Purpose:

To provide insights into the diagnosis and management of therapy-related myeloid neoplasms (t-MN) following PARP inhibitors (PARPi).

Experimental Design:

In a French cancer center, we identified and described the profiles of 13 t-MN diagnosed among 37 patients with ovarian cancer referred to hematology consultation for cytopenia under PARPi. Next, we described these 13 t-MN post-PARPi among 37 t-MN post ovarian cancer according to PARPi exposure. Finally, we described 69 t-MN post-PARPi in a national cohort.

Results:

From 2016 to 2021, cumulative incidence of t-MN was 3.5% (13/373) among patients with ovarian cancer treated with PARPi. At time of hematologic consultation, patients with t-MN had a longer PARPi exposure (9 vs. 3 months, P = 0.01), lower platelet count (74 vs. 173 G/L, P = 0.0005), and more cytopenias (2 vs. 1, P = 0.0005). Compared with t-MN not exposed to PARPi, patients with t-MN-PARPi had more BRCA1/2 germline mutation (61.5% vs. 0%, P = 0.03) but similar overall survival (OS). In the national cohort, most t-MN post-PARPi had a complex karyotype (61%) associated with a high rate of TP53 mutation (71%). Median OS was 9.6 months (interquartile range, 4–14.6). In multivariate analysis, a longer time between end of PARPi and t-MN (HR, 1.046; P = 0.02), olaparib compared with other PARPi (HR, 5.82; P = 0.003) and acute myeloid leukemia (HR, 2.485; P = 0.01) were associated with shorter OS.

Conclusions:

In a large series, we described a high incidence of t-MN post-PARPi associated with unfavorable cytogenetic and molecular abnormalities leading to poor OS. Early detection is crucial, particularly in cases of delayed cytopenia.

Translational Relevance

PARP inhibitors (PARPi) have shown promising results in several cancers but may be associated with an increased risk of therapy-related myeloid neoplasms (t-MN). In a large national cohort, we showed that these t-MN have a very poor outcome, mainly due to the high rate of TP53 mutations. Early diagnosis seems to influence survival underlying the importance of identifying people at risk. On the basis of our data, close monitoring should be performed particularly in patients with inherited BRCA1/2 mutations, longer PARPi exposure, and occurrence of delayed cytopenias, especially thrombocytopenia. Whether the detection of TP53 mutated CHIP at diagnosis or its evolution under PARPi may identify those at risk should be investigated.

PARP inhibitors (PARPi) have provided a major breakthrough in the treatment of breast cancer gene (BRCA)-mutated cancers. Patients harboring BRCA1 or BRCA2 mutations have tumors that are particularly sensitive to PARPi (1). Their clinical benefit led to the approval of four drugs (olaparib, niraparib, rucaparib, and talazoparib) for various indications, including ovarian, breast, pancreatic, and prostate cancers (2–4). Initially restricted to BRCA-mutated patients, approval has also been extended to patients with ovarian cancer without BRCA mutations (5, 6). Occurrence of cytopenias such as anemia and thrombocytopenia is frequently associated with PARPi. These side effects generally occur within 3 months after treatment initiation and, in most cases, are reversible with treatment interruption (7).

Therapy-related myeloid neoplasms (t-MN) account for 10%–20% of acute myeloid leukemias (AML) and myelodysplastic syndromes (MDS; refs. 8–10) and occur in less than 3 per 1,000 person-years after an ovarian cancer and breast cancer. In t-MN occurring after a gynecologic or breast cancer, TP53 mutation is found in about one-third of patients and is usually associated with an adverse karyotype and worse outcome (11). Recently, it has been suggested that preexisting clonal hematopoiesis (CHIP) may expand under PARPi treatment, especially if associated with mutations in the DNA damage repair (DDR) pathway (12, 13). In a recent meta-analysis of 28 controlled trials, Morice and colleagues reported an increased risk of t-MN after PARPi treatment (14). Another meta-analysis suggested that this risk was limited to patients receiving PARPi in the first-line setting (15).

In this study, we aimed to provide a real-life assessment of t-MN occurring after PARPi treatment. First, we described the profiles of t-MN among patients with ovarian cancer treated with PARPi referred to a hematologic consultation for cytopenia. Second, we compared t-MN characteristics and survival according to previous exposure to PARPi in patients with ovarian cancer. Finally, we described a large national cohort of patients with t-MN with breast or ovarian cancer who were exposed to PARPi.

Study design

First, we identified 37 patients with ovarian cancer who were referred to the hematology department of Gustave Roussy Cancer Center for cytopenia during or after PARPi treatment. Cytopenia was defined as a hemoglobin level < 10 g/dL, platelet count < 100 × 109/L, or absolute neutrophil count < 1 × 109/L. All patients had a history of ovarian cancer associated with a previous treatment (radiotherapy, chemotherapy, or immunotherapy) and a PARPi exposure (olaparib, niraparib, rucaparib, or talazoparib). Patients were divided into two groups according to the presence or absence of t-MN, and data were retrospectively collected using the Gustave Roussy database.

Second, we retrospectively identified 37 patients with t-MN after ovarian cancer in the Hematology Department of Gustave Roussy including the 13 patients from the first cohort who developed t-MN. The characteristics and survival data were compared on the basis of previous exposure to PARPi.

Finally, we retrospectively identified among 29 French hospitals, 69 patients with t-MN after exposure to PARPi for a breast and/or ovarian cancer (including the 13 patients described in cohort 1 and 2). Patients with isolated cytopenia(s) or CHIP were excluded.

The flow chart describing the three cohorts can be found in Supplementary Fig. S1.

Clinical, pathologic, and cytogenetic data were collected from the patient's medical records.

Patients with t-AML (therapy-related acute myeloid leukemia) were classified into risk groups according to the ELN 2017 classification (16), patients with t-MDS (therapy-related myelodysplastic syndrome) were classified according to the International Prognostic Scoring System (IPSS) score (17), and both were classified according to the cytogenetic myelodysplasia-related changes (MRC) classification (18). Multi-hit TP53 state was defined by the presence of more than one TP53 mutation and/or TP53 variant allele frequency (VAF) > 50% and/or deletion of chromosome 17 (confirmed by conventional cytogenetics or FISH; ref. 19). Complete remission (CR) was defined according to ELN 2017 (16).

