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857 A Clinically Practicable Approach to Predict TP53 Allelic Configurations in Myeloid Neoplasia

Program: Oral and Poster Abstracts
Type: Oral
Session: 637. Myelodysplastic Syndromes – Clinical and Epidemiological I
Hematology Disease Topics & Pathways:
Research, Acute Myeloid Malignancies, AML, Clinical Research, Diseases, Myeloid Malignancies
Monday, December 12, 2022: 3:45 PM

Waled Bahaj, MD1,2, Tariq Kewan, MD3,4*, Carmelo Gurnari, MD1,5, Arda Durmaz1*, BEN Ponvilawan, MD1*, Ishani Pandit1*, Yasuo Kubota, MD, PhD1*, Olisaemeka Ogbue6, Mai Aly, MD, BSc, MS1,7*, Yazan F. Madanat, MD8, Taha Bat, MD9, Suresh Kumar Balasubramanian, MD10, Minako Mori, MD, PhD1*, Manja Meggendorfer, PhD11, Hetty E. Carraway, MD, MBA12, Sudipto Mukherjee, MD, PhD, MPH12, Mikkael A. Sekeres, MD13, Torsten Haferlach, MD11, Valeria Visconte, PhD1 and Jaroslaw P. Maciejewski, MD, PhD, FACP1

1Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic Foundation, Cleveland, OH
2Brown Cancer Center, University of Louisville, Louisville, KY
3Smilow Cancer Center, Yale New Haven Hospital, New Haven, CT
4Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic Foundation, Cleveland Clinic, OH
5Department of Biomedicine and Prevention, Ph.D. in Immunology, Molecular Medicine and Applied Biotechnology, University of Rome Tor Vergata, Rome, Italy
6Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic Foundation, Rocky River, OH
7Assiut University, Clinical Hematology unit, Faculty of Medicine, Assiut, Egypt
8Division of Hematology/Oncology, Department of Internal Medicine, University of Texas Southwestern, Dallas, TX
9Division of Hematology and Oncology, UT Southwestern Medical Center, Dallas, TX
10Department of Oncology, Wayne State University/ Karmanos Cancer Institute, Detroit, MI
11MLL Munich Leukemia Laboratory, Munich, Germany
12Department of Hematology and Medical Oncology, Taussig Cancer institute, Leukemia Program, Cleveland Clinic, Cleveland, OH
13University of Miami, Sylvester Comprehensive Cancer Center, Miami, FL

The TP53 gene can be affected by hypomorphic/loss of function lesions occurring in diverse configurations. In addition to truncating hits, missense mutations in various hotspots may exert a dominant negative effect. Li-Fraumeni syndrome and acquired disease examples demonstrate that the presence of a wild type (WT) allele may be protective, and biallelic inactivation has the strongest leukemogenic drive. Consequently, cases with apparent biallelic TP53 lesions are associated with poor overall survival (OS) in myeloid neoplasia (MN). However, clinically applied NGS techniques currently do not always clearly identify biallelic subclones within seemingly single hit mutants, as the latter may contain subclones of various sizes. Thus, poorer than expected prognosis may be present in some cases depending on the presence and size of cryptic biallelic clones (hemizygous, homozygous, biallelic two hits) vs truly monoallelic or biclonal TP53 mosaic cases. Assessing the impact of variables surrounding TP53 mutations (TP53MT) is complex and not always feasible. Thus, the development of clinically viable algorithms may improve prognostic precision in clinical settings.

We collected clinical and molecular data from 7400 MN patients and applied a novel model to properly resolveTP53MTallelic configuration of and assess prognosis. Overall, 1285 TP53MT were found in 1010 patients. Missense mutations were the most common (74%), followed by truncating (15%), whereas 11% of the patients had concomitant missense/truncating configuration. Most missense mutations (69%) were in canonical hotspot locations. TP53MTcarriers presented with a variety of phenotypes and displayed worse OS compared to TP53WT (HR=2.7; 95%CI 2.5-3). Following the traditional criteria for estimating allelic hits1,36% of cases were classified as single hits, while 64% exhibited double hit configuration. Overall, carriers of TP53 double hits (either missense and/or truncated) had a worse OS than those with single hits TP53 (HR= 2.5; 2-3). However, a greater difference in OS between single and double TP53 hits was observed in MDS (HR= 3.1; 2.43- 4.09) compared to AML (HR= 1.5; 1.2- 2). When we compared TP53 single hits (traditional criteria) to TP53WT in both AML (HR: 1.8 [1.4-2.5]) and MDS (HR: 1.3 [1-1.7]), TP53MTcases were associated with worse OS.

