkpoint (SAC), which functions to maintain genomic integrity. TTK has emerged as a promising therapeutic target in human cancers, including triple-negative breast cancer (TNBC). Several TTK inhibitors (TTKis) are being evaluated in clinical trials, and an understanding of the mechanisms mediating TTKi sensitivity and resistance could inform the successful development of this class of agents. We evaluated the cellular effects of the potent clinical TTKi CFI-402257 in TNBC models. CFI-402257 induced apoptosis and potentiated aneuploidy in TNBC lines by accelerating progression through mitosis and inducing mitotic segregation errors. We used genome-wide CRISPR/Cas9 screens in multiple TNBC cell lines to identify mechanisms of resistance to CFI-402257. Our functional genomic screens identified members of the anaphase-promoting complex/cyclosome (APC/C) complex, which promotes mitotic progression following inactivation of the SAC. Several screen candidates were validated to confer resistance to CFI-402257 and other TTKis using CRISPR/Cas9 and siRNA methods. These findings extend the observation that impairment of the APC/C enables cells to tolerate genomic instability caused by SAC inactivation, and support the notion that a measure of APC/C function could predict the response to TTK inhibition. Indeed, an APC/C gene expression signature is significantly associated with CFI-402257 response in breast and lung adenocarcinoma cell line panels. This expression signature, along with somatic alterations in genes involved in mitotic progression, represent potential biomarkers that could be evaluated in ongoing clinical trials of CFI-402257 or other TTKis.

Triple-negative breast cancer (TNBC), characterized by lack of expression of estrogen and progesterone receptors or amplification of HER2, is recognized as an aggressive disease with poor outcomes and short survival in the metastatic setting. While TNBC is a heterogeneous disease, the majority exhibit high levels of aneuploidy and a dearth of actionable genetic alterations (e.g., focal DNA amplifications or activating point mutations that can be targeted) (1–3). The latter explains in part the current lack of targeted treatment options for this disease, and underscores the need for novel treatment strategies. The recurrent somatic changes that occur in TNBC include nearly ubiquitous TP53 mutations, as well as genetic alterations to other tumor suppressors including PTEN, RB1, BRCA1 and components of the DNA damage response pathway (1). The loss of these critical regulators of the cell cycle and genome maintenance contribute to the genomic instability characteristic of TNBC, a hallmark that represents a potential therapeutic vulnerability (4, 5).

Inhibition of TTK protein kinase (TTK), also known as monopolar spindle 1 (MPS1), has emerged as a promising therapeutic strategy for the treatment of aneuploid tumors, with TNBCs an important focus of clinical development. As a mediator of the spindle assembly checkpoint (SAC), which delays anaphase until all chromosomes are properly attached to the mitotic spindle, TTK has an integral role in maintaining genomic integrity (6). Because most cancer cells are aneuploid, they are heavily reliant on the SAC to adequately segregate their abnormal karyotypes during mitosis. This is evidenced by the fact that the SAC is often weakened but rarely completely inactivated in cancer cells (7–9). Abrogation of the SAC by TTK inhibition results in intolerable levels of genomic instability that are incompatible with cancer cell survival (10, 11). With several TTK inhibitors (TTKis) currently being evaluated as anticancer therapeutics in clinical trials, a more complete understanding of the mechanisms mediating TTKi sensitivity and resistance could have a significant impact by guiding their successful clinical development.

In this study, we aimed to identify cellular mechanisms of resistance to the clinical TTKi CFI-402257. Importantly, we investigated this question in biologically relevant, aneuploid TNBC cell lines that model one of the principal human malignancies for which CFI-402257 is being developed. Using genome-wide CRISPR/Cas9 enrichment screens in three TNBC models, we found that genetic disruption of anaphase-promoting complex/cyclosome (APC/C) components or other genes involved in mitotic progression confers resistance to CFI-402257 and other TTKis. Our work independently validates and extends findings from a previous study reporting that APC/C dysfunction promotes diploid cell tolerability of genomic instability induced by reversine, a chemical probe that inhibits TTK (12). Furthermore, we report an APC/C gene expression signature that is associated with response to CFI-402257 in breast and lung cancer cell line panels. This genetic signature represents a promising biomarker for further development and evaluation in ongoing clinical trials, where its application in evaluating APC/C function could inform patient selection or predict drug response to clinical TTKis.

