Intimal sarcoma is an extremely rare, life-threatening malignant neoplasm. Murine double minute 2 (MDM2) amplification is observed in >70% of intimal sarcomas. Milademetan, an MDM2 inhibitor, may provide clinical benefit in this patient population. We conducted a phase Ib/II study in patients with MDM2-amplified, wild-type TP53 intimal sarcoma as a substudy of a large nationwide registry for rare cancers in Japan. Milademetan (260 mg) was administered orally once daily for 3 days every 14 days, twice in a 28-day cycle. Of 11 patients enrolled, 10 were included in the efficacy analysis. Two patients (20%) showed durable responses for >15 months. Antitumor activity correlated with TWIST1 amplification (P = 0.028) and negatively with CDKN2A loss (P = 0.071). Acquired TP53 mutations were detected in sequential liquid biopsies as a novel exploratory resistance mechanism to milademetan. These results suggest that milademetan could be a potential therapeutic strategy for intimal sarcoma.

Significance:

Strategies to optimize outcomes could include the use of new biomarkers (TWIST1 amplification and CDKN2A loss) to select patients with MDM2-amplified intimal sarcoma who might benefit from milademetan and combination with other targeted treatments. Sequential liquid biopsy of TP53 can be used to evaluate disease status during treatment with milademetan.

See related commentary by Italiano, p. 1765.

This article is highlighted in the In This Issue feature, p. 1749

Intimal sarcoma is an extremely rare mesenchymal neoplasm that originates from large blood vessels and the heart and is one of the most common primary cardiac malignant histologies (refs. 1, 2; Supplementary Table S1). Patients with intimal sarcoma have poor outcomes, with a reported median overall survival (OS) of 8 to 13 months (3). Intimal sarcoma is a tumor characterized by murine double minute 2 (MDM2) nuclear overexpression and amplification of the 12q12–15 region [containing the cyclin-dependent kinase (CDK4) and MDM2 genes; ref. 4]. We speculated that MDM2 inhibition may be a potential therapeutic strategy for this disease.

In human tumors that retain tumor suppressor protein p53, its activity is frequently inhibited by intermolecular interactions between p53 and MDM2, forming a regulatory feedback loop. In normal, unstressed cells, MDM2 maintains a low level of p53 activity by promoting p53 export from the nucleus and p53 proteasome-mediated degradation through its E3 ubiquitin ligase activity (5). In the presence of stress, p53 is activated and subsequently acts as a transcription factor that modulates the expression of various genes, including MDM2 (6). The MDM2 binding domain on p53 overlaps with the transcriptional activation domain of p53, thereby inhibiting the activity of p53. In human tumors, disruption of the MDM2/p53 balance through overexpression and/or oncogenic activation of MDM2 promotes tumorigenesis and tumor growth by preventing p53 function. Pharmacologic inhibition of MDM2 and wild-type p53 interaction in tumor cells can sustain the increase in p53 activity and subsequent antitumor activity (7, 8). Pharmacologic restoration of the p53 pathway may represent an effective strategy for cancer therapy targeting a wide array of human cancers that retain the wild-type p53 (9).

Milademetan (DS3032, RAIN-32) is a novel, specific, small-molecule MDM2 inhibitor that disrupts MDM2 and p53 interactions in tumor cells. It is now under development as an oral drug for cancer treatment (10). p53 plays an essential role in preventing neoplasia by inducing cell-cycle arrest or apoptosis in cells undergoing various physiologic stresses. Inactivation of p53 by mutation occurs in many human tumors, resulting in a loss of tumor suppressor activity, thereby removing a pivotal barrier to neoplastic development. In many early clinical studies, patients were originally stratified for MDM2 inhibitors based on their p53 status (11–15). Although the activation of p53 is almost universal after MDM2 inhibition, the outcomes range from cell-cycle arrest to apoptosis in vitro, depending on the cell type, dose, and exposure duration (16–18). No remarkable antitumor activity has been achieved in patients with solid tumors harboring wild-type TP53 in clinical studies (11–15). To stratify patients who will benefit from MDM2 inhibition, it is necessary to identify criteria other than the simple TP53 wild-type or mutation status that governs cellular response to such treatment. Dedifferentiated liposarcoma patient-derived xenografts harboring MDM2 amplification were reported to show antitumor activity, suggesting that MDM2 amplification may serve as a biomarker for MDM2 inhibitors (19). However, the determinants of response and resistance have not been comprehensively identified. Our study focused on intimal sarcomas harboring MDM2 amplification and wild-type TP53.

We conducted an investigator-initiated phase Ib/II study to evaluate the activity of milademetan in patients with MDM2-amplified intimal sarcoma as a substudy of a large nationwide registry for rare cancers in Japan (MASTERKEY Project; Supplementary Fig. S1). Whole-exome sequencing (WES) and RNA sequencing (RNA-seq) analyses of archived tumor tissue samples and targeted sequencing analysis of cell-free DNA (cfDNA) samples (liquid biopsy) were performed to identify the determinants of response and resistance.

Patient Demographics and Baseline Characteristics

Eleven patients were enrolled in the safety lead-in (n = 3) and expansion cohorts (n = 8) from December 28, 2018, to July 17, 2020. One patient was excluded from the response assessment because of the detection of a TP53 mutation revealed after enrollment (Fig. 1). The patient characteristics are shown in Table 1.

Figure 1.

Consort diagram.

Figure 1.

Consort diagram.

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Table 1.

Patient characteristics

CharacteristicsOverall (n = 11)
Median age in years (range) 33.0 (20–72) 
Gender 
 Female    8 (72.7) 
 Male    3 (27.3) 
ECOG PS 
 0    6 (54.5) 
 1    5 (45.5) 
 2    0 (0) 
Stage at the time of treatment start 
 Locally advanced/metastatic (palliative intent)   11 (100) 
 Localized (curative intent)    0 (0) 
Primary site 
 Large vessel    5 (45.5) 
  Pulmonary artery    5 (45.5) 
  Aorta    0 (0) 
 Heart    6 (54.5) 
  Left atrium    6 (54.5) 
  Right atrium    0 (0) 
 Other site    0 (0) 
Prior surgery   11 (100) 
Prior radiation    2 (18.2) 
 Primary lesion    2 (18.2) 
 Metastatic lesion    0 (0) 
Number of prior lines of systemic chemotherapy 
 1    2 (18.2) 
 2    3 (27.3) 
CharacteristicsOverall (n = 11)
Median age in years (range) 33.0 (20–72) 
Gender 
 Female    8 (72.7) 
 Male    3 (27.3) 
ECOG PS 
 0    6 (54.5) 
 1    5 (45.5) 
 2    0 (0) 
Stage at the time of treatment start 
 Locally advanced/metastatic (palliative intent)   11 (100) 
 Localized (curative intent)    0 (0) 
Primary site 
 Large vessel    5 (45.5) 
  Pulmonary artery    5 (45.5) 
  Aorta    0 (0) 
 Heart    6 (54.5) 
  Left atrium    6 (54.5) 
  Right atrium    0 (0) 
 Other site    0 (0) 
Prior surgery   11 (100) 
Prior radiation    2 (18.2) 
 Primary lesion    2 (18.2) 
 Metastatic lesion    0 (0) 
Number of prior lines of systemic chemotherapy 
 1    2 (18.2) 
 2    3 (27.3) 

Abbreviation: ECOG PS, Eastern Cooperative Oncology Group performance status.

