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540 Targeted Sequencing of 7 Genes Can Help Reduce Pathologic Misclassification of MDS

Program: Oral and Poster Abstracts
Type: Oral
Session: 637. Myelodysplastic Syndromes—Clinical Studies: Personalized Clinical-Decision Tools and treatment of lower risk MDS
Monday, December 7, 2020: 8:00 AM

Johannes B Goll, MSc1*, Travis L Jensen, BS1*, R. Coleman Lindsley, MD, PhD2, Rafael Bejar, MD, PhD3, Jason Walker4*, Robert Fulton, MS5*, Gregory A. Abel, MD, MPH6, Tareq Al Baghdadi, MD7*, H. Joachim Deeg, MD8, Amy E. DeZern, MD9, Benjamin L. Ebert, MD, PhD10, James M. Foran, MD11, Edward J. Gorak, DO, MBA, MS12, Steven D. Gore, MD13, Rami Komrokji, MD14, Jane Jijun Liu, MD15*, Jaroslaw P. Maciejewski, MD, PhD16,17, Eric Padron, MD18, Wael Saber, MD, MS19, Daniel Starczynowski, PhD20, Myron Waclawiw, PhD21*, Steffanie H. Wilson, PhD1*, Donnie Hebert, PhD22*, Harrison Reed, MSc1*, Nancy L. DiFronzo, PhD21*, Mikkael A. Sekeres, MD, MS23, Alexandra M. Harrington, MD, MT(ASCP)24, Steven H. Kroft, MD25*, Ling Zhang, MD26* and Matthew J. Walter, MD27

1The Emmes Company, LLC, Rockville, MD
2Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
3Moores Cancer Center, University of California, San Diego, La Jolla, CA
4Washington University School of Medicine, St. Louis, MO
5McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO
6Dana-Farber Cancer Institute, Boston, MA
7IHA Hematology Oncology Consultants, Ypsilanti, MI
8Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA
9Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD
10Division of Hematology, Harvard Medical School, Boston, MA
11Division of Hematology and Medical Oncology, Mayo Clinic, Jacksonville, FL
12Baptist MD Anderson Cancer Center, Jacksonville, FL
13National Institutes of Health, National Cancer Institute, Rockville, MD
14H. Lee Moffitt Cancer Center, Tampa, FL
15Illinois Cancer Care, P.C., Peoria, IL
16Cleveland Clinic Main Campus, Department of Hematology/Oncology, Cleveland, OH
17Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH
18Department of Malignant Hematology, Moffitt Cancer Center, Tampa, FL
19CIBMTR, Medical College of Wisconsin, Milwaukee, WI
20Cincinnati Children's Hospital Medical Center, Cincinnati, OH
21National Heart, Lung, and Blood Institute, National Institutes of Health, Division of Blood Diseases & Resources, Bethesda, MD
22The Emmes Company, LLC, Hamburg, NY
23Leukemia Program, Department of Hematology and Medical Oncology, Cleveland Clinic Taussig Cancer Institute, Cleveland, OH
24Medical College of Wisconsin, Milwaukee, WI
25Department of Pathology, Medical College of Wisconsin, Milwaukee, WI
26Department of Hematopathology and Laboratory Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
27Department of Medicine, Division of Oncology, Washington University In St. Louis, Saint Louis, MO

Introduction: The NHLBI National MDS Study (NCT02775383) is a prospective cohort study conducted at 92 community hospitals and 29 academic centers. It enrolls patients undergoing work up for suspected MDS to understand the genetic, epigenetic, and biological factors associated with the initiation and progression of the disease. Previously untreated, cytopenic participants undergo both local and centralized pathology review and are assigned a diagnosis, including MDS, MDS/MPN, AML with blasts < 30%, and “Other”. Emerging data suggests that Next Generation Sequencing (NGS), along with cytogenetics and clinical variables, may improve MDS diagnostic precision. Given that our study relies on central review (with additional tertiary pathology review used to adjudicate disagreements), we examined whether targeted gene sequencing data could be used to increase the agreement between local and central pathologic diagnosis of MDS vs. Other.