Results

CFI-402257 Accelerates Mitosis and Induces Mitotic Segregation Errors and Apoptosis in TNBC.

To study the cellular effects of CFI-402257 in TNBC, we selected three commonly used cell line models: MDA-MB-231, MDA-MB-468, and MDA-MB-436. Each line is reportedly aneuploid and contains a TP53 mutation (13), characteristic of clinical TNBC. The SAC functions to prevent anaphase onset until all chromosomes are sufficiently attached to the mitotic spindle, thereby ensuring proper chromosome segregation during mitosis (6). TTK inhibition causes SAC inactivation and premature onset of anaphase with improperly segregated chromosomes. To assess the effects of TTK inhibition on mitotic timing, live-cell microscopy was used to measure the time from nuclear envelope breakdown (NEBD) to onset of anaphase. CFI-402257 treatment (150 nM) significantly reduced mitotic timing by twofold to threefold in all three cell lines (Fig. 1A). As expected, scoring of mitotic cells identified significantly more mitotic errors (e.g., lagging chromosomes, anaphase bridges, and multipolar divisions) in CFI-402257–treated compared with DMSO control-treated cells (Fig. 1B and Fig. S1). We next assessed whether treatment with CFI-402257 potentiated aneuploidy using propidium iodide (PI) staining to measure DNA content. While 72 h of low-dose CFI-402257 (100 nM) had a modest effect on DNA content, a higher dose (400 nM) reproducibly increased the fraction of cells with >4n content in all three lines (Fig. 1C). Finally, we determined that aneuploidy induced by 72 h of treatment was associated with induction of apoptosis (Fig. 1D). Taken together, these cellular effects in TNBC are consistent with TTK inhibition-driven abrogation of the SAC, which accelerates mitotic progression and induces mitotic errors, aneuploidy, and apoptosis, consistent with reports for other TTKis (12, 14–17).

Fig. 1.

Fig. 1.

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CFI-402257 induces mitotic errors and leads to cell death. (A) Live-cell imaging was used to measure mitotic timing. Cells were synchronized with double-thymidine block and released into DMSO or CFI-402257 for at least 4 h before time-lapse imaging. Each dot represents a single cell, and at least 100 cells were counted per experiment. (B) Classification of mitoses in treated cells. Mitoses observed were scored as normal (N) or as abnormal if they exhibited segregation errors, including lagging chromosomes (LC), endoreduplication (ER), anaphase bridges (AB), or multipolar divisions (MP). (C) DNA content analysis of treated cells. Cells were synchronized as above and released into DMSO or CFI-402257 for 72 h. Live cells were stained with PI and analyzed by flow cytometry. (Inset) Numbers indicate the percentage of cells exhibiting >4n DNA content. (D) Assessment of apoptosis induction by CFI-402257. Cells were collected and costained with Annexin-V and PI to determine the percentage of cells undergoing apoptosis after 72 h of treatment. P values indicate significance for two-tailed Student’s t tests (mitotic timing and apoptosis) and χ2 tests (mitotic errors, normal vs. abnormal). All statistics were calculated using GraphPad Prism software. *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant. Error bars indicate mean ± SD.

Genome-Wide CRISPR/Cas9 Screen Reveals APC/C Impairment Confers Resistance to CFI-402257.

To understand mediators of CFI-402257 response, we used a functional genomics approach. Stable Cas9-expressing lines were generated for each model and used to conduct genome-wide CRISPR screens with the Toronto Human Knockout Pooled Library (18). We used a positive enrichment approach to select gene knockouts that confer resistance to CFI-402257. Cells were continuously cultured in media containing CFI-402257 or DMSO vehicle control. Three different concentrations of CFI-402257 were attempted for each cell line. Of the nine screens attempted, six were successful, as evidenced by the emergence of a drug-resistant cell population (one in MDA-MB-468, two in MDA-MB-436, and three in MDA-MB-231), and three were unsuccessful (i.e., no drug resistant cell population emerged because drug concentrations were too high). Screens were ended once a drug-resistant population had clearly emerged following the initial lagging period where CFI-402257 impaired survival and proliferation of the pooled cells (Fig. 2A). Importantly, cells transduced with an sgRNA targeting LacZ were cultured with CFI-402257 in parallel to ensure that cell death occurred at the concentrations used for the screens. Targeted sequencing of sgRNA inserts in baseline, DMSO-treated, and drug-resistant cell populations were evaluated using the MAGeCK algorithm to identify sgRNAs significantly enriched in the resistant population (19). Comparison of the CRISPR library representation at the beginning and end of the screens indicated that representation was reduced in the final CFI-402257–resistant population, as expected (Fig. S2A).