Next-generation sequencing (NGS) was performed at Gustave Roussy using the Haloplex technique (Agilent Technologies) and MiSEQ (Illumina) with an NGS panel of 77 genes. The sequencing and panel techniques differed according to centers but besides PPM1D, the recurrent genes were covered. Data collection for the control cohort was carried out in the Gustave Roussy database.

Statistical analysis

Statistical analyses were performed using SAS 9.4 (Statistical Analysis System, RRID:SCR_008567, SAS Institute Inc.) and R version 4.0.5 (R Foundation for Statistical Computing) software for analysis. We used the χ2 test to compare qualitative variables and the Wilcoxon test for quantitative variables. The Kaplan–Meier method was used to calculate median survivals. Overall survival (OS) was defined from date of diagnosis of ovarian or breast cancer or the date of diagnosis of t-MN to the date of death from any cause or censored at last follow-up. Differences in survival between two groups were evaluated using the log-rank test. Univariate and multivariate analyses of OS were performed using a Cox model. All variables associated with a P value less than 0.1 in the univariate analysis were included in the multivariate model. Differences were considered statistically significant when the P value was below to 0.05.

Ethics approval

In accordance with French regulations, ethical approval was not required, as this study was based on the patient's medical records. In accordance with the General Data Protection Regulation (GDPR) and the French law on retrospective clinical trials, the patients in our study all received an information note introducing the study, following the article 14 of the GDPR, and on personal data protection. This study was conducted using reference methodology MR-004. In addition, in a need for transparency, the research was recorded in the public directory maintained by the Health Data Hub and accessible on the website (https://www.health-data-hub.fr) catalog no. F20210210175808. The Gustave Roussy database has been declared to the CNIL (GR-2018-01).

Data availability statement

The data generated in this study are available upon reasonable request from the corresponding author.

t-MN diagnosis among patients with ovarian cancer referred for cytopenia after PARPi exposure

From 2015 to 2021, among 373 patients treated for ovarian cancer at Gustave Roussy Cancer Center with a previous exposure to PARPi, 10% (37) were referred to a hematologist for evaluation of cytopenia. Most of the patients were treated with olaparib (24/37, 64.9%) and presented with anemia (32/37, 86.5%), including 11 (34.3%) with circulating erythroblasts, isolated or associated with bicytopenia (7/37, 18.9%), or pancytopenia (3/37, 8.1%; blood smear and bone marrow aspiration of patient referred for cytopenia post-PARPi; Supplementary Fig. S2).

All patients underwent a hematologic work-up which included a bone marrow aspiration (including cytology, karyotype, and NGS) in 26 of 37 patients (70.3%) or an NGS analysis on peripheral blood for 5 of 11 other patients [31/37 (83.7%) patients performed an NGS analysis]. Among these 37 patients, t-MN diagnoses were confirmed in 13 for an overall incidence of PARPi-associated t-MN of 3.5% (13/373). t-MN included 3 t-AML (1 acute megakaryoblastic leukemia, 1 MRC AML, 1 acute monoblastic/monocytic leukemia), 9 t-MDS (4 MDS with multilineage dysplasia, 3 unclassifiable MDS, 2 MDS with excess blasts), and 1 chronic myelomonocytic leukemia.

Among the 24 of 37 patients without t-MN–related cytopenia, 14 had PARPi-related cytopenia, 2 PARPi-related erythroblastopenia, and 2 COVID-19–related cytopenia (Supplementary Fig. S3). Follow-up of patients without t-MN was 20 months (1230) at the time of analysis.

When comparing patients referred for hematologic toxicity and diagnosed with t-MN (n = 13) or not (n = 24), no differences were observed in age [65 years old (58–68) vs. 63 (56–70), P = 0.79], BRCA1/2 status [7 (53.8%) vs. 13 (54.2%), P = 0.99], treatment lines [2 (1–4) vs. 2 (1–2), P = 0.16], type of PARPi [olaparib 10 (76.9%) vs. 14 (58.3%), P = 0.99], and hemoglobin level. However, patients with t-MN were more likely to present with delayed cytopenias post-PARPi initiation [9 (11–26) vs. 4 months (2–9), P = 0.001], longer PARPi exposure [9 (8–20) vs. 3 (2–7) months, P = 0.001], lower median platelet level [74 G/L (39–90) vs. 173 G/L (119–252), P = 0.0005], and more affected cell lineages [2 (1–2) vs. 1 (0–1), P = 0.0005; Table 1].

Table 1.

Comparative analysis of patients with ovarian cancer referred for cytopenia exploration after PARPi exposure according to t-MN diagnosis.