Methods: Peripheral blood and bone marrow (BM) biopsy specimens from cytopenic patients, along with clinical history, CBC, and other results including karyotyping, FISH and pathology reports from local pathologists were reviewed by central pathologists. The updated 2016 WHO classifications were used to diagnose MDS. Targeted exon sequencing of 96 genes was performed using BM specimens. A subset of 648 individuals that were classified as MDS (n=212) or Other (n=436, including 90 CCUS and 89 individuals with other cancers) by pathology assessments were selected. A mean coverage of 1,317X was achieved and variants had a minimum variant allele frequency (VAF) of 2% (except FLT3). Variants for 596 subjects were manually reviewed to retain likely disease-causing variants to build a binary classifier (MDS vs. Other) using the maximum VAF per gene as input (Figure 1). Subjects diagnosed with MDS or Other by both central and local pathology were used for training, validation, and testing, and were considered “gold standard” (GS) cases (n=546). These subjects were split into 4 random groups with equal proportions of MDS cases. 75% of the GS cases were used to train and validate lasso-regularized logistic regression models using 3-fold cross validation. ROC curve analysis was carried out using the remaining 25% of GS cases (Test Set 1) on the best model to identify an optimal probability cut off point for classifying subjects as MDS. Model performance was then tested on 50 subjects for which the central and local pathology diagnosis disagreed (Test Set 2), as well as on 52 additional subjects irrespective of agreement (Test Set 3).

Results: The best performing logistic regression model retained 7 genes as most informative in a discriminating diagnosis of MDS from Other based on their VAFs, in order of impact: TP53, SF3B1, U2AF1, ASXL1, TET2, STAG2, and SRSF2. We used this model to assign probabilities for each of the subjects in Test Set 1 and to estimate the performance using ROC analysis (Figure 1), resulting in a high area under the curve (AUC) of 0.89. We chose a probability cut-off of ≥0.17, being associated with a high percentage of correct classification of MDS with a sensitivity and specificity of 0.90 and 0.81, respectively. Among the cohort of 50 subjects with a discordant local and central pathology diagnosis (Test Set 2), the classifier accurately reassigned 37 subjects (accuracy = 74%) from the local to the central pathology. The blinded tertiary pathology reviewer agreed with central in all Test Set 2 cases. This included 24/34 MDS cases that had been labeled as Other by local pathology (positive predictive value [PPV]=0.89). 3/16 final pathology-classified Other cases were mis-classified as MDS by the local pathologist (negative predictive value [NPV] = 0.57). Next, we assessed the ability of the model to predict MDS vs. Other for 52 additional independent subjects using the third pathologist’s diagnosis to break any ties (Test Set 3). The classifier correctly predicted 15/21 MDS cases (PPV=0.83) and misclassified 6/31 Others as MDS (NPV=0.82). The overall accuracy was 83%.

Conclusions: We identified that VAFs for 7 genes can correctly re-classify subjects as either MDS or Other in 74% of cases that were misclassified between local and central pathology review. Further assessment on an independent cohort showed an accuracy of 83% of the model. Taken together, these data suggest that complementing pathology reviews with targeted sequencing of 7 genes could improve MDS diagnosis.

Disclosures: Lindsley: Bluebird Bio: Consultancy; MedImmune: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Takeda Pharmaceuticals: Consultancy. Bejar: Aptose Biosciences: Current Employment; AbbVie/Genentech: Honoraria; Astex/Otsuka: Honoraria; Takeda: Honoraria, Research Funding; Celgene/BMS: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria; Forty-Seven/Gilead: Honoraria; Genoptix/NeoGenomics: Honoraria. DeZern: MEI: Consultancy; Astex: Research Funding; Abbvie: Consultancy; Celgene: Consultancy, Honoraria. Foran: H3Biosciences: Research Funding; Aptose: Research Funding; Kura Oncology: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Revolution Medicine: Consultancy; Xencor: Research Funding; Agios: Honoraria, Research Funding; Aprea: Research Funding; Actinium: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding. Gore: Abbvie: Consultancy, Honoraria, Research Funding. Komrokji: Acceleron: Honoraria; Incyte: Honoraria; Abbvie: Honoraria; Agios: Speakers Bureau; BMS: Honoraria, Speakers Bureau; Jazz: Honoraria, Speakers Bureau; Geron: Honoraria; Novartis: Honoraria. Maciejewski: Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria. Padron: Novartis: Honoraria; BMS: Research Funding; Incyte: Research Funding; Kura: Research Funding. Starczynowski: Captor Therapeutics: Consultancy; Tolero Therapeutics: Research Funding; Kurome Therapeutics: Consultancy, Current equity holder in private company, Research Funding. Sekeres: BMS: Consultancy; Takeda/Millenium: Consultancy; Pfizer: Consultancy.

*signifies non-member of ASH