Fig. 2.

Fig. 2.

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CRISPR/Cas9 screens identify the anaphase-promoting complex as a mediator of CFI-402257 sensitivity. (A) Screen growth curves for MDA-MB-231, MDA-MB-436, and MDA-MB-468 during CFI-402257 induced selection of drug-resistant cells. (B) Gene Ontology analyses conducted using Enrichr reveal that genes identified by the CFI-402257 resistance screens are enriched for involvement in the anaphase-promoting complex.

Single guide RNAs enriched in the final drug-resistant population are those that target genes whose inactivation promotes resistance to CFI-402257. To identify the most robust candidates, we trimmed each screen’s list of candidate genes to only those with an enrichment P value < 0.05, and then compared these lists across the six screens. This stringent analysis revealed 15 genes that were significantly enriched in at least one screen per cell line and in at least four of the six screens conducted (Table 1 and Fig. S2B). Assessment of these candidates using Enrichr analysis identified the APC/C as the most significantly enriched cellular component for two different Gene Ontology databases (GO and Jensen) (20, 21) (Fig. 2B and Table S1). ANAPC13 and ANAPC15 are both components of the APC/C itself, while MAD2L1BP, better known as p31(comet), is a negative regulator of the SAC through its antagonism of the mitotic checkpoint complex (22). In light of the identification of APC/C components in our top hits, we examined the sgRNA lists and identified other APC/C components in individual cell lines, including ANAPC4, ANAPC5, CDC16, CDC20, and CDC23 in MDA-MB-468; ANAPC4, CDC20, and CDC16 in MDA-MB-436; and ANAPC5, ANAPC10, and CDC27 in MDA-MB-231. Taken together, our functional genomics approach revealed numerous components of the complex responsible for anaphase initiation following SAC inactivation, implicating a delay in anaphase onset and mitotic progression as a mechanism mediating resistance to CFI-402257, and thus a potentially important determinant of drug response.

Table 1.

Top 15 candidate genes from CRISPR/Cas9 screens

Gene Number of screens
ANAPC13 6
ANKS1A 5
ETS1 5
LRTM1 5
MAD2L1BP 5
PLA2G16 5
ANAPC15 4
BID 4
CMIP 4
ENPP5 4
GPSM3 4
KCNH8 4
LACE1 4
SERPINA7 4
VSIG1 4
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Bold indicates candidate genes validated in this study.

Inactivation of ANAPC4, ANAPC13, and MAD2L1BP Confers Resistance to Multiple TTKis.

We chose to further investigate the mitotic checkpoint complex antagonist MAD2L1BP and the APC/C component ANAPC13 identified in our CFI-402257 screen as mediators of TTKi resistance. We also investigated ANAPC4, which was previously described to be involved in diploid cell tolerance of chromosomal instability in an siRNA screen (Table S2) (12). To confirm that these candidate genes enable TNBC resistance to CFI-402257, we disrupted them using CRISPR/Cas9 editing with sgRNAs identified in our screens and with siRNA as an orthogonal method. Knockdowns and genome edits were confirmed by quantitative PCR (qPCR), Western blot analysis (when sufficient antibodies were available), or sequencing (Fig. 3, Figs. S3 and S4, and Table S3). Following CRISPR editing or siRNA knockdown, we conducted colony survival assays to determine the effects of gene manipulation on sensitivity to CFI-402257. Both of these methods confirmed that ANAPC4, ANAPC13, and MAD2L1BP mediate CFI-402257 response in MDA-MB-231 cells, as genetic interference with these genes led to increased TNBC resistance to TTK inhibition (Fig. 3 A–C). Furthermore, we found that resistance conferred by knockdown of these genes was associated with reduced apoptosis, dampened aneuploidy induction, and elongated mitotic timing with CFI-402257 treatment in MDA-MB-231 cells (Fig. 3 D–I). Despite the high rate of mitotic errors in basal conditions (Fig. 1), we found an increase in the number of normal mitoses when knockdown cells were treated with CFI-402257 (Fig. 3 G–I). Similar effects were observed in MDA-MB-436 cells (Fig. S3).

Fig. 3.

Fig. 3.