The median age was 33.0 years (range, 20–72 years), and five patients had prior systemic therapies, including doxorubicin. All patients (n = 11) underwent primary resection. One patient underwent postoperative radiotherapy. Seven patients had local recurrence at enrollment, and eight had distant metastases (Supplementary Table S2). Targeted DNA sequencing was performed using archived tumor tissue samples prior to enrollment in six patients and after enrollment in two patients (Nos. 6 and 8), and amplified MDM2 was detected in all patients (Table 2). The median follow-up was 10.4 months (interquartile range, 4.4–22.6 months).

Table 2.

Baseline genomic alteration by targeted DNA sequencing testing and efficacy

No.Pathogenic alterationBest responseBest response SD >3 monthsPFS (months)
CDK amp, MDM2 amp, KIT amp, KDR amp, PDGFR amp, RICTOR amp, MSI/TMB not reported SD Yes 6.3 
CDK4 amp, MDM2 amp, PTCH L39fs*51, MSI-low, TMB-low SD Yes 9.0 
— SD Yes 8.9 
AKT2 amp, ATRX loss, CDK4 amp, ERBB3 amp, MDM2 amp, MSI/TMB not reported PD No 1.4 
FGF10 amp, MAP2K1 amp, MDM2 amp, MSI/TMB not reported PR Yes 16.8 
ARF amp, CDKN2A loss, MDM2 amp, MTAP loss, PDGFRA amp, TP53A189V, MSI/TMB not reported N/Aa N/Aa N/Aa 
— PD No 2.2 
CDK4 amp, FANCAW903*, KIT amp, KDR amp, KRAS amp, MDM2 amp, PDGFRA amp, RICTOR amp, RAD51 M1fs*8, MSI/TMB not reported PD No 1.4 
— SD Yes 4.0 
10 ARPC3–NOTCH2, CCND1 amp, CCND3 amp, CDK4 amp, ERBB3 amp, KIT amp, KDR amp, MDM2 amp, NOTCH2 amp, NSD3 amp, PDGFRA amp, PIM1 amp, RICTOR1 amp, VEGFA amp, MSI not determined, TMB-low PR Yes 24.9b 
11 CCND2 amp, CCND3 amp, CDKN2A loss, FGF23 amp, FGF6 amp, IRF4 amp, KDM5A amp, KDR amp, KIT amp, MTAP loss, MDM2 amp, PDGFRA amp, RAD52 amp, RICTOR amp, MSI-low, TMB-low PD No 1.9 
No.Pathogenic alterationBest responseBest response SD >3 monthsPFS (months)
CDK amp, MDM2 amp, KIT amp, KDR amp, PDGFR amp, RICTOR amp, MSI/TMB not reported SD Yes 6.3 
CDK4 amp, MDM2 amp, PTCH L39fs*51, MSI-low, TMB-low SD Yes 9.0 
— SD Yes 8.9 
AKT2 amp, ATRX loss, CDK4 amp, ERBB3 amp, MDM2 amp, MSI/TMB not reported PD No 1.4 
FGF10 amp, MAP2K1 amp, MDM2 amp, MSI/TMB not reported PR Yes 16.8 
ARF amp, CDKN2A loss, MDM2 amp, MTAP loss, PDGFRA amp, TP53A189V, MSI/TMB not reported N/Aa N/Aa N/Aa 
— PD No 2.2 
CDK4 amp, FANCAW903*, KIT amp, KDR amp, KRAS amp, MDM2 amp, PDGFRA amp, RICTOR amp, RAD51 M1fs*8, MSI/TMB not reported PD No 1.4 
— SD Yes 4.0 
10 ARPC3–NOTCH2, CCND1 amp, CCND3 amp, CDK4 amp, ERBB3 amp, KIT amp, KDR amp, MDM2 amp, NOTCH2 amp, NSD3 amp, PDGFRA amp, PIM1 amp, RICTOR1 amp, VEGFA amp, MSI not determined, TMB-low PR Yes 24.9b 
11 CCND2 amp, CCND3 amp, CDKN2A loss, FGF23 amp, FGF6 amp, IRF4 amp, KDM5A amp, KDR amp, KIT amp, MTAP loss, MDM2 amp, PDGFRA amp, RAD52 amp, RICTOR amp, MSI-low, TMB-low PD No 1.9 

Abbreviations: amp, amplification; MSI, microsatellite instability; N/A, not applicable; PD, progressive disease; PFS, progression-free survival; PR, partial response; SD, stable disease; TMB, tumor mutation burden.

aDetection of TP53 mutation after enrollment.

bOngoing as of May 1, 2022.

Safety

Eleven patients received one or more cycles of milademetan and were included in the safety analysis. The most common all-grade treatment-emergent adverse events (TEAE) were bone marrow suppression, including decreased platelet count [100% (grades 3–4, 90.9%)], decreased neutrophil count [90.9% (grades 3–4, 72.8%)], and anemia [72.7% (grades 3–4, 36.4%)], and gastrointestinal toxicity, including anorexia [90.9% (grades 3–4, 9.1%)] and nausea [72.7% (grades 3–4, 27.3%); see Table 3].

Table 3.

TEAEs by maximum grade (n = 11)

AEAny grade N (%)Grade 1 N (%)Grade 2 N (%)Grade 3 N (%)Grade 4 N (%)
Decreased platelet count 11 (100) 0 (0) 1 (9.1) 6 (54.5) 4 (36.4) 
Decreased neutrophil count 10 (90.9) 0 (0) 2 (18.2) 4 (36.4) 4 (36.4) 
Anorexia 10 (90.9) 5 (45.5) 4 (36.4) 1 (9.1) 0 (0) 
Anemia  8 (72.7) 2 (18.2) 2 (18.2) 4 (36.4) 0 (0) 
Nausea  8 (72.7) 2 (18.2) 3 (27.3) 3 (27.3) 0 (0) 
Decreased WBC count  8 (72.7) 0 (0) 2 (18.2) 4 (36.4) 2 (18.2) 
Decreased lymphocyte count  6 (54.5) 1 (9.1) 2 (18.2) 2 (18.2) 1 (9.1) 
Alopecia  5 (45.5) 5 (45.5) 0 (0) 0 (0) 0 (0) 
Vomiting  3 (27.3) 1 (9.1) 2 (18.2) 0 (0) 0 (0) 
Constipation  2 (18.2) 1 (9.1) 1 (9.1) 0 (0) 0 (0) 
Diarrhea  2 (18.2) 1 (9.1) 1 (9.1) 0 (0) 0 (0) 
Dysgeusia  2 (18.2) 2 (18.2) 0 (0) 0 (0) 0 (0) 
Fatigue  2 (18.2) 1 (9.1) 0 (0) 1 (9.1) 0 (0) 
Hypoalbuminemia  2 (18.2) 2 (18.2) 0 (0) 0 (0) 0 (0) 
Malaise  2 (18.2) 1 (9.1) 1 (9.1) 0 (0) 0 (0) 
Increased ALT  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Increased AST  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Febrile neutropenia  1 (9.1) 0 (0) 0 (0) 1 (9.1) 0 (0) 
GERD  1 (9.1) 0 (0) 1 (9.1) 0 (0) 0 (0) 
Fever  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Rash  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Maculopapular rash  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Stomatitis  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Upper respiratory infection  1 (9.1) 0 (0) 1 (9.1) 0 (0) 0 (0) 
Lower GI bleeding  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
AEAny grade N (%)Grade 1 N (%)Grade 2 N (%)Grade 3 N (%)Grade 4 N (%)
Decreased platelet count 11 (100) 0 (0) 1 (9.1) 6 (54.5) 4 (36.4) 
Decreased neutrophil count 10 (90.9) 0 (0) 2 (18.2) 4 (36.4) 4 (36.4) 
Anorexia 10 (90.9) 5 (45.5) 4 (36.4) 1 (9.1) 0 (0) 
Anemia  8 (72.7) 2 (18.2) 2 (18.2) 4 (36.4) 0 (0) 
Nausea  8 (72.7) 2 (18.2) 3 (27.3) 3 (27.3) 0 (0) 
Decreased WBC count  8 (72.7) 0 (0) 2 (18.2) 4 (36.4) 2 (18.2) 
Decreased lymphocyte count  6 (54.5) 1 (9.1) 2 (18.2) 2 (18.2) 1 (9.1) 
Alopecia  5 (45.5) 5 (45.5) 0 (0) 0 (0) 0 (0) 
Vomiting  3 (27.3) 1 (9.1) 2 (18.2) 0 (0) 0 (0) 
Constipation  2 (18.2) 1 (9.1) 1 (9.1) 0 (0) 0 (0) 
Diarrhea  2 (18.2) 1 (9.1) 1 (9.1) 0 (0) 0 (0) 
Dysgeusia  2 (18.2) 2 (18.2) 0 (0) 0 (0) 0 (0) 
Fatigue  2 (18.2) 1 (9.1) 0 (0) 1 (9.1) 0 (0) 
Hypoalbuminemia  2 (18.2) 2 (18.2) 0 (0) 0 (0) 0 (0) 
Malaise  2 (18.2) 1 (9.1) 1 (9.1) 0 (0) 0 (0) 
Increased ALT  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Increased AST  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Febrile neutropenia  1 (9.1) 0 (0) 0 (0) 1 (9.1) 0 (0) 
GERD  1 (9.1) 0 (0) 1 (9.1) 0 (0) 0 (0) 
Fever  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Rash  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Maculopapular rash  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Stomatitis  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 
Upper respiratory infection  1 (9.1) 0 (0) 1 (9.1) 0 (0) 0 (0) 
Lower GI bleeding  1 (9.1) 1 (9.1) 0 (0) 0 (0) 0 (0) 

