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852 Machine Learning Identifies Gene Mutations and Variant Allele Fractions That Refine the 2022 European Leukemianet Risk Stratification for Acute Myeloid Leukemia

Program: Oral and Poster Abstracts
Type: Oral
Session: 618. Acute Myeloid Leukemias: Biomarkers and Molecular Marker in Diagnosis and Prognosis: Refining Diagnostic Risk Assessment
Hematology Disease Topics & Pathways:
Research, Acute Myeloid Malignancies, AML, Adult, Translational Research, Genomics, Diseases, Myeloid Malignancies, Biological Processes, Technology and Procedures, Study Population, Human
Monday, December 9, 2024: 4:00 PM

Nikhil Patkar, MD1*, Aarti Ramesh Achrekar, MSc2*, Priyanka Rajesh Ugale, MSc2*, Gojiri Mawalankar, MD2*, Saurabh Kusurkar, MD2*, Shadma Shahin, MD2*, Swapnali Joshi, MSc2*, Seema Biswas, MD2*, Karishma Anam2*, Arpit Mathur2*, Vishram Terse, PhD, MSc2*, Dhanlaxmi Lalit Shetty, PhD, MSc3,4*, Nishant Jindal, MD, MBBS5*, Prashant Tembhare, MD6*, Sumeet Mirgh, MD, DM7*, Alok Shetty, MD, DM8*, Anant Gokarn, MD, DM7*, Sachin Punatar, MD, DM7*, Lingaraj Nayak, MBBS, MD, DM9*, Hasmukh Jain, MD, DM10*, Manju Sengar, MD, DM10, Navin Khattry, MD, DM7*, Bhausaheb Bagal, MD, DM7*, Sweta Rajpal, MD, DM2,11*, Gaurav Chatterjee, MD, MSc2*, Papagudi Ganesan Subramanian, MD12* and Sumeet Gujral, MD13*

1Department of Hematopathology, Tata Memorial Centre, Mumbai, India
2Department of Hematopathology, ACTREC, Tata Memorial Centre, Navi Mumbai, India
3Tata Memorial Hospital, Mumbai, India
4Cancer Cytogenetics, ACTREC, Tata Memorial Centre, Navi Mumbai, India
5Department of Medical Oncology, ACTREC, Tata Memorial Centre, Navi Mumbai, India
6Department of Hemato Pathology, Tata Memorial Centre, Mumbai, India
7Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai, India
8Department of Medical Oncology, Tata Memorial Centre, Mumbai, India
9Department of Medical Oncology, Tata Memorial Centre, MUMBAI, India
10Department of Medical Oncology, Tata Memorial Hospital, Mumbai, India
11Department of Hematopathology, Tata Memorial Centre, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai, India
12Department of Hematopathology, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai, India
13Department of Pathology, Tata Memorial Centre, Mumbai, India

Introduction: Incorporation of cytogenetic and molecular alterations helps risk-stratify patients of acute myeloid leukemia (AML) patients. The 2022 European LeukemiaNet (ELN) recommendations incorporate cytogenetics and next-generation sequencing (NGS) derived molecular data for risk stratification. Using a machine-learning (ML) approach, we identified heterogeneous outcomes in the favorable and intermediate ELN22 groups by incorporating gene mutations and variant allele fractions (VAF).

Methods: A total of 508 patients of adult AML (>18 years) were accrued over 10 years (2012 – 2023). Patients were uniformly treated with "3 + 7" induction and 3 doses of HiDAC. Diagnostic samples were sequenced using a 50-gene myeloid panel (till 2020) based on single molecule molecular inversion probes and subsequently using a 135-gene hybrid capture-based panel. Based on cytogenetics and genomic information, cases were risk-stratified per ELN22 recommendations. In each ELN category, we incorporated commonly occurring (>2%) mutations and their variant allele fractions (VAF) as features. Features in each ELN risk were selected using recursive feature elimination. Multicollinearity was assessed using variance inflation factor. A logistic regression-based model with k-fold cross-validation was developed for each ELN category to predict overall survival (OS). Top features in each ELN category were used to derive a cumulative score based on which subcategories were created. Results of the subcategories were analyzed for their impact on OS and RFS using log rank test.