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Inhibition of genes regulating mitotic progression promotes resistance of MDA-MB-231 to CFI-402257. (A) Colony survival assay for MDA-MB-231 cells transfected with siRNAs targeting ANAPC4, ANAPC13, and MAD2L1BP and treated with DMSO or CFI-402257. Colonies surviving 10–14 d of treatment were stained with SRB, solubilized, and quantified by spectrophotometry. Survival is illustrated as the proportion of drug-treated colonies relative to DMSO-treated (control) colonies. Dotted lines indicate colony growth in siNTC control cells. A representative assay is shown. (B and C) siRNA knockdown efficiencies were determined by qRT-PCR [error bars indicate maximum/minimum relative quantification (RQ) values] and Western blot analysis. (D) Quantitation of apoptosis induction in siRNA-transfected cells treated with DMSO or CFI-402257 for 72 h. (E and F) DNA content analysis of siRNA-transfected cells treated with DMSO or CFI-402257 at 100 nM or 400 nM doses for 72 h. (G–I) Mitotic timing and error analysis of siRNA-transfected cells treated with 150 nM CFI-402257. Error bars indicate mean ± SD. P values indicate significance for two-tailed Student’s t tests (apoptosis, DNA content, and mitotic timing) or χ2 tests (mitotic errors, normal vs. abnormal). All statistics were calculated using GraphPad Prism software. *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant. Error bars indicate mean ± SD.

We next asked whether genetic manipulation of ANAPC4, ANAPC13, and MAD2L1BP affected sensitivity to additional published selective TTKis, including MPI-0479605 (17), NMS-P715 (23) and Mps-Bay2a (15). Compared with CFI-402257, these exhibited similar effects on TNBC viability in sulforhodamine B (SRB) dose–response assays, although their potency was lower (Fig. 4A). Consistent with our results for CFI-402257, CRISPR/Cas9 and siRNA-mediated knockdown of ANAPC4, ANAPC13, and MAD2L1BP also conferred resistance to these TTKis, although with variable penetrance across cell lines and the genes manipulated at the concentrations tested (Fig. 4 B and C and Fig. S4).

Fig. 4.

Fig. 4.

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Delaying anaphase confers resistance to multiple TTKis. (A) Response of MDA-MB-231, MDA-MB-436, and MDA-MB-468 to various TTKis. Dose–response curves were generated using SRB assays with nine-point serial drug dilutions. For each drug dose, cell viability is plotted as the proportion of viability observed in DMSO-treated control cells. Curves were plotted with GraphPad Prism software, with error bars indicating SD. (B) Colony survival assays for MDA-MB-231 cells transfected with siRNAs targeting ANAPC4, ANAPC13, and MAD2L1BP. (C) Quantitation of colony survival assays after solubilizing SRB. Colony survival is plotted as the proportion of drug-treated colonies relative to DMSO-treated (control) colonies. Error bars indicate mean ± SD. Dotted lines indicate colony growth in siNTC control cells. Representative experiments are shown.

Response to CFI-402257 Is Associated with Reduced APC/C Gene Expression Signature in Breast and Lung Cancer Cell Lines.

Finally, we sought to investigate whether the biological mechanism revealed by our functional genomics screens could be useful to identify a biomarker correlate of intrinsic CFI-402257 response. Drug response profiles were generated for a panel of 52 breast cancer cell lines for which gene expression profiles were available (Fig. 5A and Table S4). We hypothesized that cancers with low expression of APC/C components or MAD2L1BP would be relatively resistant to CFI-402257. To test this, we evaluated the association between a gene set comprising 16 APC/C genes and MAD2L1BP (Fig. 5B), and CFI-402257 response using gene set enrichment analysis (GSEA) (24). We found that the APC/C-MAD2L1BP gene set was significantly associated with the in vitro response to CFI-402257 (Fig. 5C). Interestingly, among breast cancer subtypes, the APC/C-MAD2L1BP gene set association with CFI-402257 response was most significant in TNBC models (Fig. 5D). Assessment of the gene set in an independent panel of 20 lung adenocarcinoma cell lines confirmed the association (Fig. S5A). We then evaluated an APC/C-MAD2L1BP gene signature defined as the mean expression of the 16 APC/C genes and MAD2L1BP (Fig. 5B), and found a significant association between this metagene and CFI-402257 response in breast cancer cell lines (Fig. S5B). Furthermore, of the 17 genes composing the APC/C-MAD2L1BP gene set, we found that a metagene consisting of only ANAPC4 and CDC20 was most strongly associated with CFI-402257 response (Fig. 5E).

