Molecular Derivation of Extramedullary Myeloid Sarcomas Based on Machine Learning Analysis of Genomic Clusters in AML
Authors: Kewan Tariq , Gurnari Carmelo , Bahaj Waled , Pagliuca Simona , Awada Hassan , Balasubramanian Suresh Kumar , Patel Bhumika J. , Mukherjee Sudipto , Advani Anjali , Visconte Valeria , Carraway Hetty E. , Cook James R. , Rogers Heesun J. , Maciejewski Jaroslaw P. 
Published: November 2021

Abstract
Extramedullary deposits of leukemic blasts, also often called myeloid sarcoma (MS), constitute an unusual presentation of AML, which can occur in isolation (IMS, often in the de novo setting) or in the context of a fully-blown leukemic process (LMS) either at diagnosis or relapse. This peculiar variant of an acute leukemia may be due to distinct phenotypic features promoting homing of blasts to non-hematopoietic locations or/and be a result of specific molecular lesions (perhaps related to a specific genotype). So far, systematic studies of these phenomenon have been scarce with the largest cohorts reporting on 70 pts and less over the last decade.
By applying machine learning (ML) to perform latent class analysis of molecular features in AML patients (n=6,788), we have identified and validated 4 molecular clusters characterized by distinct clinical phenotypes (Awada et al Blood 2021). Genomic cluster-1 (GC-1) was characterized by predominantly normal karyotype and NPM1 MT that co-occurred with DNMT3A MT and FLT3 ITD, and IDH2 R140. In GC-2 mostly abnormal karyotype was present with CEBPA Bi, and IDH2 R172K, FLT3 ITD/TKD and lack of NPM1 MT. GC-3 had highest frequency of ASXL1 MT, BCORL1 MT, and DNMT3A MTalong with splicing factor mutations. Finally, GC-4 had the highest percentage of complex karyotype and TP53 MT. We observed a significant difference in survival [medians, months] across the molecularly-defined subgroups: GC-1 [34.1]; GC-2 [26.5]; GC-3 [15.8]; and GC-4 [9.2]. However, the genomic clustering (GCs 1-4) did not favor pAML over sAML (progressed from previous myeloid disorders).
These unbiased molecular features were then compared to those found in 91 MS pts (median age 64 years) to discern their possible origins from specific genomic AML clusters vs. an as yet described unique MS genomic signature. Among the 91 pts, 19% of them were IMS while 81% were LMS (of which 43% were de novo vs. 57% refractory/relapsed). Soft tissue (32%), skin (22%), lymph nodes (13%), and gastrointestinal tract (13%) were the most common extramedullary sites involved. An involvement of more than two sites was observed in 15 (16.5%) cases. MS-specific phenotypic features were explored based on immunohistochemical (IHC) stains and flow cytometry studies. MS neoplastic cells showed reactivity with CD43 (54% of cases), muramidase/lysozyme (53%), CD117 (39%), myeloperoxidase (35%), CD33 (32%), CD45 (30%), and CD34 (30%). Flow cytometry of the LMS cases demonstrated that 90% of patients expressed surface CD13, CD33, CD45, and HLA-DR while positivity for CD38 was present in 83% of cases, and CD117 and CD34 in 60%. By comparison to our AML cohort, MS patients had a significant higher median age at the time of diagnosis (64 vs. 62 years p=0.041) and leukocyte counts (WBC 7k vs. 4k/uL, p=0.002), higher percentage of sAML (67% vs. 40% p&lt;0.001), lower percentage of pAML (30% vs. 52% p&lt;0.001), and CBF pAML (3.3% vs. 6.4% p&lt;0.001). Complex karyotype was detected in 13% vs. 21% of the MS and AML cohorts, respectively. Notably, the median survival did not significantly differ between IMS and LMS subtypes of MS (31 vs. 15 mo, p=.157) while MS patients had poor survival when compared to regular AML, (48 vs. 10mo, p&lt;0.001). In term of molecular features, ASXL1 (25%), TET2 (19%), JAK2 (16%), NRAS (16%), DNMT3A (13%), SRSF2 (12%), and IDH1 (9%) were the most common mutations identified. Compared to the AML cohort, patients with MS were enriched for the following mutations: ASXL1 (24% vs. 11%, p&lt;0.001), JAK2 (16% vs. 3%, p&lt;0.001), and NRAS (16% vs. 6%, p=0.041). Finally, when we applied the ML-established molecular clustering of AML (as described above) to classify MS pts, MS cases grouped predominantly within GC-2 (53%) and GC-3 (32%), but paradoxically showed lower than molecularly-predicted survival. During the ASH meeting we will present a complete analysis of rare distinctive molecular lesions, which modify the survival and likely contribute to the described aberrant clinical behavior of extramedullary predilection of AML.

Disclosures
Balasubramanian: Servier Pharmaceuticals: Research Funding. Patel: Apellis: Consultancy, Other: educational talks, Speakers Bureau; Alexion: Consultancy, Other: educational talks, Speakers Bureau. Mukherjee: McGraw Hill: Honoraria, Other: Editor of Hematology Oncology Board Review (ongoing); Acceleron: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Membership on an entity's Board of Directors or advisory committees; AAMDS in Joint Partnership with Cleveland Clinic Taussig Cancer Institute: Honoraria; Genentech: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb Co.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Research/Independent Contractor, Research Funding; Eusa Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Teaching and Speaking; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Research/Independent Contractor, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees; Partnership for Health Analytic Research: Honoraria; BioPharm: Consultancy; Jazz Pharmaceuticals: Research Funding. Advani: Macrogenics: Research Funding; Glycomimetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Research Funding; Kite Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Immunogen: Research Funding; OBI: Research Funding; Abbvie: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Carraway: Celgene, a Bristol Myers Squibb company: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Other: Independent review committee; Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Stemline: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Other: Independent review committee; Astex: Other: Independent review committee; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Maciejewski: Bristol Myers Squibb/Celgene: Consultancy; Novartis: Consultancy; Regeneron: Consultancy; Alexion: Consultancy.