Abbreviations: AE, adverse event; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GERD, gastroesophageal reflux disease; GI, gastrointestinal; WBC, white blood cell.

One patient (No. 1) withdrew from the study before the initiation of the fourth cycle owing to a prolonged platelet count decrease (grade 4). All patients (n = 11) experienced treatment interruption due to grades 4 (n = 4), 3 (n = 6), and 2 (n = 1) decreased platelet count. Ten of the 11 patients needed a dose reduction: six for decreased platelet count, three for nausea, and one for fatigue. Of the four patients treated with milademetan for more than 6 months, three experienced two levels of dose reduction (120 mg) and one experienced one level of dose reduction (200 mg). No treatment-related mortalities and cardiotoxicities were observed.

Pharmacokinetics

The overall pharmacokinetic (PK) profiles of milademetan are presented in Supplementary Table S3A. The PK profile of each patient is presented in Supplementary Table S3B. The median time of the maximum observed plasma concentration (Tmax) was 3.7 hours (2.4–8.0 hours). Milademetan was cleared from the plasma, with a mean terminal elimination phase half-life (T1/2) of 8.9 to 60.8 hours (Supplementary Fig. S2). Nine patients (Nos. 3–11) who received prophylactic administration of aprepitant for antiemesis had lower clearance than the remaining two patients (Nos. 1 and 2) who did not receive prophylactic administration.

Antitumor Activity

Of the 10 patients treated with milademetan, two achieved partial responses (PR) for an overall response rate (ORR) of 20.0% [95% confidence interval (CI), 2.5–55.6; Fig. 2A]. One patient remained on study treatment for >22 months (Fig. 2B). The time to response (TTR) in the two patients was 2.1 and 6.2 months. One patient (No. 1) had 32.7% tumor shrinkage at the first imaging assessment (unconfirmed PR); however, she did not initiate the fourth cycle owing to a prolonged platelet count decrease (grade 4) and withdrew from the study (Supplementary Fig. S3). After discontinuation of the study, imaging evaluation confirmed disease progression. The overall disease control rate (DCR) was 60.0% (95% CI, 26.2–87.6). Six of the 10 patients showed the best response as stable disease (SD) ≥3 months (Table 2). The percentage change in the sum of tumor diameters from baseline over time is shown in Fig. 2A. The median progression-free survival (PFS) was 4.7 months (95% CI, 1.3–8.3; Supplementary Fig. S4A). The proportions of patients without disease progression at 6 and 12 months were 40.0% (95% CI, 12.3–67.0) and 20.0% (95% CI, 3.1–47.5), respectively. The PFS ratio was evaluable in only five of the 10 patients. In two of these five patients, the PFS ratio exceeded 1.3 (Supplementary Table S4). Median OS was 12.2 months (95% CI, 1.9–not reached; Supplementary Fig. S4B). The proportions of patients surviving at 6 and 12 months were 70.0% (95% CI, 32.9–89.2) and 58.3% (95% CI, 23.0–82.1), respectively.

Figure 2.

Antitumor activity A. Best percentage change in the sum of tumor diameter from baseline and molecular characteristics. Best response in the target lesion. Dotted lines at −30% and 20% indicate the boundaries for response and progression, respectively. In the bottom row, the predicted copy numbers (CN) and expression (exp.) of the MDM2, TP53, CDKN2A, and TWIST1 genes are presented for each patient. Patients exhibiting a 30% or more tumor shrinkage were classified as group A and the others as group B. HD, homodeletion; NE, not evaluable; PD, progressive disease; PR, partial response; SD, stable disease. B, Change in target lesions over time. Dotted lines at −30% and 20% indicate the boundaries for response and progression, respectively. Yellow lines represent patients with PD as the best response. Green lines represent patients with SD as the best response. Blue lines represent patients who showed a PR as the best response. IQR, interquartile range.

Figure 2.

Antitumor activity A. Best percentage change in the sum of tumor diameter from baseline and molecular characteristics. Best response in the target lesion. Dotted lines at −30% and 20% indicate the boundaries for response and progression, respectively. In the bottom row, the predicted copy numbers (CN) and expression (exp.) of the MDM2, TP53, CDKN2A, and TWIST1 genes are presented for each patient. Patients exhibiting a 30% or more tumor shrinkage were classified as group A and the others as group B. HD, homodeletion; NE, not evaluable; PD, progressive disease; PR, partial response; SD, stable disease. B, Change in target lesions over time. Dotted lines at −30% and 20% indicate the boundaries for response and progression, respectively. Yellow lines represent patients with PD as the best response. Green lines represent patients with SD as the best response. Blue lines represent patients who showed a PR as the best response. IQR, interquartile range.

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Very promising antitumor activity was observed in the two patients for >15 months (Fig. 3). However, one of these patients had a history of anthracycline exposure.

Figure 3.

Baseline and on-study CT images of two patients with a durable response. Blue arrows indicate the target lesions. Pt., patient.

Figure 3.

Baseline and on-study CT images of two patients with a durable response. Blue arrows indicate the target lesions. Pt., patient.

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Molecular Characteristics of Patients with Clinical Benefit

Genomic alterations were analyzed for all 10 patients, and gene expression was analyzed for nine patients (excluding No. 2) using their archived tumor tissue samples (Supplementary Table S3A). From these data, we could not find any molecular pathways clearly associated with the antitumor activity of milademetan. Focusing on eight genes (CDK4, CDKN2A, CDKN2B, EGFR, ERBB3, MDM2, PDGFRA, and TP53) that were known to be frequently affected in intimal sarcoma and 10 genes (AKT1, ATM, BBC3, CDKN1A, CDKN1C, CHEK2, MDM4, PMAIP1, PPM1D, and TWIST1) that were reportedly associated with MDM2 inhibitor responses, we found that patients with good response were associated with TWIST1 copy-number amplification (P = 0.028) and tended to be negatively associated with CDKN2A copy-number loss (P = 0.071; Fig. 2A; Supplementary Table S5A). There was a correlation between MDM2 copy number and tumor shrinkage (correlation coefficient = −0.53; Supplementary Fig. S5). Additionally, tumor tissue samples after treatment (disease progression) were analyzed in two patients (Nos. 3 and 9; Supplementary Table S5B). Although these two patients acquired additional single-nucleotide variants and copy-number alterations, we could not identify genomic alterations associated with disease progression.