Fig. 5.

Fig. 5.

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The APC/C gene signature is associated with CFI-402257 response in vitro. (A) Distribution of CFI-402257 sensitivity across 52 breast cancer cell lines. The AAC was calculated from dose–response assays and used as a metric of cell line drug sensitivity. The P value for an ANOVA comparing AACs across breast cancer subtypes is indicated. (B) List of 17 genes composing the APC/C-MAD2L1BP gene set investigated. The genes composing the two-gene metagene (below) are indicated in bold. (C and D) GSEA of APC/C-MAD2L1BP gene set association with CFI-402257 response in all breast cancer cell lines (n = 52) (C), and only in TNBC lines (n = 26) (D). (E) Correlation between the two-gene metagene and CFI-402257 response in 52 breast cancer cell lines. The metagene score was calculated as the mean expression of the genes for each sample. Pearson correlation coefficients and P values are indicated. (F) Violin plots displaying the distribution and probability density of the two-gene metagene scores across various TCGA tumor types. Only tumor types with 500 or more patients were assessed.

To address the potential utility of the APC/C metagene as a clinical correlate of CFI-402257 response, we investigated the variability in the two-gene metagene score across various tumor types using public gene expression data from The Cancer Genome Atlas (TCGA). This showed substantial variability within breast and other tumors, and importantly, revealed numerous outliers with very low scores that could represent tumors with intrinsic resistance to CFI-402257 (Fig. 5F). The variation we observed in APC/C metagene scores prompted us to assess the frequency of APC/C complex genetic disruption in clinical tumors. A previous study reported that point mutations in APC/C complex components occur in up to 23% of nearly 8,000 tumors in the TCGA pan-cancer dataset (12). Our focused analysis of TCGA breast cancers considering somatic DNA alterations with potential loss of function consequences (i.e., point mutations and homozygous deletions) identified these in 4% of primary tumors (17/482), while down-regulation of gene expression was apparent in 46% of cases (222/482) (Fig. S6). Thus, clinical cancers exhibit measurable differences in markers of APC/C function, which are predicted to be associated with TTKi response based on our functional and correlative studies.

Discussion

Several TTKis, including CFI-402257, are currently being tested in early-phase clinical trials to characterize their safety and explore their antitumor activity as cancer therapeutics (e.g., NCT02792465, NCT02138812, NCT02366949; EudraCT no. 2014–002023-10) (25) as monotherapy or in combination with taxane chemotherapy. For several of the agents under investigation, breast cancer (and TNBC in particular) is a primary indication of interest. Patient stratification is becoming increasingly important for the development of novel therapies, in order to improve the probability of success in the clinic. This effort can benefit significantly from an understanding of mechanisms of sensitivity and resistance characterized in nonclinical settings (26). Previous reports have identified gatekeeper mutations in the TTK kinase domain as potential mechanisms of acquired resistance to TTKi (analogous to those observed in many clinically approved kinase inhibitors) (27), or have suggested somatic mutations and alterations associated with response (28), but the relevance of these to intrinsic TNBC response are uncertain.

Our approach, using functional genomic screens followed by validation and correlative analyses in TNBC models, was designed to identify biologically relevant processes or pathways that could be linked to drug response for the clinical TTKi CFI-402257. The identification of the APC/C as a central complex mediating sensitivity to CFI-402257 is directly relevant to the rationale for TTK inhibition in TNBC, whereby the characteristic genomic instability of these tumors was identified as a therapeutic vulnerability that can be exploited by TTK-targeting agents (11). Inhibition of TTK in these tumors will cause synthetic lethality by abrogating the SAC and consequently increase aneuploidy to intolerable levels that lead to cancer cell death (29).

