Hung, Kevin

Abstract Background: TP53-mutated myeloid neoplasms (MNs) represent one of the most lethal subgroups of blood cancers. The World Health Organization (WHO-5) recognize TP53-mutated (TP53mut) myelodysplastic syndrome (MDS) and International Consensus Classification (ICC) recognize TP53mut MDS and acute myeloid leukaemia (AML) as distinct disease entities, acknowledging their dismal prognosis and the urgent need for novel therapeutic strategies. However, key discrepancies exist between the classifications, creating uncertainty in diagnosis, influencing therapeutic decisions, and complicating clinical trial enrolment for patients with uniformly poor survival. Importantly, neither classifications included TP53-mutated myelofibrosis (MF), other myeloproliferative neoplasms (MPN), and MDS/MPN overlap syndromes, despite growing evidence that these cases carry similar adverse outcomes. To address these critical gaps, we conducted a comprehensive analysis across the full spectrum of TP53-mutated MN. Methods: We included TP53mut cases with variant allele frequency (VAF ≥2%) of AML, MDS, MDS/MPN overlap, myelofibrosis and other MPN managed at the Mayo clinic (Rochester, USA) and Local Health Network in South Australia (Australia). Cases were classified according to the revised 4th edition WHO classification (WHO-4R). Biallelic TP53 loss was defined as: (i) ≥2 mutations with VAF ≥2%; (ii) single TP53mut with VAF ≥2% plus 17p loss on karyotype, FISH, or SNP array; or (iii) single TP53mut with VAF ≥50% with or without 17p loss. Monoallelic loss was defined as a single TP53mut with VAF <50% without 17p loss or copy neutral loss of heterozygosity. The primary endpoint was overall survival (OS) from diagnosis, censored at allogeneic transplantation. Conditional inference tree analysis was performed to define the effect of individual predictors on OS. Results: We identified 853 TP53mutMN cases including WHO-4R-defined AML (BM/PB blasts ≥20%, n=314; 36.8%), MDS with excess blasts-2 (EB-2; BM 10–19% or PB 5–19%, n=129; 15.1%), MDS-EB-1 (BM 5–9% or PB 2–4%, n=100; 11.7%), and MDS with low blasts (LB; BM <5% and PB <1%, n=228; 26.7%). MF included chronic phase (MF-CP, n=48; 5.6%), accelerated phase (MF-AP, n=7; 0.8%), and blast phase (MF-BP, n=17; 2.0%). Additional cases comprised other MPN-chronic phase (n=3, 0.4%) and MDS/MPN overlap syndromes (n=7, 0.8%). Of 848 evaluable TP53mut MN, 616 (72.6%) harbored biallelic TP53 loss and 232 (27.4%) had monoallelic loss, with 42.4% (n=98) of monoallelic cases harboring a complex karyotype (CK). Biallelic loss was highly prevalent in AML (83.1%), MDS (70.4%), and MDS/MPN overlap (71.4%), but was less frequent in cases with MPN (33.3%) and MF-chronic phase (25.0%). Across the spectrum, the frequency of biallelic loss increased stepwise with disease progression, rising from MDS-LB (62.8%) to MDS-EB1 (76.0%), MDS-EB2 (79.5%), AML (83.1%), and MF-AP/BP (79.2%) (P<0.0001). In multivariable analysis, WHO-4R category, TP53mut VAF, biallelic loss and CK were independent predictors of poor survival in TP53mut MN. Conditional inference tree analysis stratified the cohort into seven prognostic groups with distinct median OS: (1) AML, MF-BP/AP, and MDS/MPN overlap regardless of mono/biallelic and CK status (n=335, 39.7%; median OS 4.0 months); (2) MDS-EB1/EB2 with biallelic loss or monoallelic plus CK (n=212, 25.1%; 7.2 months); (3) MDS-LB, MF-CP and MPN with CK (n=156, 18.5%, OS 10.2 months); (4) biallelic MDS-LB (n=28, 3.3%; OS 15.6 months), (5) monoallelic MDS-EB1/EB2 without CK (n=20, 2.4%; OS 26.2 months), (6) monoallelic MDS-LB without CK (n=57, 6.7%; OS 33.4 months), and (7) MF-CP and other MPN without CK (n=36, 4.3%; OS 37.0 months). This analysis defines a clear stepwise risk gradient, identifying subsets with extremely poor prognosis versus a relatively indolent disease. Conclusions: This is the first study to evaluate the prognostic impact of TP53mut MN across the entire MN spectrum, providing a framework for future refinement of TP53-driven disease classification. Key findings include: (i) MF-AP/BP and MDS/MPN overlap exhibit survival outcomes as dismal as AML, irrespective of the TP53 allele status; and (ii) complex karyotype is a surrogate for “biallelic equivalent”, refining risk interpretation in monoallelic cases. Overall, our study defines seven prognostic subgroups spanning all TP53mut MN, offering a foundation for risk-adapted clinical trial design and future classification updates.