Eight of the 10 patients had their cfDNA collected sequentially at baseline, on cycle 2 day 1, and during disease progression; however, one did not consent to the exploratory analysis study using cfDNA, and one had cfDNA collected at baseline but not during disease progression due to ongoing treatment. Of the eight patients, TP53 mutations in cfDNA were detected in one and five patients at baseline and disease progression, respectively (Fig. 4A; Supplementary Table S6). One patient with a TP53 mutation at baseline had early disease progression after 1.5 months of treatment. The cfDNA allele frequency of the TP53 mutations increased with disease progression (Fig. 4B).

Figure 4.

Emerging TP53 mutation in blood cfDNA during disease progression. A, White bars represent patients with undetectable TP53 in the blood cfDNA. Gray bars represent patients with detectable TP53 in the blood cfDNA. B, Chronologic TP53 mutation in blood cfDNA at baseline and on treatment. For individual patients, the best response, time to best overall response, time to first disease progression, timing of liquid biopsy, and variant allele frequency of TP53 in the blood cfDNA are presented. PD, progressive disease; Pt., patient; VAF, variant allele frequency.

Figure 4.

Emerging TP53 mutation in blood cfDNA during disease progression. A, White bars represent patients with undetectable TP53 in the blood cfDNA. Gray bars represent patients with detectable TP53 in the blood cfDNA. B, Chronologic TP53 mutation in blood cfDNA at baseline and on treatment. For individual patients, the best response, time to best overall response, time to first disease progression, timing of liquid biopsy, and variant allele frequency of TP53 in the blood cfDNA are presented. PD, progressive disease; Pt., patient; VAF, variant allele frequency.

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The findings of our study show that milademetan is clinically active, with durable responses, in patients with intimal sarcoma with MDM2 amplification. Two (20%) of the 10 patients with MDM2-amplified intimal sarcoma achieved a PR. Hence, our study met the primary endpoint for these patients. In addition to two patients with PR, one patient who discontinued the study due to a prolonged platelet count decrease also had 32.7% tumor shrinkage (unconfirmed PR) at the first imaging assessment. Two patients with PR were disease progression-free for more than 15 months.

We found an ORR and DCR of 20.0% (95% CI, 2.5–55.6) and 60.0% (95% CI, 26.2–87.8), respectively, in patients with MDM2-amplified intimal sarcoma. Although milademetan was a genomically matched treatment, its antitumor activity was not sufficient when compared with the efficacy of anthracycline-based regimens (real-world ORR, 38%; ref. 20). In addition to MDM2 amplification, further exploration of predictive biomarkers is warranted (21). Loss of P14 ARF (CDKN2A/2B loss) function may be associated with reduced sensitivity to MDM2 inhibitors in vitro (22, 23). In our study, the antitumor activity of milademetan showed a relatively negative correlation with CDKN2A loss (P = 0.071; Fig. 2A; Supplementary Table S5A). TWIST1 is a highly conserved basic helix–loop–helix transcriptional regulator. Its overexpression triggers epithelial-to-mesenchymal transition and cancer stem cell traits in various cancer cell lines (24). TWIST1 overexpression inhibits the p53 pathway involved in Myc-induced apoptosis (25). TWIST1 amplification was expected to reduce the antitumor activity of the MDM2 inhibitor (milademetan). However, in our study, TWIST1 amplification correlated with antitumor activity (P = 0.028). It is necessary to verify whether CDKN2A loss and TWIST1 amplification could be associated with the antitumor activity of MDM2 inhibitors.

The schedule and dosage of milademetan used in our study warrant reconsideration in terms of toxicity. The most common AEs were gastrointestinal- and hematology-related events. Nausea (grade ≥3) was observed in three (27.3%) patients who required additional antiemetics and dose reduction. All patients (n = 11) experienced treatment interruption, and 10 (90.9%) of the 11 experienced dose reduction due to decreased platelet count, decreased neutrophil count, anorexia, nausea, and fatigue. Of the four patients treated with milademetan for more than 6 months, three experienced two levels of dose reduction (120 mg) and one experienced one level of dose reduction (200 mg; Supplementary Fig. S3). Milademetan (120 mg) orally once daily for 3 days every 14 days twice in a 28-day cycle may be an optimal dosing regimen, which ensures maximal efficacy with minimal toxicity (26). Ten (90.9%) of the 11 patients experienced decreased platelet count (grade ≥3) in our study, whereas three (15.0%) of the 20 in the milademetan phase I study at the same dose and schedule had the same toxicity (21).

Acquired resistance remains a significant problem with MDM2 inhibitors, as even short exposure generates resistant cell populations across divergent cell lines (27–29). Adapted cells are characterized by the acquisition of loss-of-function mutations in TP53, mainly in the sequence coding the DNA-binding domain (27, 30, 31). In our study, acquired TP53 mutations were detected as loss-of-function mutations in sequential liquid biopsies (Fig. 4A; Supplementary Table S6). Interestingly, these TP53-mutant subclones increased as the disease progressed (Fig. 4B). It is not yet known whether these TP53 mutations will compromise treatment effects. Monitoring adapted cells within tumor heterogeneity is an important step in identifying acquired resistance in the context of patient treatment.

At the time of diagnosis of intimal sarcoma, it is difficult to resect completely or with adequate margins, considering that the tumor occurs in the large blood vessels and the heart. Prompt tumor shrinkage may be crucial in both localized and advanced stages because it may facilitate local treatment (surgery and/or radiotherapy), control symptoms, and improve quality of life. Nevertheless, prompt tumor shrinkage with currently available cytotoxic drugs, including anthracycline-based regimens, is hard to expect (20). Innovative new treatments are warranted both in the localized and in the metastatic stages. The extreme rarity of intimal sarcoma poses significant challenges in terms of diagnosis, understanding of disease biology, and generating clinical evidence to support new drug discovery and development. This rarity also makes it extremely difficult to conduct well-powered prospective clinical studies. Our study may be a good model for developing genomically matched treatments for extremely rare sarcomas. The approach of this study suggests that precise translational research can uncover novel biomarkers and resistance mechanisms of genomically matched treatment in extremely rare sarcomas.

Our study had some limitations. First, five of the 10 patients evaluated for antitumor activity were enrolled in our study without prior chemotherapy, because no standard chemotherapy for intimal sarcoma exists. Moreover, intimal sarcoma is extremely rare; hence, only 10 patients were evaluated in our study. These factors may have affected the evaluation of antitumor activity in our study.

In conclusion, our study shows that milademetan, an MDM2 inhibitor, is active in patients with MDM2-amplified intimal sarcoma and warrants further assessment. Strategies to optimize outcomes include the use of new predictive biomarkers such as TWIST1 amplification and CDKN2A loss to select patients who might benefit from milademetan and a combination of milademetan with other targeted treatments. We report the first findings from our study in patients with solid tumors to show that milademetan leads to a higher proportion of TP53-mutant subclones by selecting a preexisting cell subpopulation. Sequential liquid biopsy monitoring of TP53 can be used to evaluate disease status. Our study may be a good model for the design of studies aimed at developing genomically matched treatments for extremely rare sarcomas.