Patients with ovarian cancer referred for cytopenia without t-MNPatients with ovarian cancer referred for cytopenia with t-MN
Characteristics(N = 24)(N = 13)P
Median age at OC/BC, years (IQR) 63 (56–70) 65 (58–68) 0.7868a 
Presence of germline BRCA mutation, N (%) 13 (54.2%) 7 (53.8%) 0.9851b 
Median treatment lines for OC/BC, N (IQR) 2 (1–22 (1–40.1585a 
Olaparib treatment, N (%) 14 (58.3%) 10 (76.9%) 0.99b 
Median time of PARPi treatment, months (IQR) 3 (2–79 (8–200.0010a 
Median cytopenia count, N (IQR) 1 (0–1) 2 (1–20.0005a 
Cytopenia(s) amount, N (IQR) 2 (1–21 (0–1) 0.0005a 
 Median WBC per mL (IQR) 4 (3–64 (3–50.9873a 
 Median ANC per mL (IQR) 2 (2–31 (1–30.1431a 
 Median hemoglobin level g/dL (IQR) 10 (9–129 (8–110.3009a 
 Median platelet count per mL (IQR) 173 (119–252) 74 (39–90) 0.0005a 
Median time to cytopenia post-PARPi initiation, months (IQR) 4 (2–99 (11–260.0014a 
Molecular biology (NGS) results 
TP53 mutation, N (%) 6/18 (33.3%) 10 (76.9%) 0.0166b 
 Median TP53 VAF, % (IQR) 2 (2–529 (9–50) 0.0028a 
PPM1D mutation, N (%) 5/18 (27.8%) 3/13 (23.1%) 1b 
Patients with ovarian cancer referred for cytopenia without t-MNPatients with ovarian cancer referred for cytopenia with t-MN
Characteristics(N = 24)(N = 13)P
Median age at OC/BC, years (IQR) 63 (56–70) 65 (58–68) 0.7868a 
Presence of germline BRCA mutation, N (%) 13 (54.2%) 7 (53.8%) 0.9851b 
Median treatment lines for OC/BC, N (IQR) 2 (1–22 (1–40.1585a 
Olaparib treatment, N (%) 14 (58.3%) 10 (76.9%) 0.99b 
Median time of PARPi treatment, months (IQR) 3 (2–79 (8–200.0010a 
Median cytopenia count, N (IQR) 1 (0–1) 2 (1–20.0005a 
Cytopenia(s) amount, N (IQR) 2 (1–21 (0–1) 0.0005a 
 Median WBC per mL (IQR) 4 (3–64 (3–50.9873a 
 Median ANC per mL (IQR) 2 (2–31 (1–30.1431a 
 Median hemoglobin level g/dL (IQR) 10 (9–129 (8–110.3009a 
 Median platelet count per mL (IQR) 173 (119–252) 74 (39–90) 0.0005a 
Median time to cytopenia post-PARPi initiation, months (IQR) 4 (2–99 (11–260.0014a 
Molecular biology (NGS) results 
TP53 mutation, N (%) 6/18 (33.3%) 10 (76.9%) 0.0166b 
 Median TP53 VAF, % (IQR) 2 (2–529 (9–50) 0.0028a 
PPM1D mutation, N (%) 5/18 (27.8%) 3/13 (23.1%) 1b 

Note: Bold indicates P < 0.05.

Abbreviations: ANC, absolute neutrophil count; BC, breast cancer; IQR, interquartile range; OC, ovarian cancer; WBC, white blood cell count.

aWilcoxon test.

bχ2 test.

After NGS evaluation of patients without t-MN, 5 patients (13.5%) were classified as CHIP, 7 (18.9%) as CCUS (clonal cytopenia of undetermined significance), and 2 (5%) as ICUS (idiopathic cytopenia of undetermined significance; Supplementary Fig. S3). A total of 77% of t-MN had a TP53 mutation, 33% of patients without t-MN had a TP53-mutated CHIP; moreover, TP53 VAF was higher in patients with t-MN [29% (9–50) vs. 2% (2–5), P = 0.028]. The incidence of PPM1D-mutated CHIP was not different [5 (27.8%) vs. 3 (23.1%)] between these two groups.

t-MN after ovarian cancer according to prior PARPi exposure (Table 2)

From 2000 to 2021, 37 patients were referred for t-MN post ovarian cancer at Gustave Roussy, with an increased incidence of 66% during the last 6 years (15 patients between 2021 and 2016 compared with 9 patients between 2015 and 2010) including the 13 (35.1%) patients exposed to PARPi described above. The other 24 patients developed t-MN after treatment for ovarian cancer but were never exposed to a PARPi. The t-MN post-PARPi patients were comparable in terms of age [53 (41–65) vs. 58 (55–63), P = 0.4], number of treatment lines for ovarian cancer [3 (2–4) vs. 2 (2–4), P = 0.7], and ovarian cancer status at t-MN diagnosis (progressive disease, 38.5% vs. 62.5%, P = 0.3). Compared with t-MN occurring in patients not exposed to PARPi, patients with t-MN-PARPi harbored more BRCA1/2 germline mutations (53.9% vs. 0% P = 0.03). Median time between primary cancer and t-MN was equivalent between the two groups [58.1 (95% confidence interval, CI: 36.3–104.5) vs. 56.8 (95% CI: 32–80.6) months, P = 0.9]. The MDS/AML ratio showed a high incidence of MDS in both groups (66.7% and 69.2%; P = 0.9). IPSS prognostic score was lower in the t-MDS PARPi group (P = 0.04) but no difference was observed in the ELN 2017 AML classification (P = 0.2). t-MN patients exposed or not to PARPi had a high percentage of adverse karyotype (84.6% vs. 69.6%, P = 0.54) and TP53 mutations (77% vs. 47%, P = 0.1) but patients with t-MN post-PARPi had more clonal abnormalities [2 (interquartile range, ICR: 1–2) vs. 1 (1–1), P = 0.004; Supplementary Fig. S4]. The clinicopathologic characteristics of the two groups are shown in Table 2.

Table 2.

Comparative analysis of t-MN among patients treated for ovarian cancer according to prior PARPi exposure.