Abstract Introduction: The 5th edition of the World Health Organization (WHO-5) and the International Consensus Classification (ICC) recognize TP53-mutated myeloid neoplasms (MN) as a distinct disease category, reflecting their uniformly dismal outcomes and the urgent need for novel therapeutic strategies. However, both classifications do not include TP53-non-mutatedcases with 17p (TP53 locus) loss, despite emerging evidence that such lesions may confer biologic and clinical behaviour similar to TP53-mutated disease. Our preliminary work demonstrated that 17p loss without TP53 mutation in therapy-related MN (t-MN) is associated with poor survival, approximating that of TP53-mutated cases (Hiwase et al., Blood 2023). Yet, the true frequency and prognostic impact of 17p loss in TP53-non-mutatedMN remains largely undefined, representing a critical gap in current disease classification and risk stratification. To address this critical knowledge gap, we aim to define the frequency and prognostic impact of 17p loss across the TP53 locus in TP53-non-mutatedMN, including both myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). Finally, we compared the survival outcomes of this cohort with those of TP53-mutated MN. Method This international collaborative study was designed to evaluate the frequency and prognostic significance of 17p loss in TP53-non-mutatedMN. We included MDS and AML patients who had conventional cytogenetic analysis and did not have TP53-mutation(TP53-non-mutated)by next-generation sequencing (NGS) with sensitivity of ≥2% variant allele frequency (VAF). These cases were systematically reviewed for 17p loss using karyotype data, and where available, fluorescence in situ hybridization (FISH) and SNP array were used to confirm the 17p/TP53 locus deletion. To assess the clinical impact, we compared the overall survival (OS) of TP53-non-mutatedcases with 17p loss against a reference cohort of TP53-mutated MNs with VAF ≥2% (n=603) (South Australian Myeloid Neoplasm Registry (SA-MN) and Mayo Clinic, Rochester, USA). Results We screened 8876 cases of TP53-non-mutatedMN cases across an international cohort comprising the SA-MN (Australia; n=1046), the Düsseldorf MDS Registry (Germany; n=545), Munich Leukaemia Laboratory (Germany; n=5785), and King's College Hospital, (United Kingdom; n=1500). We identified 85 (1%) cases with 17p loss across the TP53 locus, representing the largest international cohort to define the frequency of 17p loss in TP53-non-mutatedMN. Complex karyotype was present in 40% (n=34) of cases, frequently co-occurring with del(5q) and del(7q). Clinically, most cases were MDS (n=69; 81.2%), including MDS-IB1 (n=19), MDS-IB2 (n=15), MDS-LB (n=16), t-MDS (n=8), MDS/MPN overlap (n=3), CCUS (n=1), or unspecified MDS (n=7), while AML accounted for 16 cases (18.8%). Among evaluable cases, the majority were male (78.6%) and had a median age of 66.5 years at diagnosis. The most frequent cytogenetic abnormality causing 17p loss across the TP53 locus was monosomy 17 (39%), followed by i(17q) (29%), add (17p) (14%), derivative chromosome 17 from unbalanced translocations (11%), and del(17p) (7%). The majority represented de-novo MN (60%), with t-MN in 40% of cases. Median OS of evaluable 17p loss in TP53-non-mutatedcases (n=28; 10.2 months) was poor and comparable to TP53-mutated MN (n=603, 8.7 months; P=0.42). Similarly, survival censored for a stem cell transplant was also equally poor (10.4 vs. 8.7 months; P=0.34) in both groups. Complex vs. non-complex karyotype (7.7 vs. 10.7 months; P=0.68) did not significantly influence the OS of 17p loss. Median OS of MDS cases tended to be longer compared to AML (16.7 vs. 9.1 months; P=0.11), although not statistically significant. Conclusion: In this largest international study, 1% of TP53-non-mutatedMNs harbor 17p loss across the TP53 locus, displaying poor survival equivalent to TP53-mutated disease. Exclusive reliance on NGS to identify TP53 mutations misses these high-risk structural TP53 abnormalities, which are readily detectable by conventional karyotyping. These findings provide compelling evidence to include TP53-non-mutatedcases with 17p loss in the next revision of the classifications, enabling accurate prognostication and equitable access to curative and clinical trials of novel therapies.