Study Design and Population

This was an open-label phase Ib/II study, conducted as a substudy of basket trials under a large nationwide registry for rare cancers in Japan (MASTERKEY Project; trial registration no: JMA-IIA00402). The study consisted of two cohorts, which are described in Supplementary Fig. S6. First, we evaluated the safety, tolerability, and PK of milademetan in a safety lead-in cohort (n = 3). After this safety evaluation of the first three patients, an expansion cohort was initiated. Milademetan (260 mg) was administered orally once daily for 3 days every 14 days twice in a 28-day cycle. Patients avoided food for 2 hours before and 1 hour after drug administration (21). The severity of AEs was graded using the NCI Common Terminology Criteria for Adverse Events (CTCAE) v4.0. for dose reductions and interruptions, respectively (Supplementary Table S7). Dose levels (−1) and (−2) were 200 mg and 120 mg, respectively. If a patient experienced several AEs and had conflicting dose recommendations, the recommended dose adjustment that reduced the dose to the lowest dose was used. A maximum of two milademetan dose-level reductions were allowed. The treatment was permanently discontinued if a third dose-level reduction was required.

Eligible patients had histologically confirmed intimal sarcoma (32) composed of spindle-shaped, pleomorphic, or epithelioid cells (lack of specific lineage differentiation; refs. 33, 34). General eligibility criteria included age ≥18 years; Eastern Cooperative Oncology Group performance status of 0, 1, or 2; and adequate bone marrow, organ, and cardiac function (Supplementary Table S8). Eligibility criteria included MDM2 expression as assessed by IHC or MDM2 amplification as confirmed by FISH or next-generation sequencing (copy number ≥4) in archived formalin-fixed, paraffin-embedded (FFPE) tumor tissue samples. MDM2 IHC and FISH were performed using the Invitrogen IF2 IHC antibody with EnVision detection system and the Zytolight SPEC MDM2/CEN 12 dual-color probes, respectively. When tumor TP53 status was unknown before participation in our study, tumor TP53 genotyping was performed in archived tumor tissue samples. Confirmation of wild-type TP53 was not required before milademetan dosing; however, the investigator and patient were informed about the genotyping results after they were available. If the test result showed that a patient's tumor contained a nonsynonymous mutation, insertion, or deletion in TP53 after milademetan had begun, the patient could discontinue the study unless a clinical benefit (defined as a clinical response or radiologic response) was noted. Furthermore, if the TP53 testing result was returned as indeterminate, the subject could continue the study if a clinical benefit was noted, and TP53 retesting could be considered. Stable brain metastases were permitted if they were clinically stable.

Written informed consent was obtained by the investigators from all patients before participation. The study was conducted according to the protocol and ethical principles of the Declaration of Helsinki, the International Council for Harmonisation Consolidated Guideline E6 for Good Clinical Practice, and the applicable local regulatory requirements. The study was approved by the institutional review board or ethics committee of the NCCH (Approval No. 2020-067 and No. 2014-229).

Primary and Secondary Endpoints

The primary endpoint was the number of patients with a response (CR or PR) confirmed by central diagnosis according to RECIST version 1.1 (35). Secondary endpoints included response rate confirmed by central diagnosis per RECIST version 1.1, DCR, TTR, PFS, OS, and safety assessment (the frequency of AEs and serious AEs).

PK Analysis

Blood samples for PK analysis were collected from the safety lead-in and expansion cohorts. Samples were collected for cycle 1 on day 1 at 1, 2, 3, and 6 hours after dose and on day 2 of cycle 1 before dose. Samples were collected before dose on days 15, 16, and 17 of cycle 1. In cycle 2, plasma samples for PK analysis were collected before dose on day 1 at 1 and 3 hours after dose. The PK samples were shipped to a central laboratory to be forwarded to the Q2 Solutions laboratory. The data were determined using SRM turbo ion spray LC/MS-MS in the positive ion mode. Peak areas were integrated using the SCIEX program Analyst, v. 1.6.2, using the Windows 7 platform. A weighted (1/× 2) linear regression was performed using the laboratory information management system Watson v. 7.4.2 (Thermo Fisher Scientific, Inc.). All concentration calculations were based on the peak area ratio of milademetan to its internal standard. The analyte concentrations in the quality control samples were determined by back-calculating the calibration curve. Concentration data and statistics were downloaded from Watson unless otherwise noted in the individual tables. Microsoft Excel was used to calculate the results of various experiments when Watson could not be used. The work described in this bioanalytical report was conducted per the Q2 Solutions standard operating procedures unless superseded by the bioanalysis plan and amendments. Population PK analysis was conducted using Phoenix WinNonlin (version 8.1; Certara). The analyzed parameters included the maximum observed plasma concentration (Cmax), Tmax, t1/2, and area under the plasma concentration–time curve.

Safety Assessment

TEAEs were defined as AEs that started or worsened during the treatment period (from the start date to 6 months after the end date of the study treatment). TEAEs were graded using the NCI CTCAE v4.0. Physical examinations, monitoring of vital signs, electrocardiograms, and laboratory assessments were performed throughout the study.

Predictive Biomarker Studies

Genomic DNA was prepared from FFPE tumor tissue samples using the QIAamp DNA FFPE Tissue Kit (Qiagen), and total RNA was prepared using the RNeasy FFPE Kit (Qiagen). Control genomic DNA was prepared from blood samples using the PAXgene Blood DNA Kit (Qiagen). For WES analysis, sequencing libraries were prepared from 200 to 1,600 ng of genomic DNA using the Sure­Select Human All Exon V7 SureSelect XT Reagent Kit (Agilent Technologies), and KAPA Hyper Prep Kit (KAPA Biosystems). Paired-end sequencing (2 × 75 bases) was performed on a NextSeq 500 sequencer (Illumina). The resulting sequence reads were aligned with the human reference genome (GRCh38/hg38) using the Burroughs Wheeler Aligner (BWA)–MEM algorithm. Mutations [single-nucleotide variants and short insertions and deletions (indel)] were detected using MuTect2. After exclusion of mutations in intergenic, intronic (other than splicing junctions), and untranslated regions, nonsynonymous mutations were selected. Copy-number variation was analyzed using allele-specific copy-number analysis of tumors. For RNA-seq, sequencing libraries were prepared from 200 ng of RNA using the SureSelect Human All Exon V7 and SureSelect XT HS2 RNA Reagent Kit (Agilent Technologies). Paired-end sequencing (2 × 150 bp) was performed using a NextSeq 500 sequencer. For gene expression analysis, sequencing reads were aligned to the human reference genome (GRCh38/hg38) and the transcripts per million value for each gene was calculated using STAR.