To further resolve the uncertainty of TP53MT allelic status assessment, we applied ML-driven recursive partitioning on cumulative hazard objective benchmarked to external survival data. Obligatory biallelic cases were identified among patients with: i) single TP53 hit and VAF >50%, ii) double TP53 hits with a combined VAF>50%, iii) TP53MT VAF+del17p clonality >50%. Cases with VAF <50% can be differentiated into those likely with truly monoallelic TP53MTand/or likely containing subclonal cryptic biallelic TP53 hits. We then cross-validated VAF cutoff values (Fig1-A) and applied random forest regression2 with survival as a surrogate marker for TP53 allelic status. A VAF cutoff of 23% was found to be optimal in separating monoallelic and biallelic TP53MT based on the frequency of VAF splitting criteria and decrease in error. Thus, we classified TP53MT into: A) “obligatory” biallelic (OBi), B) “probable biallelic” (PBi), and C) “probable monoallelic” (PMo). Based on this approach, 579 patients (57%) had OBi, 239 (24%) had PBi, and 192 (19%) had PMoTP53MT (Fig1-B). Of note, the OS of patients with PMo TP53MT (median OS: 29 [10-77]) was similar to that of the TP53WT (median: 42 [15-103]), p=.070). However, patients with PBi TP53MT (median OS: 14 [7-37]) had worse outcomes compared to TP53WT (p<.001). Furthermore, OS was similar when we compared AML to MDS within the OBi TP53MT. These results were recapitulated in our single cell DNA sequencing studies. In 4 patients (3 likely monoallelic , 1 likely biallelic TP53MT) a combined single cell DNA and CN analysis was performed. We found that some cells contained monoallelic TP53MT while others had indeed biallelic lesions in all cases studied. Finally, our new algorithm was able to further discriminate OS differences beyond the traditionally classified single and double TP53 hit groups. Validity of our algorithm was confirmed in an external confirmatory cohort of 92 patients.

In sum, our novel approach more accurately resolves TP53 genomic configuration and uncovers genetic mosaicism to improve the prognostic evaluation.

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Disclosures: Madanat: Sierra Oncology, Stemline Therapeutics, Morphosys, Taiho, and Novartis: Membership on an entity's Board of Directors or advisory committees; BluePrint Medicines, GERON, OncLiv: Consultancy, Honoraria. Balasubramanian: Kura Oncology: Research Funding. Meggendorfer: MLL Munich Leukemia Laboratory: Current Employment. Carraway: Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Speakers Bureau; Stemline: Speakers Bureau; AbbVie: Other: DSMB; BMS: Consultancy, Honoraria, Speakers Bureau; CTI Biopharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Syndax: Other: DSMB; Takeda: Other: DSMB. Mukherjee: Jazz Pharmaceuticals: Other: Principal investigator for Investigator Initiated Trials (the Institution gets the funding), Research Funding; BioPharm: Consultancy; Celgene/Acceleron: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisor or review panel participant, Research Funding; Partnership for Health Analytic Research, LLC: Honoraria; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisor or review panel participant, Research Funding; Aplastic Anemia and MDS International Foundation: Honoraria; Eusa Pharma: Consultancy, Other: Advisor or review panel participant; Teaching and Speaking; McGraw Hill Hematology Oncology Board Review: Honoraria, Other: Advisor or review panel participant; AbbVie: Membership on an entity's Board of Directors or advisory committees, Other: Advisor or review panel participant; Genentech: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Advisor or review panel participant, Research Funding; Blueprint Medicines: Membership on an entity's Board of Directors or advisory committees, Other: Advisor or review panel participant. Sekeres: Kurome: Membership on an entity's Board of Directors or advisory committees; Bristol Myers-Squibb: Membership on an entity's Board of Directors or advisory committees; Takeda/Millenium: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Haferlach: Munich Leukemia Laboratory: Current Employment, Other: Part ownership. Maciejewski: Alexion: Consultancy; Apellis Pharmaceuticals: Consultancy.

*signifies non-member of ASH