TTK protein kinase (also known as MPS1; IC50 = 1.7 nM)

CFI-402257 Accelerates Mitosis and Induces Mitotic Segregation Errors and Apoptosis in TNBC. [1]
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, 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. 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 inhibitiondriven abrogation of the SAC, which accelerates mitotic progression and induces mitotic errors, aneuploidy, and apoptosis, consistent with reports for other TTKis. Genome-Wide CRISPR/Cas9 Screen Reveals APC/C Impairment Confers Resistance to CFI-402257. [1]
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. 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). 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). 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. 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. Inactivation of ANAPC4, ANAPC13, and MAD2L1BP Confers Resistance to Multiple TTKis. [1]
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). 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). We next asked whether genetic manipulation of ANAPC4, ANAPC13, and MAD2L1BP affected sensitivity to additional published selective TTKis, including MPI-0479605, NMS-P715 and Mps-Bay2a. 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). Response to CFI-402257 Is Associated with Reduced APC/C Gene Expression Signature in Breast and Lung Cancer Cell Lines. [1]
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/CMAD2L1BP 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). 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. 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.

1. Mitotic Timing & Error Analysis:
o TNBC cells (MDA-MB-231/468/436) synchronized via double-thymidine block.
o Treated with CFI-402257 (150 nM) or DMSO control.
o Live-cell microscopy measured time from nuclear envelope breakdown (NEBD) to anaphase onset.
o Mitotic errors (lagging chromosomes, anaphase bridges, multipolar divisions) quantified.

2. DNA Content & Aneuploidy Induction:
o Cells treated with CFI-402257 (100–400 nM, 72 h).
o Propidium iodide (PI) staining + flow cytometry to assess >4n DNA content.

3. Apoptosis Assay:
o Annexin-V/PI staining after CFI-402257 treatment (72 h).
o Flow cytometry to quantify apoptotic cells (Annexin V⁺).

4. Genome-Wide CRISPR/Cas9 Resistance Screens:
o Cas9-expressing TNBC lines transduced with Toronto Human Knockout Library.
o Positive selection under CFI-402257 pressure (3 doses per cell line).
o MAGeCK algorithm identified enriched sgRNAs in resistant populations.

5. Functional Validation (siRNA/CRISPR):
o siRNA knockdown or CRISPR knockout of ANAPC4, ANAPC13, and MAD2L1BP.
o Colony survival assays to confirm CFI-402257 resistance.
o Mechanistic analysis: Mitotic timing, apoptosis, and DNA content post-knockdown.

6. Cross-Resistance to Other TTKis:
o Dose-response assays (SRB) for CFI-402257, MPI-0479605, NMS-P715, Mps-Bay2a.
o Resistance validation in ANAPC4/ANAPC13/MAD2L1BP-knockdown cells.

7. Pharmacogenomic Profiling:
o CFI-402257 sensitivity (AAC) tested in 52 breast/20 lung cancer cell lines. o GSEA linked APC/C gene signature (16 genes + MAD2L1BP) to drug response.[1]

Disruption of the anaphase-promoting complex confers resistance to TTK inhibitors in triple-negative breast cancer. Proc Natl Acad Sci U S A. 2018 Feb 13;115(7):E1570-E1577. doi: 10.1073/pnas.1719577115.

Luvixasertib is an orally bioavailable selective bispecific protein kinase TTK (monopolar spindle 1 kinase, Mps1) inhibitor with potential antitumor activity. Upon administration, luvixasertib selectively binds to and inhibits Mps1 activity. This inactivates the spindle assembly checkpoint (SAC) and accelerates mitosis, leading to chromosome misalignment and segregation errors, as well as instability of the mitotic checkpoint complex. This can induce death in Mps1-overexpressing cancer cells. Mps1 is a tyrosine and serine/threonine kinase expressed in proliferating normal tissues and is essential for normal SAC function and chromosome alignment. Mps1 is overexpressed in a variety of human tumors and plays a crucial role in the uncontrolled growth of tumor cells.

C28H30N6O3

498.5762

497.242

C, 70.00; H, 6.28; N, 14.07; O, 9.65

1610759-22-2

1610759-22-2;1610677-37-6 (HCl);

118086034

White to off-white solid powder

3.6

3

7

8

37

805

0

O([H])C1(C([H])([H])[H])C([H])([H])C([H])(C([H])([H])N([H])C2=C([H])C(=NC3=C(C([H])=NN23)C2C([H])=C([H])C(=C(C([H])([H])[H])C=2[H])C(N([H])C2([H])C([H])([H])C2([H])[H])=O)OC2=C([H])N=C([H])C([H])=C2[H])C1([H])[H]