Blood samples were analyzed for cfDNA sequentially at three points (before treatment with milademetan, on cycle 2 day 1, and at the time of disease progression) as part of the exploratory analyses for resistance mechanisms. Circulating tumor DNA was analyzed using the TOP panel version 6 (36). This evaluates nucleotide variants and indels for 737 genes to calculate tumor mutation burden and infer copy-number variation. cfDNA and total genomic DNA were isolated from plasma samples and buffy coat samples using QIAamp MinElute ccfDNA Kits and the QIAamp DNA Mini Kit (Qiagen); 20 ng of cfDNA and 50 ng of gDNA samples were then used for target fragment enrichment using the Twist Library Preparation EF Kit (Twist Bioscience). A cfDNA library was constructed using the Twist UMI Adapter System. Massively parallel sequencing of isolated fragments was conducted using NovaSeq 6000 (Illumina) with a paired-end option. To obtain collapsing reads, paired-end sequencing reads with a unique molecular identifier (UMI) were processed as follows: (i) trimmed UMI reads that were masked nucleotides with a quality score less than 20 were mapped to the human reference genome (hg38) using BWA–MEM (http://bio-bwa.sourceforge.net/); (ii) selected reads were extracted by every UMI and mapped position; and (iii) collapsing reads were constructed of both strand reads, and two or more reads had more than 60% of the same bases. These reads were aligned to hg38 using BWA–MEM. Somatic mutations were called using the Genome Analysis Toolkit (https://gatk.broadinstitute.org/hc/en-us), MuTect2, VarScan2 (http://varscan.sourceforge.net), and our in-house somatic caller. Mutations were discarded if any of the following criteria were met: The read depth was <100, the variant allele frequency (VAF) in tumor samples was <0.05, the mutation occurred in only one strand of the genome, the mutation was identified in paired normal white blood cells (the mutant read number in germline control samples was >2), or the variant was present in normal human genomes in either the 1000 Genomes Project dataset (https://www.internationalgenome.org/) or our in-house database. Gene mutations were annotated using SnpEff (http://snpeff.sourceforge.net). Copy-number status was analyzed using our in-house pipeline, which determines the log R ratio (LRR) as follows: (i) we selected SNP positions in the 1000 Genomes Project database that were homozygous (VAF, ≤0.05 or ≥0.95) or heterozygous (VAF, 0.4–0.6) in the genomes of respective normal samples; (ii) we adjusted normal and tumor read depths at the selected position based on GþC percentage of a 100-bp window flanking the position; (iii) we calculated the LRR = log2 (ti/ni), where ni and ti are the normal and tumor-adjusted depths at position i; and (iv) we determined each representative LRR by the median of a moving window (1 Mb) centered at position i. The LRR values of the copy-number of both alleles, the major allele, or the minor allele were determined for every region of the genome.

Statistical Analysis

The sample size was determined based on clinical rather than statistical considerations given the rarity of amplified MDM2 intimal sarcomas. The minimum number of patients to be enrolled was five, which was considered to be enrollable over 3 years. A maximum of 10 patients were enrolled in the study. Descriptive statistics were provided for selected demographics, efficacy, safety, and PK data from the safety lead-in and expansion cohorts. Assessments of the changes from baseline to after treatment included only patients with baseline and posttreatment measurements. Safety analyses were performed based on the safety analysis set, which included all patients enrolled in the safety lead-in and expansion cohorts who received at least one dose of milademetan (n = 11).

Efficacy analyses were performed based on the efficacy analysis set, which was identical to the safety analysis set. Few therapies have been reported to reduce tumor size in intimal sarcoma, and there is no established chemotherapy as the standard of care for intimal sarcoma. Intimal sarcoma is an extremely rare cancer with a high unmet need that progresses rapidly and has a poor prognosis. If antitumor activity was seen in at least one in five patients, we considered it was reasonable to conclude that milademetan showed favorable clinical activity. If the true response rate is 15%, the probability that more than or equal to one out of five cases will respond is 55.6%. ORR and DCR and their two-sided 95% exact CI (using the Clopper–Pearson method) were provided. The distribution of time-to-event endpoints was estimated using the Kaplan–Meier method. The PFS ratio was defined as PFS2/PFS1 (PFS2: PFS with milademetan; PFS1: PFS with systemic chemotherapy administered prior to enrollment in this study). If the PFS ratio was ≥1.3, milademetan was defined as clinically beneficial for patients with MDM2-amplified intimal sarcoma as a genomically matched treatment (37, 38). PK analyses were performed based on the PK analysis set, which included all patients in the safety analysis set who had at least one PK sample with a measurable concentration of milademetan. The data cutoff dates for the safety and efficacy analyses were April 30, 2021, and May 18, 2022, respectively.

Gene copy-number and expression in patients (n = 3) who exhibited tumor shrinkage of 30% or more and in other patients (n = 7) were compared using a t test.

Ethical Approval Statement

All experimental procedures were approved by the NCCH Institutional Review Board (Approval No. 2020-067 and No. 2014-229).

Data Availability

The data generated in this study are publicly available in the NBDC Human Database at https://humandbs.biosciencedbc.jp/en/hum0409-v1 under dataset ID JGAS000619, and within the article and its supplementary data files.

T. Koyama reports grants from the Japan Agency for Medical Research and Development (AMED), Daiichi Sankyo, and the NCC during the conduct of the study, as well as grants and personal fees from Chugai, personal fees from AstraZeneca and Sysmex, and grants from PACT, Chugai, Daiichi Sankyo, Novartis, Eli Lilly, Pfizer, Janssen, Zymeworks, and Takeda outside the submitted work. T. Shimizu reports nonfinancial support and other support from Daiichi Sankyo during the conduct of the study, as well as grants from Daiichi ­Sankyo, AbbVie, Eisai, Bristol Myers Squibb, Pfizer, AstraZeneca, Takeda, Astellas, Incyte, 3D Medicine, Chordia Therapeutics, Novartis, Eli Lilly, and LOXO Oncology, and personal fees from MSD, Chugai, Taiho, AbbVie, Daiichi Sankyo, and Chordia Therapeutics outside the submitted work. K. Sudo reports grants from Daiichi Sankyo during the conduct of the study, as well as personal fees from AstraZeneca, Pfizer, Eisai, and Nihon Medi-Physics, and grants from NanoCarrier, AstraZeneca, Pfizer, Amgen, PRA Health Sciences, Takeda, and Merck outside the submitted work. H.S. Okuma reports grants from the Japan Agency for Medical Research and Development (AMED) during the conduct of the study. H. Ichikawa reports grants from Chugai, Eisai, Healios, and Ono Pharmaceutical outside the submitted work. S. Kohsaka'reports grants from Konica Minolta during the conduct of the study; grants from Boehringer Ingelheim, AstraZeneca, Chordia Therapeutics, Eisai, TransThera Sciences, and CIMIC outside the submitted work; and a patent for PH-7477-PCT-EP pending. A. Hirakawa reports personal fees from Ono Pharmaceutical, Astellas, AbbVie, Kissei Pharmaceutical, Nippon Shinyaku Co. Ltd., Novartis, Kyowa Kirin, Chugai, and Taiho outside the submitted work. A. Yoshida reports grants from Daiichi Sankyo and personal fees from Eisai outside the submitted work. T. Ueno reports grants from Konica Minolta Realm and Ambry Genetics during the conduct of the study, as well as a patent for the Junction capture method pending. N. Matsui reports grants from the Japan Agency for Medical Research and Development (AMED), Daiichi Sankyo, and the NCC (2022-A-02) during the conduct of the study. K. Nakamura reports grants from Daiichi Sankyo during the conduct of the study, as well as personal fees from Takeda, Chugai, AstraZeneca, Lilly, and Taiho outside the submitted work. N. Yamamoto reports grants from Boehringer Ingelheim during the conduct of the study, as well as personal fees from Eisai, Takeda, Boehringer Ingelheim, Cmic, Chugai, Merck, and Healios, and grants from Astellas, Chugai, Eisai, Taiho, Bristol Myers Squibb, Pfizer, Novartis, Eli Lilly, AbbVie, Daiichi Sankyo, Boehringer Ingelheim, Bayer, Kyowa Kirin, Takeda, Ono Pharmaceutical, Janssen, MSD, Merck, GSK, Sumitomo Pharma, Chiome Bioscience, Otsuka, Carna Biosciences, Genmab, Shionogi, Toray, Kaken, AstraZeneca, Cmic, InventisBio, and Rakuten Medical outside the submitted work. K. Yonemori reports other support from Daiichi Sankyo during the conduct of the study; personal fees from Pfizer, Eisai, AstraZeneca, Daiichi Sankyo, Eli Lilly, Takeda, Chugai, Fuji Film, PDR, MSD, Ono Pharmaceutical, Boehringer Ingelheim, Bayer, Bristol Myers Squibb, Janssen, and Sanofi outside the submitted work; and honoraria (as adviser) from Eisai, AstraZeneca, Sanofi, Genmab, Gilead, OncXerna, Takeda, Novartis, and MSD and research support (to institution) from MSD, Daiichi Sankyo, AstraZeneca, Taiho, Pfizer, Novartis, Takeda, Chugai, Ono, Sanofi, Seattle Genetics, Eisai, Eli Lilly, Genmab, Boehringer Ingelheim, Kyowa-Hakko Kirin, Nihon Kayaku, and Haihe. No disclosures were reported by the other authors.