t-MN post ovarian cancer treated without PARPit-MN post ovarian cancer treated with PARPi
Characteristics(N = 24)(N = 13)P
Median age at OC, years (IQR) 53 (41–65) 58 (55–63) 0.4357a 
Germline BRCA1/2 mutation   0.0335b 
BRCA1/2, N (%)  7/13 (53.9%)  
 Absence, N (%) 9/9 (100%) 6/13 (46.2%)  
Median treatment lines before t-MN, N (IQR) 3 (2–42 (2–40.7086a 
t-MN Type n = 24 n = 13 0.8736b 
 AML, N (%) 8 (33.3%) 4 (30.8%)  
 MDS, N (%) 16 (66.7%) 9 (69.2%)  
Median time between t-MN and OC, months (IQR) 56.8 (32.0–80.6) 58.1 (36.3–104.5) 0.8862b 
Median age at t-MN, years (IQR) 62 (54–70) 65 (58–68) 0.5777b 
OC status at t-MN n = 24 n = 13 0.2875a 
 CR, N (%) 6 (25%) 4 (30.8%)  
 SD, N (%) 3 (12.5%) 4 (30.8%)  
 PD, N (%) 15 (62.5%) 5 (38.5%)  
IPSS score n = 16 n = 8 0.0411b 
 Low + Int-1, N (%) 5 (31.3%) 6 (75%)  
 Int-2 + High, N (%) 12 (68.8%) 2 (25%)  
ELN 2017 score n = 8 n = 4 0.2231b 
 Favorable, N (%) 1 (12.5%)   
 Intermediate, N (%) 3 (37.5%)   
 Adverse, N (%) 4 (50.0%) 4 (100%)  
MRC classification n = 23 n = 13 0.5368b 
 Favorable, N (%) 1 (4.3%)   
 Intermediate, N (%) 6 (26.1%) 2 (15.4%)  
 Adverse, N (%) 16 (69.6%) 11 (84.6%)  
TP53 mutation, N (%) 7/15 (46.7%) 10/13 (76.9%) 0.1021a 
Median NGS mutations per patient, N (IQR) 1 (1–12 (1–20.0042a 
Treatment n = 24 n = 13 0.2267b 
 Intensive therapy, N (%) 7 (29.2%) 1 (7.7%)  
 Low-dose therapy, N (%) 7 (29.2%) 7 (53.8%)  
 Best supportive care, N (%) 9 (37.5%) 4 (30.8%)  
 Undetermined, N (%) 1 (4.2%) 1 (7.7%)  
t-MN Complete remission, N (%) 5/23 (21.7%) 1/13 (7.7%) 0.2774b 
HSCT, N (%) 1/24 (4.2%) 1/25 (4%) 0.6069b 
Median OS from OC diagnosis, months (IQR) 64.8 (43.8–91.5) 108.4 (39.8–139.1) 0.6987c 
Median OS from t-MN diagnosis, months (IQR) 6.1 (2.9–15.7) 8.2 (2.1–14.3) 0.7689c 
t-MN post ovarian cancer treated without PARPit-MN post ovarian cancer treated with PARPi
Characteristics(N = 24)(N = 13)P
Median age at OC, years (IQR) 53 (41–65) 58 (55–63) 0.4357a 
Germline BRCA1/2 mutation   0.0335b 
BRCA1/2, N (%)  7/13 (53.9%)  
 Absence, N (%) 9/9 (100%) 6/13 (46.2%)  
Median treatment lines before t-MN, N (IQR) 3 (2–42 (2–40.7086a 
t-MN Type n = 24 n = 13 0.8736b 
 AML, N (%) 8 (33.3%) 4 (30.8%)  
 MDS, N (%) 16 (66.7%) 9 (69.2%)  
Median time between t-MN and OC, months (IQR) 56.8 (32.0–80.6) 58.1 (36.3–104.5) 0.8862b 
Median age at t-MN, years (IQR) 62 (54–70) 65 (58–68) 0.5777b 
OC status at t-MN n = 24 n = 13 0.2875a 
 CR, N (%) 6 (25%) 4 (30.8%)  
 SD, N (%) 3 (12.5%) 4 (30.8%)  
 PD, N (%) 15 (62.5%) 5 (38.5%)  
IPSS score n = 16 n = 8 0.0411b 
 Low + Int-1, N (%) 5 (31.3%) 6 (75%)  
 Int-2 + High, N (%) 12 (68.8%) 2 (25%)  
ELN 2017 score n = 8 n = 4 0.2231b 
 Favorable, N (%) 1 (12.5%)   
 Intermediate, N (%) 3 (37.5%)   
 Adverse, N (%) 4 (50.0%) 4 (100%)  
MRC classification n = 23 n = 13 0.5368b 
 Favorable, N (%) 1 (4.3%)   
 Intermediate, N (%) 6 (26.1%) 2 (15.4%)  
 Adverse, N (%) 16 (69.6%) 11 (84.6%)  
TP53 mutation, N (%) 7/15 (46.7%) 10/13 (76.9%) 0.1021a 
Median NGS mutations per patient, N (IQR) 1 (1–12 (1–20.0042a 
Treatment n = 24 n = 13 0.2267b 
 Intensive therapy, N (%) 7 (29.2%) 1 (7.7%)  
 Low-dose therapy, N (%) 7 (29.2%) 7 (53.8%)  
 Best supportive care, N (%) 9 (37.5%) 4 (30.8%)  
 Undetermined, N (%) 1 (4.2%) 1 (7.7%)  
t-MN Complete remission, N (%) 5/23 (21.7%) 1/13 (7.7%) 0.2774b 
HSCT, N (%) 1/24 (4.2%) 1/25 (4%) 0.6069b 
Median OS from OC diagnosis, months (IQR) 64.8 (43.8–91.5) 108.4 (39.8–139.1) 0.6987c 
Median OS from t-MN diagnosis, months (IQR) 6.1 (2.9–15.7) 8.2 (2.1–14.3) 0.7689c 

Note: Bold indicates P < 0.05.

Abbreviations: HSCT, hematopoietic stem cell transplant; PD, progressive disease; SD, stable disease.

aWilcoxon test.

bχ2 test.

Only 7.7% of PARPi patients were treated intensively for their t-MN compared with 29.2% (P = 0.23) and a very low CR rate (7.7% of patients in the t-MN PARPi group vs. 21.7%, P = 0.3) was observed.

Median OS from ovarian cancer diagnosis was 108.4 (IQR: 39.8–139.1) months in the t-MN-PARPi group compared with 64.8 (IQR: 43.8–91.5) months; P = 0.69. Median OS from t-MN diagnosis was 8.2 (IQR: 2.1–14.3) months in the t-MN-PARPi group compared with 6.1 (IQR: 2.9–15.7; P = 0.8) months.

In univariate analysis, neither age (HR, 1.034; 95% CI: 0.994–1.076; P = 0.09), BRCA1/2 status, cancer status, treatment lines, PARPi treatment, type of t-MN, cytogenetic MRC classification, nor TP53 mutations influenced OS (Supplementary Table S1).