Abstract This retrospective analysis aimed to provide evidence-based risk stratification of TP53-mutated (TP53mut) myeloid neoplasms (MNs). Of 580 MNs harboring TP53mut with variant allele frequency (VAF) ≥2%, 219 (37.8%), 194 (33.4%), 92 (15.9%), and 75 (12.9%) were classified as acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) with low blasts (MDS-LB), MDS with excess blasts (MDS-EB)-2, and -EB1 according to the revised fourth edition of the World Health Organization (WHO) classification, respectively. Hierarchical analysis identified the following 4 risk groups with distinct survival: (1) MDS-LB, (2) MDS-EB1/EB2/AML VAF <10%, (3) MDS-EB1/EB2 VAF ≥10%, and (4) AML VAF ≥10%. We next evaluated the impact of allelic status, VAF, and complex karyotype (CK). In our cohort, the significance of biallelic status was limited to MDS with <5% blasts and not for blasts 5% to 9%, as proposed by the International Consensus Classification (ICC), or 5% to 19%, as proposed by the fifth edition of the WHO (WHO-5). MDS-EB1 and -EB2 with VAF ≥10% had comparable survival (9.6 vs 7.2 months; P = .12), regardless of allelic status. Contrary to the ICC proposal, MDS-EB1/EB2 with VAF <10% and CK had poor survival compared with those without CK, comparable to MDS-EB1/EB2 with VAF ≥10% (5.6 vs 26.2 vs 6.3 months; P = .003). Survival of TP53mut AML was poor (median 3.9 months) regardless of allelic/CK status. Thus, using ICC or WHO-5 may underestimate prognosis of MDS with blasts 5% to 19% and 5% to 9%, respectively. Collectively, the hierarchical model acknowledges poor survival of 91.9% TP53mut MDS and AML compared with 36.5% and 80.7% by WHO-5 and ICC, respectively.