UEFIRPJHDWPZBI-CGSFZAOMSA-N

InChI=1S/C29H31N5O3/c1-18-11-20(6-9-23(18)28(35)33-21-7-8-21)24-17-32-34-25(24)12-22(37-27-5-3-4-10-30-27)13-26(34)31-16-19-14-29(2,36)15-19/h3-6,9-13,17,19,21,31,36H,7-8,14-16H2,1-2H3,(H,33,35)/t19-,29+

N-cyclopropyl-4-(7-((((1s,3s)-3-hydroxy-3-methylcyclobutyl)methyl)amino)-5-(pyridin-2-yloxy)pyrazolo[1,5-a]pyridin-3-yl)-2-methylbenzamide

CFI402257 CFI 402257 CFI-402257

2934.99.9001

Powder      -20°C    3 years

                     4°C     2 years

In solvent   -80°C    6 months

                  -20°C    1 month

Room temperature (This product is stable at ambient temperature for a few days during ordinary shipping and time spent in Customs)

May dissolve in DMSO (in most cases), if not, try other solvents such as H2O, Ethanol, or DMF with a minute amount of products to avoid loss of samples

Note: Listed below are some common formulations that may be used to formulate products with low water solubility (e.g. < 1 mg/mL), you may test these formulations using a minute amount of products to avoid loss of samples.

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Injection Formulation 1: DMSO : Tween 80： Saline = 10 : 5 : 85 (i.e. 100 μL DMSO stock solution → 50 μL Tween 80 → 850 μL Saline)
*Preparation of saline: Dissolve 0.9 g of sodium chloride in 100 mL ddH ₂ O to obtain a clear solution.
Injection Formulation 2: DMSO : PEG300 ：Tween 80 : Saline = 10 : 40 : 5 : 45 (i.e. 100 μL DMSO → 400 μLPEG300 → 50 μL Tween 80 → 450 μL Saline)
Injection Formulation 3: DMSO : Corn oil = 10 : 90 (i.e. 100 μL DMSO → 900 μL Corn oil)
Example: Take the Injection Formulation 3 (DMSO : Corn oil = 10 : 90) as an example, if 1 mL of 2.5 mg/mL working solution is to be prepared, you can take 100 μL 25 mg/mL DMSO stock solution and add to 900 μL corn oil, mix well to obtain a clear or suspension solution (2.5 mg/mL, ready for use in animals).

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Injection Formulation 4: DMSO : 20% SBE-β-CD in saline = 10 : 90 [i.e. 100 μL DMSO → 900 μL (20% SBE-β-CD in saline)]
*Preparation of 20% SBE-β-CD in Saline (4°C，1 week): Dissolve 2 g SBE-β-CD in 10 mL saline to obtain a clear solution.
Injection Formulation 5: 2-Hydroxypropyl-β-cyclodextrin : Saline = 50 : 50 (i.e. 500 μL 2-Hydroxypropyl-β-cyclodextrin → 500 μL Saline)
Injection Formulation 6: DMSO : PEG300 : castor oil : Saline = 5 : 10 : 20 : 65 (i.e. 50 μL DMSO → 100 μLPEG300 → 200 μL castor oil → 650 μL Saline)
Injection Formulation 7: Ethanol : Cremophor : Saline = 10： 10 : 80 (i.e. 100 μL Ethanol → 100 μL Cremophor → 800 μL Saline)
Injection Formulation 8: Dissolve in Cremophor/Ethanol (50 : 50), then diluted by Saline
Injection Formulation 9: EtOH : Corn oil = 10 : 90 (i.e. 100 μL EtOH → 900 μL Corn oil)
Injection Formulation 10: EtOH : PEG300：Tween 80 : Saline = 10 : 40 : 5 : 45 (i.e. 100 μL EtOH → 400 μLPEG300 → 50 μL Tween 80 → 450 μL Saline)

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Oral Formulation 1: Suspend in 0.5% CMC Na (carboxymethylcellulose sodium)
Oral Formulation 2: Suspend in 0.5% Carboxymethyl cellulose
Example: Take the Oral Formulation 1 (Suspend in 0.5% CMC Na) as an example, if 100 mL of 2.5 mg/mL working solution is to be prepared, you can first prepare 0.5% CMC Na solution by measuring 0.5 g CMC Na and dissolve it in 100 mL ddH2O to obtain a clear solution; then add 250 mg of the product to 100 mL 0.5% CMC Na solution, to make the suspension solution (2.5 mg/mL, ready for use in animals).

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Oral Formulation 3: Dissolved in PEG400
Oral Formulation 4: Suspend in 0.2% Carboxymethyl cellulose
Oral Formulation 5: Dissolve in 0.25% Tween 80 and 0.5% Carboxymethyl cellulose
Oral Formulation 6: Mixing with food powders

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Note: Please be aware that the above formulations are for reference only. InvivoChem strongly recommends customers to read literature methods/protocols carefully before determining which formulation you should use for in vivo studies, as different compounds have different solubility properties and have to be formulated differently.

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 (Please use freshly prepared in vivo formulations for optimal results.)