Description of the national t-MN PARPi cohort

Clinical and biological characteristics (Table 3)

Sixty-nine patients diagnosed with a t-MN post-PARPi between 2015 and 2021 were included in the French cohort (PARPTOX1) including 40.6% (28) t-AML and 59.4% (41) t-MDS. Median time between primary cancer and t-MN was 70 months (IQR, 51.2–100.3). Patients had a history of ovarian cancer (75%), breast cancer (9%), or both cancers (16%). BRCA1/2 germinal mutation was found in 48 of 67 (71.7%) patients. Overall, 34.4% (20/58) of patients were treated for their cancer with radiotherapy, 46.5% (27/58) received topoisomerase-2 inhibitors, and 98.3% (58/59) alkylating agents. Patients had received a median of two prior treatment lines (IQR, 2–4). Twelve (17%) patients developed t-MN after receiving a PARPi in first line. Only 25.4% of patients were in progression of their breast or ovarian cancer at the time of t-MN diagnosis, 34.9% had stable disease, and 39.7% were in complete response.

Table 3.

Analysis of the national t-MN post-PARPi patient's cohort.

t-MN post gynecologic cancer treated with PARPi
Characteristics(N = 69)
Type of cancer n = 69 
 Breast, N (%) 6 (8.7%) 
 Ovarian, N (%) 52 (75.4%) 
 Breast and ovarian, N (%) 11 (15.9%) 
Germline BRCA1/2 mutation, N (%) 48/67 (71.7%) 
Median treatment lines before t-MN, N (IQR) 2 (2–4
Type of PARPi n = 69 
 Olaparib, N (%) 50 (73.9%) 
 Niraparib, N (%) 12 (18.8%) 
 Rucaparib, N (%) 3 (7.1%) 
 Talazoparib, N (%) 2 (2.9%) 
Median duration of PARPi treatment, months (IQR) 14.2 (8.0–29.1) 
Cytopenia(s) occurring during PARPi, N (%) 33 (50.8%) 
t-MN type n = 69 
 AML, N (%) 28 (40.6%) 
 MDS, N (%) 41 (59.4%) 
Cancer status at t-MN n = 63 
 CR, N (%) 25 (39.7%) 
 SD, N (%) 22 (34.9%) 
 PD, N (%) 16 (25.4%) 
Median time between t-MN and initiation of PARPi, months (IQR) 19.0 (10.0–33.9) 
Median time between t-MN and discontinuation of PARPi, months (IQR) 1.3 (0.2–4.1) 
Median time between OC/BC and t-MN, months (IQR) 70.0 (51.2–100.3) 
Median age at t-MN, years (IQR) 66 (57–71) 
TP53 mutation 
 Presence of TP53, N (%) 32/45 (71.1%) 
 Multi-Hit TP53 aberration, N (%) 24/32 (75%) 
MRC classification 
 Favorable, N (%) 4/54 (6.3%) 
 Intermediate, N (%) 11/54 (17.2%) 
 Adverse, N (%) 49/54 (76.6%) 
IPSS classification n = 34 
 Low + Int-1, N (%) 17 (50%) 
 Int-2 + High, N (%) 17 (50%) 
ELN 2017 classification n = 28 
 Favorable, N (%) 2 (7.1%) 
 Intermediate, N (%) 5 (17.9%) 
 Adverse, N (%) 21 (75%) 
Treatment n = 68 
 Intensive therapy, N (%) 13 (19.1%) 
 Low-dose therapy, N (%) 32 (47.1%) 
 Best supportive care, N (%) 16 (23.5%) 
 Undetermined, N (%) 7 (10.3%) 
t-MN Complete remission, N (%) 12/64 (18.8%) 
HSCT, N (%) 5/68 (7.4%) 
Median OS from cancer diagnosis, months (IQR) 102.2 (69–171.4) 
Median OS from t-MN diagnosis, months (IQR) 9.6 (4–14.6) 
t-MN post gynecologic cancer treated with PARPi
Characteristics(N = 69)
Type of cancer n = 69 
 Breast, N (%) 6 (8.7%) 
 Ovarian, N (%) 52 (75.4%) 
 Breast and ovarian, N (%) 11 (15.9%) 
Germline BRCA1/2 mutation, N (%) 48/67 (71.7%) 
Median treatment lines before t-MN, N (IQR) 2 (2–4
Type of PARPi n = 69 
 Olaparib, N (%) 50 (73.9%) 
 Niraparib, N (%) 12 (18.8%) 
 Rucaparib, N (%) 3 (7.1%) 
 Talazoparib, N (%) 2 (2.9%) 
Median duration of PARPi treatment, months (IQR) 14.2 (8.0–29.1) 
Cytopenia(s) occurring during PARPi, N (%) 33 (50.8%) 
t-MN type n = 69 
 AML, N (%) 28 (40.6%) 
 MDS, N (%) 41 (59.4%) 
Cancer status at t-MN n = 63 
 CR, N (%) 25 (39.7%) 
 SD, N (%) 22 (34.9%) 
 PD, N (%) 16 (25.4%) 
Median time between t-MN and initiation of PARPi, months (IQR) 19.0 (10.0–33.9) 
Median time between t-MN and discontinuation of PARPi, months (IQR) 1.3 (0.2–4.1) 
Median time between OC/BC and t-MN, months (IQR) 70.0 (51.2–100.3) 
Median age at t-MN, years (IQR) 66 (57–71) 
TP53 mutation 
 Presence of TP53, N (%) 32/45 (71.1%) 
 Multi-Hit TP53 aberration, N (%) 24/32 (75%) 
MRC classification 
 Favorable, N (%) 4/54 (6.3%) 
 Intermediate, N (%) 11/54 (17.2%) 
 Adverse, N (%) 49/54 (76.6%) 
IPSS classification n = 34 
 Low + Int-1, N (%) 17 (50%) 
 Int-2 + High, N (%) 17 (50%) 
ELN 2017 classification n = 28 
 Favorable, N (%) 2 (7.1%) 
 Intermediate, N (%) 5 (17.9%) 
 Adverse, N (%) 21 (75%) 
Treatment n = 68 
 Intensive therapy, N (%) 13 (19.1%) 
 Low-dose therapy, N (%) 32 (47.1%) 
 Best supportive care, N (%) 16 (23.5%) 
 Undetermined, N (%) 7 (10.3%) 
t-MN Complete remission, N (%) 12/64 (18.8%) 
HSCT, N (%) 5/68 (7.4%) 
Median OS from cancer diagnosis, months (IQR) 102.2 (69–171.4) 
Median OS from t-MN diagnosis, months (IQR) 9.6 (4–14.6) 