Background: TP53-mutated (TP53mut) myeloid neoplasms (MN) have particularly poor survival. Discrepancies in defining TP53mut MN have impact on diagnostic work up, therapeutic decisions, and clinical trial enrolment. Methods: MN cases harboring TP53mut (variant allele frequency, VAF ≥2%) were classified based on bone marrow (BM) and peripheral blood (PB) blast % using the 4th revision of the WHO classification (WHO-4R). Biallelic loss was defined as (i) ≥2 mutations each with VAF ≥2%; (ii) single TP53mut VAF ≥2% plus 17p loss detected on karyotype, FISH, or SNP; or (iii) single TP53mut VAF ≥50%, whereas monoallelic loss was defined as single TP53mut VAF <50% without 17p loss. Primary endpoint was overall survival (OS) from diagnosis. Conditional Inference Trees (CIT) analysis was used to determine the true effect of a predictor. Results: We identified 580 cases including WHO-4R defined acute myeloid leukemia (AML, BM/PB blasts ≥20%, n=219, 37.8%), myelodysplastic syndrome (MDS) with excess blasts-2 (EB-2, BM 10-19% or PB 5%-19%, n=92, 15.9%), MDS with excess blasts-1 (EB-1, BM 5-9% or PB 2-4%, n=75, 12.9%), and the remaining were MDS with low blasts (-LB, BM <5% and PB ≤1%, n=194, 33.4%). Of the 578 cases evaluable for allelic status, 437 (75.6%) and 141 (24.4%) had biallelic and monoallelic TP53 loss, respectively. Higher frequency of biallelic loss was observed with increasing blasts. 63.2%, 73.3%, 78% and 86.3% of cases with MDS-LB, MDS-EB1, MDS-EB2, and AML had bi-allelic TP53 loss (P<0.0001). In a multivariable analysis, WHO-4R categories, VAF ≥10%, and biallelic loss were independent predictors of poor survival. CIT analysis further stratified the cohort into 4 groups with distinct survival: (1) MDS-LB (n=194, 33.4%); (2) MDS-EB1/EB2 and AML with VAF <10% (n=38, 6.6%); (3) MDS-EB1/EB2 with VAF ≥10% (n=149, 25.7%); and (4) AML with VAF ≥10% (n=199, 34.3%). MDS-LB cases could be further stratified based on allelic status and complex karyotype (CK): OS was poor for cases with biallelic TP53 loss and monoallelic TP53mut with CK compared to monoallelic TP53mut without CK, who had the most favorable survival (12.7 vs. 13 vs. 34.8 months, P<0.0001).MDS-EB1/EB2/AML with VAF<10% could also be stratified by CK: MDS-EB1/EB2/AML with VAF<10% cases without CK had the favorable survival compared to their counterparts with CK and MDS-EB1/EB2 with VAF ≥10% cases (26.2 vs. 5.6 vs. 6.3 months, P=0.003).MDS-EB1/EB2 with VAF ≥10% was a homogenous subgroup: Biological characteristics including the proportion of cases with biallelic TP53 loss, CK (P>0.9), monosomal karyotype (MK, P>0.9), del 5q (P=0.6), del 7q (P=0.4), and del 17p (P=0.2) were comparable between MDS-EB1 and -EB2 with VAF ≥10%. Importantly, median OS of MDS-EB1 and EB2 with VAF ≥10% was comparable (9.6 vs. 7.2 months, P=0.12). OS in this group was comparable regardless of the blast %, allelic status, or presence of CK.AML with VAF ≥10% had extremely poor survival: Median OS was 3.9 months. Survival of AML was equally poor irrespective of the mono- or biallelic (3.6 vs. 3.9, P=0.89) and non-CK vs. CK (1.8 vs. 3.9 months, P=0.09). Combined, our model would acknowledge poor survival of 514 (89.1%) cases. In contrast, retrospective application of the 5th edition of the WHO classification (WHO-5) and International Consensus Classification (ICC) would classify only 211 (36.4%) and 468 (80.7%) cases as biallelic/multi-hit TP53mut MN, respectively. Finally, the Harrell's c-index of the proposed model, WHO-5, and ICC was 0.66, 0.571, and 0.617, respectively. Conclusion: We provide evidence for subsequent refinements in classifying MN harboring TP53mut. Our salient findings include: (i) acknowledgement of CK as ‘biallelic equivalent’ in MDS-LB; as well as EB1/EB2/AML with VAF 2 to <10% cases; and (ii) demonstration of poor survival of MDS-EB1 and -EB2 with VAF ≥10% regardless of the allelic status. In conclusion, our proposed model acknowledged poor survival of a higher proportion of cases as TP53mut MN compared to the current models with a higher c- index.