T. Koyama: Conceptualization, resources, data curation, formal analysis, supervision, validation, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. T. Shimizu: Conceptualization, resources, data curation, formal analysis, supervision, validation, investigation, visualization, methodology, writing–original draft, project administration, ­writing–review and editing. Y. Kojima: Resources, data curation, writing–review and editing. K. Sudo: Resources, data curation, writing–review and editing. H.S. Okuma: Resources, data curation, writing–review and editing. T. Shimoi: Resources, data curation, writing–review and editing. H. Ichikawa: Data curation, formal analysis, writing–review and editing. S. Kohsaka: Data curation, formal analysis, writing–review and editing. R. Sadachi: Data curation, formal analysis, writing–review and editing. A. Hirakawa: Data curation, formal analysis, writing–review and editing. A. Yoshida: Data curation, writing–review and editing. R.M. Ando: Data curation, formal analysis, writing–review and editing. T. Ueno: Data curation, formal analysis, writing–review and editing. M. Yanagaki: Data curation, formal analysis, writing–review and editing. N. Matsui: Resources, data curation, writing–review and editing. K. Nakamura: Resources, data curation, writing–review and editing. N. Yamamoto: Resources, data curation, writing–review and editing. K. Yonemori: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, validation, investigation, visualization, methodology, project administration, writing–review and editing.

The authors thank the patients whose data were analyzed in this study and their families, as well as the investigators and site staff who made the research possible. The authors appreciate Emi Noguchi, Masahisa Kamikura, Sawako Tomatsuri, Natsuko Okita, Yasuhiro Fujiwara, and Hiroyuki Mano for study support. This work was supported by grants-in-aid from the Japan Agency for Medical Research and Development (AMED) under grant number JP16lk0201044, Daiichi Sankyo, and an NCC research grant (2022-A-02). Milademetan was provided by Daiichi Sankyo. Daiichi Sankyo had the opportunity to review the final manuscript but did not have the right to prevent publication. We thank Editage (www.editage.com) for English language editing.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Cancer Discovery Online (http://cancerdiscovery.aacrjournals.org/).