The most common PARPi used was olaparib (n = 50, 73.9%); 12 patients (18.8%) received niraparib, 3 (7.1%) rucaparib, 2 (2.9%) talazoparib, and 2 received two different PARPi (rucaparib and olaparib or niraparib). The median time between cancer diagnosis and initiation of PARPi was 44.1 months (IQR, 32.9–72.4). The median duration of PARPi treatment was 14.2 months (IQR, 8.0–29.1). History of PARPi-related hematologic toxicity was reported in 50.8% of patients including anemia in 56.5%, isolated or associated with bicytopenia (30.4%), or pancytopenia (17.4%). t-MN were diagnosed 1.3 months (range, 0–50) after PARPi discontinuation (including 14 patients diagnosed after 6 months).

The median age at t-MN diagnosis was 66 years (IQR, 57–71). Only 9.4% (6) of patients had a normal karyotype; 76.6% (49) harbored adverse genetic abnormalities including 60.9% of complex karyotype. Two patients had favorable AML [core-binding factor (CBFB)-AML], and 1 had KMT2A-AML.

Molecular landscape of t-MN post-PARPi

NGS data were available for 45 patients (65.2%). Patients had a median of 1 mutation (IQR, 1–2). The most frequently mutated gene at t-MN diagnosis was TP53 (n = 32, 71.1%) with a median VAF of 41% (IQR, 17–67). A total of 75% (n = 24) were multi-hit mutations (Supplementary Table S2). As described, most TP53 mutations were localized within the DNA-binding domain (Fig. 1A), hotspot mutations at amino acid positions R248 and R273 were the most recurrent TP53 gene mutations. PPM1D was mutated in 7/33 patients (21.2%), with concurrent TP53 mutation in five cases with low VAF (1%, 3%, 4%, 6%, and 8%), without concurrent TP53 mutation in two cases with higher VAF (37% and 41%). Other genes mutated with a prevalence > 5% were DNMT3A (n = 15, 19%), PTPN11 (n = 3, 6.7%), RUNX1 (n = 3, 6.7%), and TET2 (n = 3, 6.7%). No gene mutation was identified in 5 (11%) patients. The association between different mutations is shown in Fig. 1B. IPSS score was “Low and Intermediate-1″ and “Intermediate-2 and High” MDS groups for 50% of patients, respectively. AMLs were mainly considered as adverse (75%) according to the ELN 2017 classification.

Figure 1.

NGS mutations in the national t-MN post-PARPi cohort. A, Mutation Lolliplot displaying the distribution of TP53 mutations observed in 32 patients. B, Commutation plot visualizing the mutated genes in PARPi-associated t-MN. Mutations are depicted by colored bars, and each column represents 1 of the 45 sequenced subjects.

Figure 1.

NGS mutations in the national t-MN post-PARPi cohort. A, Mutation Lolliplot displaying the distribution of TP53 mutations observed in 32 patients. B, Commutation plot visualizing the mutated genes in PARPi-associated t-MN. Mutations are depicted by colored bars, and each column represents 1 of the 45 sequenced subjects.

Close modal

Treatment and OS

Low-dose therapy (azacitidine monotherapy or in combination) was the most commonly used treatment (47.1%), 19.1% received intensive treatment, 32.3% had best supportive care, and CR was achieved in only 18.8% of the cases. Hematopoietic stem cell transplantation (HSCT) was performed in 5 patients (7.4%). Median OS from ovarian cancer and/or breast cancer and t-MN diagnosis were, respectively, 102.2 (IQR, 69–171.4) months and 9.6 (IQR, 4–14.6) months. In univariate analysis, a longer delay between discontinuation of PARPi treatment and t-MN diagnosis (HR, 1.039; 95% CI: 1.002–1.077; P = 0.0361), as well olaparib treatment compared with other PARPi (HR, 5.791; 95% CI: 1.773–18.912; P = 0.0036) and AML diagnosis (HR, 2.293; 95% CI: 1.192–4.411; P = 0.0129) were associated with shorter OS (Supplementary Table S3).

Indeed, median OS of t-MN patients diagnosed > 6 months after PARPi discontinuation was only 3.9 (IQR: 2–6.9) months compared with 10.2 months (IQR: 5.3–14.6, P = 0.035). Patients with t-AML had a shorter OS compared with t-MDS 6.1 (IQR: 2.1–11.8) versus 10.7 (IQR: 6.2–18.7, P = 0.014) months, as well as patients treated with olaparib for ovarian cancer and/or breast cancer compared with other PARPi [6.7 (IQR: 3.5–13.9) vs. 24 months (IQR: 10.2–24), P = 0.0007; Fig. 2].

Figure 2.

OS of the national t-MN post-PARPi cohort: A, OS of t-MN after PARPi treatment from the national cohort. B, OS of t-MN after PARPi treatment from the national cohort according to t-MN type: AML versus MDS. C, OS of t-MN after PARPi treatment from the national cohort according to the time between PARPi discontinuation and t-MN diagnosis (<6 vs. ≥6 months). D, OS of t-MN after PARPi treatment from the national cohort according to PARPi treatment received [olaparib vs. other PARPi treatments (rucaparib, niraparib, talazoparib)].

Figure 2.

OS of the national t-MN post-PARPi cohort: A, OS of t-MN after PARPi treatment from the national cohort. B, OS of t-MN after PARPi treatment from the national cohort according to t-MN type: AML versus MDS. C, OS of t-MN after PARPi treatment from the national cohort according to the time between PARPi discontinuation and t-MN diagnosis (<6 vs. ≥6 months). D, OS of t-MN after PARPi treatment from the national cohort according to PARPi treatment received [olaparib vs. other PARPi treatments (rucaparib, niraparib, talazoparib)].