Background: TP53 mutations (TP53mut) are highly prevalent in therapy-related myeloid neoplasms (t-MN) compared to de novo MN (35-40% vs 7-13%) and are associated with a poor outcome. Understanding the risk factors involved in the pathogenesis of TP53mut t-MN is critical to prevent its development. Methods: We characterized t-MN cases by examining primary cancer type vs autoimmune disease diagnosis vs solid organ transplantation, treatment modality, and latency (interval between primary cancer/disease and t-MN diagnosis) to identify patient and disease-related factors associated with TP53mut t-MN. Allelic loss of TP53mut MN was defined according to International Consensus Classification (ICC) criteria (Arber et al., Blood 2022). Results: Of 587 t-MN patients, 33% (n=194) had acute myeloid leukemia (t-AML) and 67% (n=393) had myelodysplastic syndrome (t-MDS, blasts<20%). Primary diagnosis comprised of 243 (41.6%) solid cancers and 300 (51.4%) hematological malignancies, while 7% (n=41) of t-MN cases had autoimmune disease or underwent solid organ transplant. Overall, 94 (16.1%) patients received prior radiotherapy (RT) alone and 75.6% (n=444) received chemotherapy (CT) with/without RT. 109 patients (18.7%) underwent autologous stem cell transplant (ASCT). The median latency from primary diagnosis to t-MN was 83.2 months (IQR 41.3, 153.2), and there was a trend towards shorter latency in t-AML compared to t-MDS (70.5 vs 85.8 months; P=0.07). Of the t-MN patients, 280 (47.7%) harbored TP53mut, which was associated with significantly poorer survival compared to wild-type (TP53wt) t-MN (9.7 vs 21.9 months; P <0.001). In contrast to TP53wt (59.0% vs 41.0%), the majority of TP53mut t-MN presented with t-MDS vs t-AML (75.7% vs 24.3%; P <0.001). According to ICC criteria, multi-hit MDS (n=131; 47.8%) was the most common entity, followed by AML (n=68; 24.8%), MDS/AML (n=34; 12.4%), and single-hit MDS (n=8, 2.9%). Poor prognostic karyotype changes e.g., del 5q, del 7q, complex karyotype and monosomal karyotype, were more prevalent in TP53mut compared to TP53wt t-MN. Co-mutations in other genes were enriched in TP53wt t-MN. As TP53mut t-MN is associated with a dismal outcome, we assessed the factors associated with its development. There were no significant differences in median age at primary cancer/disease diagnosis (59.0 vs 59.9 years; P=0.4) or gender (females 43.3% vs 39.3%; P=0.3) between TP53mut and TP53wt t-MN. However, TP53mut patients were older at t-MN diagnosis (69 vs 67.4 years; P=0.05). Correlations between gene mutations and prior malignancies revealed a significant association between TP53mut and hematological primary cancers (odds ratio [OR] 1.6; P=0.006), especially multiple myeloma (MM, OR 4.9; P<0.001) and lymphoproliferative disease (LPD, OR 2.0; P=0.013). Among solid cancers, head and neck malignancies were significantly associated with increased risk of developing TP53mut t-MN (OR 7.7; P=0.01). Compared to RT alone, ASCT (OR 2.2; P=0.004) and CT (OR 2.0; P=0.008) were associated with an increased risk of TP53mut t-MN. Recent studies indicate that CT/RT confer a selective advantage to preexisting TP53mut hematopoietic stem and progenitor cells, allowing clonal expansion/evolution and progression to t-MN. We hypothesized that TP53mut t-MN with high-risk disease features is a function of TP53mut clonal expansion/evolution rate and would predict latency between primary cancer and t-MN. Indeed, the latency between primary cancer and t-MN diagnosis was longer in TP53mut (87.8 months, IQR 45.5, 154.1) compared to TP53wt (74.7 months, IQR 37.5, 146.9 months) t-MN (P=0.05). Interestingly, 54% and 29% of TP53mut t-MN had a latency of ≥5 and ≥10 years, respectively. There were no correlations between latency and TP53 variant allele frequency (VAF) (r=0.38 and P=0.7) or between TP53mut t-MDS and t-AML (85.2 vs 109.3 months; P=0.9). Together, latency between primary cancer and t-MN was not associated with TP53mut t-MN phenotype, VAF or other poor-risk disease features. Conclusion: Hematological malignancies, especially MM and LPD treated with high-dose CT, were strongly associated with TP53mut t-MN development, highlighting the importance of careful and ongoing screening in this population. Also, the long latency of TP53mut t-MN provides an opportunity to devise effective surveillance strategies and preventative interventions long before TP53mut t-MN development.