Our study carried out in TNBC cell lines has revealed multiple components of the APC/C, which promotes mitotic progression into anaphase, as well as additional genes involved in initiating mitotic exit. These models harbor TP53 mutations and exhibit aneuploidy, characteristic features of clinical TNBCs, supporting the clinical relevance of our findings. Another group has recently reported their investigation of diploid cell tolerance to chromosomal instability using reversine, a chemical probe that inhibits TTK, to model this phenomenon (12). Sansregret et al. conducted a 4-day siRNA screen in immortalized nonmalignant, diploid retinal-pigment epithelial (RPE1) cells, and validated candidate genes in RPE1 and HCT116, a near-diploid colon cancer cell line. These authors reported that APC/C dysfunction enables these cells to tolerate excessive chromosomal instability induced by reversine treatment (12). Interestingly, this siRNA-screen identified both overlapping and nonoverlapping candidates compared with our screen. Among other factors, this may reflect the differing ploidy states or genetic backgrounds of the models studied or the use of CRISPR/Cas9 vs. siRNA systems (Table S3). For instance, TP53 was identified in the Sansregret screen, but not in our screen, where the TNBC models already harbor TP53 mutations, like nearly all TNBC tumors. Although we did not identify ANAPC1 and UBE2C, the APC/C components ANAPC13, ANAPC15, and CDC20 were uniquely identified in our screens, as were other genes implicated in progression to anaphase or mitotic exit: MAD2L1BP/p31(comet), DYNC1LI1, DYNC1LI2, TRIP13, and RNF8 (30–34). Importantly, siRNA knockdown of ANAPC15 and MAD2L1BP, two of the top candidates identified in our screens, have been shown to delay mitotic progression in HeLa and RPE1 cells (35–37) providing mechanistic insight for their association with TTKi resistance and corroborating our mechanistic studies. The shared finding of the APC/C as a central mediator of resistance to TTK inhibition, despite the differences in approach and cellular contexts, lends strong support to the biological importance of these discoveries.

Also relevant to our findings, Wild et al. (14) studied the impact of deletion of the E2 ubiquitin-conjugating enzymes, UBE2C and UBE2S, on APC/C function in HCT116 cells. These E2s are used by the APC/C to ubiquitinate mitotic proteins, including CCNB1 and securin, whose degradation is required for mitotic exit (22). Concordant with our findings, Wild et al. (14) showed that UBE2C and UBE2S deletion weakened APC/C function and elongated NEBD to anaphase time, rendering cells insensitive to reversine or deletion of the spindle assembly checkpoint gene, MAD2. Collectively, these data support the hypothesis that prolonging anaphase onset provides time for cancer cells to avoid otherwise lethal mitotic segregation errors induced by TTK inhibition. Our study provides independent support of these findings, but does so in multiple aneuploid cancer models, which is the clinically relevant disease being targeted by TTKi in development. Moreover, we demonstrated that this mechanism confers resistance not only to CFI-402257, a clinical TTKi, but also several other selective TTKis.

To extend these mechanism-based discoveries toward predictors of TTKi response that could be applied clinically, we pursued a gene expression-based approach, with the rationale that gene expression might capture various alterations affecting the mitotic exit pathway, and supported by the observation that gene expression predictors are often the strongest predictors of cancer dependencies (38). To do so, we assembled a metagene expression signature based on the biological findings from our functional genomic screens. The metagene comprised 16 APC/C complex components and MAD2L1BP, another governor of anaphase progression identified by our screens. Analysis of this metagene in both breast and lung cancer cell lines revealed a significant association with response to CFI-402257: models with low APC/C metagene scores (i.e., low expression of APC/C and MAD2L1BP genes) exhibited relative resistance to TTK inhibition, consistent with our CRISPR/Cas9 screen findings. Subsequent analyses revealed that a two-gene signature of CDC20 and ANAPC4 expression alone was even more strongly associated with CFI-402257 response in breast cancer cell lines. Interestingly, we observed the strongest TTKi resistance phenotypes with ANAPC4 depletion in our validation studies.

To investigate the potential clinical utility of the APC/C metagene for stratifying or selecting patients for TTKi therapy, we assessed the reduced metagene signature in 11 different tumor types from TCGA’s pan-cancer dataset. We observed substantial variability in metagene scores both across and within different tumor types, and identified outliers with very low scores in multiple tumor types. These markers could potentially indicate patients with intrinsic resistance to CFI-402257. Characterization of these APC/C low cancers may reveal alternative vulnerabilities that could be exploited (29). Assessment of the APC/C metagene, other biomarkers of APC/C functional capacity, or somatic alterations in components of the APC/C pathway in ongoing clinical trials will determine the clinical significance of our findings. If validated in the clinic, these discoveries could have an important impact on the successful development of TTKis, such as CFI-402257, as novel cancer therapeutics for TNBC and other cancers.

Methods

Cell Lines.