Close modal

In the multivariate analysis, a longer delay between the end of PARPi treatment and t-MN diagnosis (HR, 1.047; 95% CI: 1.008–1.087; P = 0.0179), olaparib treatment compared with other PARPi (HR, 6.249; 95% CI: 1.901–20.543; P = 0.0025) and AML diagnosis (HR 2.374; 95% CI: 1.228–4.590; P = 0.0102) were associated with shorter OS independently of the BRCA1/2 status (Table 4).

Table 4.

Univariate and multivariate analysis for OS from t-MN diagnosis of the national t-MN post-PARPi patient's cohort.

Univariate analysisMultivariate analysis
CharacteristicsCrude HR (95%CI)PAdjusted HR (95% CI)P
Presence of BRCA1/2 mutation (ref: absence) 2.018 (0.908–4.488) 0.0850 1.393 (0.601–3.231) 0.4399 
PARPi type: Olaparib 5.791 (1.773–18.912) 0.0036 6.249 (1.901–20.543) 0.0025 
Time between t-MN and PARPi discontinuation, months 1.039 (1.002–1.077) 0.0361 1.047 (1.008–1.087) 0.0179 
Type of t-MN: AML 2.293 (1.192–4.411) 0.0129 2.374 (1.228–4.590) 0.0102 
Univariate analysisMultivariate analysis
CharacteristicsCrude HR (95%CI)PAdjusted HR (95% CI)P
Presence of BRCA1/2 mutation (ref: absence) 2.018 (0.908–4.488) 0.0850 1.393 (0.601–3.231) 0.4399 
PARPi type: Olaparib 5.791 (1.773–18.912) 0.0036 6.249 (1.901–20.543) 0.0025 
Time between t-MN and PARPi discontinuation, months 1.039 (1.002–1.077) 0.0361 1.047 (1.008–1.087) 0.0179 
Type of t-MN: AML 2.293 (1.192–4.411) 0.0129 2.374 (1.228–4.590) 0.0102 

Note: Cox proportional hazards model. Bold indicates P < 0.05.

The benefit of PARPis has been widely demonstrated in numerous clinical trials, first in patients with relapsed ovarian cancer in response to a platinum rechallenge, and now as maintenance after first-line chemotherapy for advanced ovarian cancer, regardless of BRCA1/2 mutational status. Since the approval of olaparib in 2014, PARPi have become a treatment of choice in ovarian cancer but also a therapeutic option in subgroups of breast, pancreatic, and prostate cancers (2, 5, 20). Initial data suggesting a higher risk of developing t-MN after PARPi treatment (21) has already been confirmed in a large meta-analysis of randomized clinical trials (14). Moreover, numerous case series have recently been published, suggesting a higher incidence than expected (13, 22–27). In this study, we performed a comprehensive overview of PARPi t-MN in a real-life setting, providing insight into the identification of patients at risk, t-MN post-PARPi characteristics, and prognostic factors.

Our study corroborates the hypothesis of an increased risk of t-MN among patients with ovarian cancer treated with PARPi with an increase in t-MN diagnoses in the last 6 years of 66% and a cumulative incidence of 3.5% among 373 patients with ovarian cancer treated with PARPi in a single cancer center.

As cytopenias are a frequent side effect of PARPi treatment, it may be difficult for the physician to identify which patients require further work-up to rule out a t-MN. Our data suggest that delayed cytopenia (i.e., after the first 3 months of PARPi initiation), especially in case of thrombocytopenia, bicytopenia, or pancytopenia, should raise a suspicion for t-MN. At this point, a complete hematologic evaluation including conventional cytogenetics should be recommended, as some of the t-MN do not meet morphologic dysplasia criteria (1/3 in our cohort; Supplementary Fig. S2), and NGS results alone may not distinguish CHIP from t-MN.

Although t-MN is recognized as a distinct entity in the World Health Organization 2016 classification of hematologic malignancies (28), it remains a heterogeneous disease. Genomic alterations may be driven by the type of chemotherapy received for cancer treatment given the known association between alkylating agents and TP53 mutations (29). Despite the fact that post-PARPi t-MN patients tended to have less active cancer, fewer treatment lines for cancer, and were diagnosed more quickly, OS is not better compared to non-PARPi t-MN likely due to the high proportion of complex karyotype and TP53 mutations. Almost all patients who developed post-PARPi t-MN had a germline BRCA1/2 mutation, a feature that was not described in non-PARPi t-MN; this could be explained by the fact that PARPi's initial indications were restricted to BRCA-mutated patients. Although patients with BRCA2-mutated breast cancer treated with chemotherapy tend to have a higher risk of developing AML (30), this has not been yet confirmed in other studies (31). BRCA1/2 mutations result in DNA repair deficiency, which could increase genetic instability in healthy hematopoietic cells in response to PARPi, and therefore be responsible for the emergence of malignant clones. This hypothesis is in accordance with the higher number of clonal abnormalities observed in t-MN post-PARPi compared with t-MN without PARPi. A recent study suggested that the development of CHIP in germline BRCA1/2-mutated patients was linked to the use of platinum-based agents more than the BRCA1/2 mutation itself (32). Therefore, the question remains whether PARPi could act as a trigger for the expansion of CHIP in this background. Since then, indications for PARPi have been extended to nonmutated BRCA patients; subsequent studies will determine whether BRCA1/2 status influences the risk of t-MN post-PARPi.

Although prevalence of PARPi-associated t-MN remains low and the underlying mechanism unclear, we were able to identify and study 69 cases from various French centers. To our knowledge, this is the largest retrospective cohort assessing the characteristics of t-MN after PARPi treatment among patients with breast and/or ovarian cancer. In addition to harboring TP53 mutations in over two thirds of cases, PARPi-associated t-MN were usually multi-hit TP53, which is known to be associated with poor outcome in MDS (19). Interestingly, our data suggest the importance of early diagnosis as increased time between PARPi discontinuation and t-MN diagnosis had a negative impact on survival. Another poor prognostic factor was an AML diagnosis usually presenting with dysplastic features suggestive of a preexisting phase of undiagnosed MDS. These two observations underscore the importance of a close follow-up for patients at risk.