Results: Median age of the cohort was 35.0 years (M:F, 1.6:1) with median follow-up of 29.5 months. The median OS was 80 months (95% CI 34.8-87.3) and median RFS was 52.3 months (95% CI 35.2–87.9) months. Based on ELN22 recommendations, patients were classified as favorable (n=275), intermediate (n=157), or adverse risk (n=75). Patients classified as ELN22-adverse had inferior OS [(HR 3.2; 95% CI 2.0 to 5.3;(p <0.0001)] and RFS [(HR 2.7; 95% CI 1.3 to 5.4;(p=0.0004)] as compared to ELN-22 favorable risk. Similarly, patients classified as ELN22-intermediate risk had inferior OS [(HR 1.8; 95% CI 1.1 to 3.0] and RFS [(HR 1.4; 95% CI 0.9 to 2.0] as compared to ELN22 favorable risk. Based on supervised ML in the ELN-favorable group, high NPM1 (≥37.8%), RAD21 (≥14.74), WT1 VAF (≥42.87), presence of ETV6 and KIT exon17 mutations were each assigned a negative point whereas NRAS mutations were assigned a positive point. For ELN-intermediate risk, high FLT3-ITD VAF (≥18.57%) and WT1 mutation were each assigned a negative point. No significant feature could be identified in ELN22 adverse group. In each ELN22 risk, the presence of a cumulative negative score was assigned to a subgroup (ELN22 Favorable II (n=81), ELN22 Intermediate II(n=43)) and those with positive scores to another subgroup (ELN22 Favorable I (n=194), ELN22 Intermediate I(n=114)). The median OS of ELN22 Favorable II [42.2 months, (95% CI 22.1 to 87.3 months) HR: 0.96 (95% CI 0.6-1.53)] was similar to ELN22 Intermediate I risk group [34.8 months, (95% CI 23.8 to 86.0 months); HR: 1.04 (95% CI 0.7-1.7)] but greatly different from ELN Favorable I group [median not reached, HR: 2.01 (95% CI 1.3-3.1)]. Similarly, the median OS of ELN22 Intermediate II [15.9 months, (95% CI 12.8 to 70.9 months) HR: 0.72 (95% CI 0.4-1.4)] was similar to ELN22 adverse risk group [16.6 months, (95% CI 12.4 to 20.7 months); HR: 1.4 (95% CI 0.7-2.7)]. The median RFS of ELN22 Favorable II [42.4 months, (95% CI 23.6 to 71.8 months) HR: 1.04 (95% CI 0.6-1.8)] was similar to ELN22 Intermediate I risk group [38.4 months, (95% CI 23.4 to 52.3 months); HR: 0.96 (95% CI 0.6-1.6)]. However, the median RFS of ELN22 Intermediate II [35.2 months, (95% CI 11.9 to 87.9 months) HR: 0.65 (95% CI 0.2-1.8)] was superior to ELN22 adverse risk group [21.1 months, (95% CI 10.0 to 63.8 months); HR: 1.5 (95% CI 0.6-4.2)]. This classification proposal was independently validated on the BEAT-AML2 dataset (Bottomly et al, 2022), where the ELN adverse group had different survival rates when compared to ELN favorable I and II risk groups (HR 2.3; 95%CI 1.66-5.0 & HR 4.8; 95%CI 3.5 to 6.5 respectively). Such observations were not made for the ELN intermediate risk group in the BEAT-AML2 cohort.

Conclusion: We demonstrate the applicability of ELN2022 risk stratification for AML and suggest improvements based on the incorporation of additional genes and mutational VAF.

Disclosures: Patkar: Illumina Inc: Research Funding.

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