The breast cancer cell line (39) and the lung adenocarcinoma cell line (40) panels were generous gifts from Drs. Benjamin Neel and Adi Gazdar, respectively. Cas9 was introduced into MDA-MB-231, MDA-MB-468, and MDA-MB-436 using lenti-Cas9-blast (52962; Addgene). For MDA-MB-231 and MDA-MB-468, cells stably expressing Cas9 were subcloned to select lines with efficient Cas9 editing activity, evaluated by transduction of cells with sgRNAs targeting essential genes followed by assessment of cell viability. A nonclonal Cas9 expressing population of MDA-MB-436 cells was used for the screens.

CRISPR/Cas9 Screens.

The Toronto Human Knockout pooled library (TKO) was a gift from Dr. Jason Moffat (1000000069; Addgene) (18). Cas9-expressing cell lines were transduced with the TKO library at low multiplicity of infection to ensure single viral integrations per cell with 200× library coverage. Following puromycin selection, library infected cells were expanded for 7–10 d. Genomic DNA (gDNA) was harvested to determine baseline library representation and cells were plated at densities to maintain 200× library coverage at the onset of CFI-402257 or DMSO (vehicle) treatments. For each cell line, three doses ranging from IC60–IC90 concentrations were attempted. Cas9 lines transduced with sgLacZ were used as a negative control to ensure that screen drug doses resulted in cell death. During the screens, cells were cultured as usual and counted at each passage to monitor cell doublings for 30–50 d. At the end of the screen, gDNA was extracted from CFI-402257–treated cells and doubling-matched DMSO controls, and together with baseline gDNA, was subjected to targeted sequencing of the sgRNA locus. Enriched sgRNAs were identified using the MAGeCK algorithm (19), and Gene Ontology analyses were conducted using Enrichr (20, 21).

Candidate Gene Validation Studies.

To validate candidate genes, MDA-MB-231 and MDA-MB-436 were transduced with lentiCRISPR-V2 (LCV2) encoding Cas9 and the candidate gene-targeting sgRNAs identified as most significantly enriched in our screens. sgRNA sequences were as follows: ANAPC4, CCTGCAGCATCTAGTCCAAG; ANAPC13, CCTGAACCTGAACAAGACAA; MAD2L1BP, ACTTGAGACAAGCTCTACGC; and GFP (negative control), GGGGCGAGGAGCTGTTCACCG. Editing of candidate genes in LCV2 lines was confirmed by TA-cloning and sequencing of the sgRNA-target sites. As an orthogonal approach, we conducted siRNA knockdowns to confirm their effects on CFI-402257 response using ON-TARGETplus SMARTpools (Dharmacon). Lipofectamine 3000 (Thermo Fisher Scientific) was used to deliver 10 nM siRNA or nontargeting control (siNTC) to cells. Knockdown efficiencies were determined using qPCR and Western blot analysis (anti-ANAPC4, A301-176A, Bethyl Laboratories; anti-MAD2L1BP, sc-134381, Santa Cruz Biotechnology) at 48–72 h posttransfection.

Drug Response Assays.

Response of cell lines to TTKi (CFI-402257, MPI-0479605, NMS-P715, and Mps-Bay2a) was evaluated using colony survival and SRB assays. For colony assays, cells were seeded sparsely and treated with DMSO or TTKi for 10–14 d, and then fixed and stained with SRB. For quantification, SRB was solubilized with 10 mM Tris⋅HCl, and absorbance was quantified on a spectrophotometer. For SRB dose–response assays, cells were seeded in 96-well plates and treated with serial drug dilutions. After 5 d of treatment, cells were fixed, stained with SRB, and solubilized, and absorbance was quantified on a spectrophotometer. CFI-402257 was synthesized as described previously (10), and MPI-0479605, NMS-P715, and Mps-Bay2a were synthesized by the Campbell Family Institute for Breast Cancer Research.

Live-Cell, Time-Lapse Microscopy.

Cells were synchronized with double thymidine block, plated in Eppendorf chamber slides, and released into 167 nM siR-DNA stain (Cytoskeleton) and CFI-402257 at 150 nM or DMSO for a minimum of 4 h before imaging. Cells were held in a humidified Chamlide stage incubator kept at 37 °C and 5% CO2 (Live Cell Instrument). Time-lapse images were captured using Volocity 6.3 software (Quorum Technologies) on a Yokogawa spinning disk confocal microscope (Quorum Technologies) equipped with a Hamamatsu ImageEM EM-CCD camera at 20× magnification every 4 min for 20–28 h. The time from NEBD to anaphase was recorded for each dividing cell. For all dividing cells, mitoses were scored as normal or abnormal (i.e., endoreduplication, lagging chromosomes, anaphase bridge, or multipolar divisions).