Intriguingly, olaparib, compared with other PARPi, negatively influenced OS, independently of BRCA1/2 status or duration of PARPi treatment. One hypothesis is that olaparib may be more toxic to hematopoietic cells as supported by the high rate of complex karyotypes in patients treated with olaparib compared with others (Supplementary Table S4). It will be interesting to evaluate whether all PARPi treatments have the same effect on hematopoietic cells and can induce resistance to standard AML/MDS treatments, regardless of BRCA status.

One of the potential approaches to detect patients at risk of t-MN is CHIP detection, especially DDR-mutated CHIP, which could represent a preleukemic state (33). Indeed, it has been suggested that PARPi treatment may drive the emergence or expansion of preexisting clones, especially DDR-mutated clones (12, 13). Whether the detection of TP53-mutated CHIP in patients treated with PARPi may identify those at higher risk of developing t-MN should be further investigated.

This study has several limitations. As PARPi treatments were initially indicated in ovarian cancers only (34), the majority of the national cohort was composed of patients with PARPi-treated ovarian cancer (75,4%). It will be crucial to determine the risk of t-MN in other cancers becoming eligible for PARPi, especially those not treated with alkylating agents, such as prostate cancer. Indeed, more than PARP inhibition alone, the association of PARPi with chemotherapy could be responsible for a higher incidence of t-MN. Moreover, as PARPi improve ovarian cancer survival, patients may have more time to develop t-MN causally related to PARPi or not (35). Another limit comes from the type of PARPi used. Indeed, olaparib, which is the most represented treatment in the cohort (73,9%), was the first drug to be authorized. These results are in line with the other studies cited above; however, further studies are needed to assess the t-MN characteristics of other PARPi drugs.

The clinical benefits of PARPi are no longer debatable. However, the early therapeutic trials that led to the approval of these drugs, especially those with a short follow-up, did not register any warning signals. A small number of MDS and AML cases have been reported after a longer follow-up. Given their low prevalence, it is essential to encourage centralized data collection regarding all t-MN diagnosed during or after PARPi. Special vigilance is required for patients in first-line treatment where the risk is usually low.

Conclusion

We describe a large cohort of PARPi-related t-MN. OS is poor, likely attributable to unfavorable cytogenetic and molecular abnormalities. Time between PARPi interruption/discontinuation seems to influence OS, underscoring the importance of early diagnosis. Particular consideration should be done on BRCA1/2 patients, and in case of thrombocytopenia or more than one cytopenia and relatively long PARPi exposure. Further studies should be performed to evaluate this risk when PARPi are administered in front-line therapy.

S. Bertoli reports personal fees from AbbVie, Astellas, Jazz Pharmaceuticals, Pfizer, and BMS-Celgene outside the submitted work. L. Gastaud reports personal fees from AbbVie, Pfizer, BMS, GSK, and Immunocore outside the submitted work. C. Simand reports personal fees from AbbVie, Jazz Pharmaceuticals, Astellas, and Amgen outside the submitted work. A. Genthon reports personal fees from AbbVie outside the submitted work. P.-Y. Dumas reports personal fees from Daichii, Janssen, BMS, AbbVie, and Jazz, as well as grants and personal fees from Astellas outside the submitted work. P. Pautier reports other support from AstraZeneca, GSK, and Onxeo, as well as personal fees from PharmaMar outside the submitted work. S. Thepot reports other support from BMS and Astellas outside the submitted work. L. Adés reports personal fees from BMS, Novartis, Takeda, AbbVie, and Jazz Pharma outside the submitted work. C. Récher reports grants, personal fees, and non-financial support from AbbVie, Astellas, and BMS; personal fees from Amgen, Novartis, and Takeda; grants and personal fees from Jazz Pharma; grants from Iqvia and Maat Pharma; and personal fees and non-financial support from Servier outside the submitted work. H. Dombret reports personal fees from Incyte, Daiichi Sankyo, and Pfizer; grants and personal fees from Jazz Pharma; grants from Servier, BMS-Celgene, and Astellas; grants, personal fees, and non-financial support from Amgen; non-financial support from Novartis and Sandoz; and grants and non-financial support from AbbVie outside the submitted work. C. Marzac reports personal fees from Astellas, Celgene, and BMS outside the submitted work. A. Leary reports grants, non-financial support, and other support from AstraZeneca, MSD, Clovis, and GSK; other support from Genmab, Apmonia, and Ability Pharma; and personal fees from Blueprint and Zentalis during the conduct of the study. J.-B. Micol reports personal fees from AbbVie and Astellas, as well as grants and personal fees from Jazz Pharmaceuticals outside the submitted work. No disclosures were reported by the other authors.

V. Marmouset: Conceptualization, data curation, writing–original draft, writing–review and editing. J. Decroocq: Resources. S. Garciaz: Resources. G. Etienne: Resources. A. Belhabri: Resources. S. Bertoli: Resources. L. Gastaud: Resources. C. Simand: Resources. S. Chantepie: Resources. M. Uzunov: Resources. A. Genthon: Resources. C. Berthon: Resources. E. Chiche: Resources. P.-Y. Dumas: Resources. J. Vargaftig: Resources. G. Salmeron: Resources. E. Lemasle: Resources. E. Tavernier: Resources. J. Delage: Resources. M. Loirat: Resources. N. Morineau: Resources. F. Blanc-Durand: Resources. P. Pautier: Resources. V. Vergé: Visualization. N. Auger: Data curation. M. Thomas: Resources. L. Stefani: Resources. M. Lepelley: Resources. T. Boyer: Resources. S. Thepot: Resources. M.-P. Gourin: Resources. P. Bourquard: Resources. M. Duchmann: Writing-review and editing. P.-M. Morice: Resources. M. Michallet: Resources. L. Adés: Resources. P. Fenaux: Resources. C. Récher: Resources. H. Dombret: Resources. A. Pagés: Formal analysis. C. Marzac: Resources. A. Leary: Resources. J.-B. Micol: Conceptualization, supervision, writing–original draft, writing–review and editing.

The authors thank the collaborators from UNIHEM, French Network of Pharmacovigilance Centers, ALFA, FILO, and GFM groups.

J.-B. Micol received support from INCA PLBIO21-080.

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 Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

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