1.
Neuville
A
,
Collin
F
,
Bruneval
P
,
Parrens
M
,
Thivolet
F
,
Gomez-Brouchet
A
, et al
.
Intimal sarcoma is the most frequent primary cardiac sarcoma: clinicopathologic and molecular retrospective analysis of 100 primary cardiac sarcomas
.
Am J Surg Pathol
2014
;
38
:
461
9
.
2.
Stacchiotti
S
,
Frezza
AM
,
Blay
JY
,
Baldini
EH
,
Bonvalot
S
,
Bovée
J
, et al
.
Ultra-rare sarcomas: a consensus paper from the connective tissue oncology society community of experts on the incidence threshold and the list of entities
.
Cancer
2021
;
127
:
2934
42
.
3.
Van Dievel
J
,
Sciot
R
,
Delcroix
M
,
Vandeweyer
RO
,
Debiec-Rychter
M
,
Dewaele
B
, et al
.
Single-center experience with intimal sarcoma, an ultra-orphan, commonly fatal mesenchymal malignancy
.
Oncol Res Treat
2017
;
40
:
353
9
.
4.
Bode-Lesniewska
B
,
Zhao
J
,
Speel
EJ
,
Biraima
AM
,
Turina
M
,
Komminoth
P
, et al
.
Gains of 12q13-14 and overexpression of mdm2 are frequent findings in intimal sarcomas of the pulmonary artery
.
Virchows Arch
2001
;
438
:
57
65
.
5.
Shangary
S
,
Wang
S
.
Small-molecule inhibitors of the MDM2-p53 protein-protein interaction to reactivate p53 function: a novel approach for cancer therapy
.
Annu Rev Pharmacol Toxicol
2009
;
49
:
223
41
.
6.
Levine
AJ
,
Oren
M
.
The first 30 years of p53: growing ever more complex
.
Nat Rev Cancer
2009
;
9
:
749
58
.
7.
Vassilev
LT
,
Vu
BT
,
Graves
B
,
Carvajal
D
,
Podlaski
F
,
Filipovic
Z
, et al
.
In vivo activation of the p53 pathway by small-molecule antagonists of MDM2
.
Science
2004
;
303
:
844
8
.
8.
Shangary
S
,
Qin
D
,
McEachern
D
,
Liu
M
,
Miller
RS
,
Qiu
S
, et al
.
Temporal activation of p53 by a specific MDM2 inhibitor is selectively toxic to tumors and leads to complete tumor growth inhibition
.
Proc Natl Acad Sci U S A
2008
;
105
:
3933
8
.
9.
Vassilev
LT
.
MDM2 inhibitors for cancer therapy
.
Trends Mol Med
2007
;
13
:
23
31
.
10.
Arnhold
V
,
Schmelz
K
,
Proba
J
,
Winkler
A
,
Wünschel
J
,
Toedling
J
, et al
.
Reactivating TP53 signaling by the novel MDM2 inhibitor DS-3032b as a therapeutic option for high-risk neuroblastoma
.
Oncotarget
2018
;
9
:
2304
19
.
11.
Takahashi
S
,
Fujiwara
Y
,
Nakano
K
,
Shimizu
T
,
Tomomatsu
J
,
Koyama
T
, et al
.
Safety and pharmacokinetics of milademetan, a MDM2 inhibitor, in Japanese patients with solid tumors: a phase I study
.
Cancer Sci
2021
;
112
:
2361
70
.
12.
Stein
EM
,
DeAngelo
DJ
,
Chromik
J
,
Chatterjee
M
,
Bauer
S
,
Lin
CC
, et al
.
Results from a first-in-human phase I study of siremadlin (HDM201) in patients with advanced wild-type TP53 solid tumors and acute leukemia
.
Clin Cancer Res
2022
;
28
:
870
81
.
13.
Saleh
MN
,
Patel
MR
,
Bauer
TM
,
Goel
S
,
Falchook
GS
,
Shapiro
GI
, et al
.
Phase 1 trial of ALRN-6924, a dual inhibitor of MDMX and MDM2, in patients with solid tumors and lymphomas bearing wild-type TP53
.
Clin Cancer Res
2021
;
27
:
5236
47
.
14.
Italiano
A
,
Miller
WH
Jr
,
Blay
JY
,
Gietema
JA
,
Bang
YJ
,
Mileshkin
LR
, et al
.
Phase I study of daily and weekly regimens of the orally administered MDM2 antagonist idasanutlin in patients with advanced tumors
.
Invest New Drugs
2021
;
39
:
1587
97
.
15.
Gluck
WL
,
Gounder
MM
,
Frank
R
,
Eskens
F
,
Blay
JY
,
Cassier
PA
, et al
.
Phase 1 study of the MDM2 inhibitor AMG 232 in patients with advanced P53 wild-type solid tumors or multiple myeloma
.
Invest New Drugs
2020
;
38
:
831
43
.
16.
Jeay
S
,
Ferretti
S
,
Holzer
P
,
Fuchs
J
,
Chapeau
EA
,
Wartmann
M
, et al
.
Dose and schedule determine distinct molecular mechanisms underlying the efficacy of the p53-MDM2 inhibitor HDM201
.
Cancer Res
2018
;
78
:
6257
67
.
17.
Kojima
K
,
Konopleva
M
,
McQueen
T
,
O'Brien
S
,
Plunkett
W
,
Andreeff
M
.
Mdm2 inhibitor Nutlin-3a induces p53-mediated apoptosis by transcription-dependent and transcription-independent mechanisms and may overcome Atm-mediated resistance to fludarabine in chronic lymphocytic leukemia
.
Blood
2006
;
108
:
993
1000
.
18.
Ray-Coquard
I
,
Blay
JY
,
Italiano
A
,
Le Cesne
A
,
Penel
N
,
Zhi
J
, et al
.
Effect of the MDM2 antagonist RG7112 on the P53 pathway in patients with MDM2-amplified, well-differentiated or dedifferentiated liposarcoma: an exploratory proof-of-mechanism study
.
Lancet Oncol
2012
;
13
:
1133
40
.
19.
Cornillie
J
,
Wozniak
A
,
Li
H
,
Gebreyohannes
YK
,
Wellens
J
,
Hompes
D
, et al
.
Anti-tumor activity of the MDM2-TP53 inhibitor BI-907828 in dedifferentiated liposarcoma patient-derived xenograft models harboring MDM2 amplification
.
Clin Transl Oncol
2020
;
22
:
546
54
.
20.
Frezza
AM
,
Assi
T
,
Lo Vullo
S
,
Ben-Ami
E
,
Dufresne
A
,
Yonemori
K
, et al
.
Systemic treatments in MDM2 positive intimal sarcoma: a multicentre experience with anthracycline, gemcitabine, and pazopanib within the world sarcoma network
.
Cancer
2020
;
126
:
98
104
.
21.
Gounder
MM
,
Bauer
TM
,
Schwartz
GK
,
Weise
AM
,
LoRusso
P
,
Kumar
P
, et al
.
A first-in-human phase I study of milademetan, an MDM2 inhibitor, in patients with advanced liposarcoma, solid tumors, or lymphomas
.
J Clin Oncol
2023
;41:1714–24
.
22.
Van Maerken
T
,
Rihani
A
,
Dreidax
D
,
De Clercq
S
,
Yigit
N
,
Marine
JC
, et al
.
Functional analysis of the p53 pathway in neuroblastoma cells using the small-molecule MDM2 antagonist nutlin-3
.
Mol Cancer Ther
2011
;
10
:
983
93
.
23.
Gamble
LD
,
Kees
UR
,
Tweddle
DA
,
Lunec
J
.
MYCN sensitizes neuroblastoma to the MDM2-p53 antagonists Nutlin-3 and MI-63
.
Oncogene
2012
;
31
:
752
63
.
24.
Beck
B
,
Lapouge
G
,
Rorive
S
,
Drogat
B
,
Desaedelaere
K
,
Delafaille
S
, et al
.
Different levels of Twist1 regulate skin tumor initiation, stemness, and progression
.
Cell Stem Cell
2015
;
16
:
67
79
.
25.
Valsesia-Wittmann
S
,
Magdeleine
M
,
Dupasquier
S
,
Garin
E
,
Jallas
AC
,
Combaret
V
, et al
.
Oncogenic cooperation between H-Twist and N-Myc overrides failsafe programs in cancer cells
.
Cancer Cell
2004
;
6
:
625
30
.
26.
Fourie Zirkelbach
J
,
Shah
M
,
Vallejo
J
,
Cheng
J
,
Ayyoub
A
,
Liu
J
, et al
.
Improving dose-optimization processes used in oncology drug development to minimize toxicity and maximize benefit to patients
.
J Clin Oncol
2022
;
40
:
3489
500
.
27.
Aziz
MH
,
Shen
H
,
Maki
CG
.
Acquisition of p53 mutations in response to the non-genotoxic p53 activator Nutlin-3
.
Oncogene
2011
;
30
:
4678
86
.
28.
Shen
H
,
Maki
CG
.
Persistent p21 expression after Nutlin-3a removal is associated with senescence-like arrest in 4N cells
.
J Biol Chem
2010
;
285
:
23105
14
.
29.
Shen
H
,
Moran
DM
,
Maki
CG
.
Transient nutlin-3a treatment promotes endoreduplication and the generation of therapy-resistant tetraploid cells
.
Cancer Res
2008
;
68
:
8260
8
.
30.
Michaelis
M
,
Rothweiler
F
,
Barth
S
,
Cinatl
J
,
van Rikxoort
M
,
Löschmann
N
, et al
.
Adaptation of cancer cells from different entities to the MDM2 inhibitor nutlin-3 results in the emergence of p53-mutated multi-drug-resistant cancer cells
.
Cell Death Dis
2011
;
2
:
e243
.
31.
Skalniak
L
,
Kocik
J
,
Polak
J
,
Skalniak
A
,
Rak
M
,
Wolnicka-Glubisz
A
, et al
.
Prolonged idasanutlin (RG7388) treatment leads to the generation of p53-mutated cells
.
Cancers (Basel)
2018
;
10
:
396
.
32.
Travis
WD
,
Brambilla
E
,
Burke
AP
,
Marx
A
,
Nicholson
AG
, editors. Pulmonary artery intimal sarcoma. In:
WHO classification of tumours of lung, pleura, thymus and heart
. 4th ed.
Vol. 7
.
Lyon (France)
:
International Agency for Research on Cancer
;
2015
. p.
128
9
.
33.
Staats
P
,
Tavora
F
,
Burke
AP
.
Intimal sarcomas of the aorta and iliofemoral arteries: a clinicopathological study of 26 cases
.
Pathology
2014
;
46
:
596
603
.
34.
Tavora
F
,
Miettinen
M
,
Fanburg-Smith
J
,
Franks
TJ
,
Burke
A
.
Pulmonary artery sarcoma: a histologic and follow-up study with emphasis on a subset of low-grade myofibroblastic sarcomas with a good long-term follow-up
.
Am J Surg Pathol
2008
;
32
:
1751
61
.
35.
Eisenhauer
EA
,
Therasse
P
,
Bogaerts
J
,
Schwartz
LH
,
Sargent
D
,
Ford
R
, et al
.
New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)
.
Eur J Cancer
2009
;
45
:
228
47
.
36.
Kohsaka
S
,
Tatsuno
K
,
Ueno
T
,
Nagano
M
,
Shinozaki-Ushiku
A
,
Ushiku
T
, et al
.
Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens
.
Cancer Sci
2019
;
110
:
1464
79
.
37.
Von Hoff
DD
,
Stephenson
JJ
Jr
,
Rosen
P
,
Loesch
DM
,
Borad
MJ
,
Anthony
S
, et al
.
Pilot study using molecular profiling of patients’ tumors to find potential targets and select treatments for their refractory cancers
.
J Clin Oncol
2010
;
28
:
4877
83
.
38.
Massard
C
,
Michiels
S
,
Ferté
C
,
Le Deley
MC
,
Lacroix
L
,
Hollebecque
A
, et al
.
High-throughput genomics and clinical outcome in hard-to-treat advanced cancers: results of the MOSCATO 01 trial
.
Cancer Discov
2017
;
7
:
586
95
.