Flow Cytometry.

Induction of aneuploidy and apoptosis after 72 h of treatment with CFI-402257 were measured by PI and annexin-V (AnV) combined with PI staining, respectively. To assess drug-induced apoptosis, cells were collected following treatment, fixed, and stained with AnV-FITC at 2.25 µg/mL (BioLegend) and PI at 10 µg/mL (Sigma-Aldrich), and measured on a BD FACSCanto II flow cytometer. For ploidy analysis, viable cells were fixed with ethanol, stained with PI (10 µg/mL), and measured on a BD FACSCanto II flow cytometer. FlowJo software was used to quantify the proportion of AnV+PI− and AnV+PI+ cells as a readout of apoptosis, and to determine the fraction of cells with 2n, 4n, or >4n DNA content based on PI staining.

Pharmacogenomic Analyses.

CFI-402257 dose–response curves were generated for a panel of 52 breast cancer cell lines and 20 lung adenocarcinoma cell lines. The PharmacoGx pipeline was used to generate drug response metrics for each cell line, including area above the drug dose–response curve (AAC) (41–45). Drug response data were integrated with publicly available gene expression profiles to evaluate the association between cell line CFI-402257 sensitivity (AAC) and a gene set comprising 16 APC/C genes and MAD2L1BP using GSEA (24). All genes in the genome were ranked according to their univariate association with CFI-402257 response and entered into GSEA. GSEA was run with the 17-gene APC/C-MAD2L1BP gene list submitted as a gene set for testing enrichment compared with one million random permutations of the ranked gene list. Metagene scores were defined as the mean expression of the genes composing them (e.g., 17 genes composing the APC/C-MAD2L1BP gene set, or ANAPC4 and CDC20 in the two-gene metagene). Breast cancer cell line gene expression profiles were obtained from Marcotte et al. (39), and lung adenocarcinoma cell line gene expression profiles were obtained from the Cancer Cell Line Encyclopedia (CCLE) (46). All gene expression profiles were reprocessed from raw data files using the Kallisto pipeline (47). TCGA gene expression profiles were obtained from University of California Santa Cruz Xena browser (xena.ucsc.edu), and genetic analyses were conducted using the Nature 2012 breast cancer cohort in cBioPortal (48, 49).

Research Reproducibility.

The genomic data used in this study are publicly available through our PharmacoGx platform. CCLE raw data are available at https://portals.broadinstitute.org/ccle/. The raw RNA-seq data for the breast cancer cell line panel are available from the National Center for Biotechnology Information’s Gene Expression Omnibus (accession no. GSE73526). Our code and documentation are open-source and publicly available through the GitHub repository (https://github.com/bhklab/). A detailed tutorial describing how to run our pipeline and reproduce our analysis results is available in the GitHub repository.

Supplementary Material

Supplementary File
pnas.201719577SI.pdf (1.4MB, pdf)

Acknowledgments

We thank Dr. Troy Ketela and members of the T.W.M. laboratory and Pelletier laboratory for experimental discussions, Dr. Jacqueline Mason and the CFIBCR Therapeutics group for providing drugs and scientific input, Drs. Benjamin Neel and Adi Gazdar for sharing cancer cell lines, The Cancer Genome Atlas for data access, and the Advanced Optical Microscopy Facility for technical support. This work was supported by the Terry Fox Research Institute, Canadian Institutes of Health Research, the Princess Margaret Cancer Foundation, and Stand Up To Cancer Canada–Canadian Breast Cancer Foundation Breast Cancer Dream Team Research Funding, with supplemental support of the Ontario Institute for Cancer Research through funding provided by the Government of Ontario (Funding Award SU2C-AACR-DT-18-15). Stand Up To Cancer Canada is a program of the Entertainment Industry Foundation Canada. Research funding is administered by the American Association for Cancer Research International–Canada, the Scientific Partner of SU2C Canada.

Footnotes

The authors declare no conflict of interest.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1719577115/-/DCSupplemental.

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Supplementary Materials

Supplementary File
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