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Defining the Incidence and Clinical Impact of Genomic Alterations Across Different Histologic Types of Lymphoma Using a Clinically Validated Comprehensive Targeted Sequencing Assay

Connie Batlevi, Franck Rapaport, Andrew M. Intlekofer, Anne Reiner, Craig H Moskowitz, Steven M Horwitz, Andrew D Zelenetz, Lia Palomba, Alison J Moskowitz, John F. Gerecitano, Paul A Hamlin Jr., Amanda R. Copeland, Matthew J Matasar, Craig S. Sauter, Anita Kumar, Ariela Noy, David J. Straus, Carol S. Portlock, Frederick Criscuolo, Jie He, Daniel Royston, Sohail Balasubramanian, Yekaterina Reznikovskaya, Janine D. Pichardo, Phil Stephens, Vincent Miller, Ross L. Levine, Venkatraman Seshan, Ahmet Dogan and Anas Younes

Abstract

Background:

Lymphoma is a clinically and molecularly heterogenous disease. Next generation sequencing of primary lymphoma samples has identified common recurring genomic alterations (GAs). The distribution and frequency of recurring GAs across lymphoma subtypes remains unknown because prior studies vary in sequencing methods, depth of coverage, and specimen source. In this study, we benchmark the distribution of GAs across different lymphoma subtypes by prospectively analyzing lymphoma cases and performing comprehensive DNA/RNA targeted sequencing of genes commonly found in hematologic malignancies using the Foundation One Heme (F1H) clinical assay.

Methods:

After obtaining proper consent, archived specimens from 183 samples [formalin fixed paraffin embedded (FFPE) N=141, peripheral blood N=28, BM aspirate N=14] distributed across lymphoma subtypes (including 62 DLBCL, 38 T cell lymphoma, 32 FL, 17 CLL, 13 MCL) were sequenced to high, uniform coverage averaging >600x for DNA, >20 million pairs for RNA. GAs were determined, including base substitutions, small insertions and deletions, rearrangements, and copy number alterations. Significant non-synonymous variants were identified as mutations from the COSMIC database, amplifications of established oncogenes, or homozygous deletions and/or clear loss-of-function mutations of known tumor suppressors. Fisher's exact test with Monte Carlo estimation corrected by false discovery rate was used for associations.

Results:

Samples from prospectively consented patients were banked for a median of 30 days prior to genomic analysis, range 1 day to 6.5 yr. Sequencing data was reported a median of 16 days from sample date receipt. GAs were identified in 95% of samples, with a median of 4 GAs/sample. The most common GAs were TP53 (29%), MLL2 (27%), BCL2 (25%), CDKN2A/B (17%) and CREBBP (14%). Alterations of chromatic modifiers (80%), BCR/NFkB components (51%), and cell cycle pathway (44%) were most common. In our group of unpaired follicular lymphoma samples (N=7 treatment naïve, N=25 treatment exposed), the number of GAs increased with treatment exposure. We found similar gene and biological signatures regardless of prior therapy; however differences emerge in genes of potential clinical relevance. Sequencing profiles augmented or altered the pathologic diagnosis in 11 of 183 (6%) of the cases. Importantly we were able to classify the GAs as actionable, potentially actionable and variants of unclear significance to better define the clinical relevance of targeted genomic sequencing.

Conclusions:

Integration of comprehensive next generation targeted genomic sequencing and clinical analysis in lymphoma provides an opportunity to describe the spectrum and incidence of GAs across different lymphoma subtypes and provide guidance on application of genomic profiling. This work serves to benchmark GAs across all lymphoma subtypes in a clinically relevant population and enables design of basket trials selecting patients based on shared genomic and biologic similarity instead of lymphoma subtype. To our knowledge, this is the largest repository of clinically annotated genomic sequencing in lymphoma.

Total SpecimensN = 183
Median Age at Diagnosis57Range 21 - 84
Median Age at Biopsy61Range 21 - 91
Sex
• Male
• Female
113
70
62%
38%
Biospecimen source
• Paraffin embedded
• Peripheral blood
• Marrow aspirate
141
28
14
77%
15%
8%
Patient consent
• Prospective consent
• Retrospective consent
145
38
79%
21%
Prospectively consented patients (N=145)
Median Days to Result
Median Age of Sample
16
30 days
8 - 81
1 day - 6.5 yr
Table 1.

Disclosures Palomba: Janssen: Consultancy. Gerecitano: Genentech: Consultancy, Other: Advisory Board; AbbVie: Consultancy, Other: Advisory Board. Matasar: Spectrum: Consultancy; Genentech: Consultancy. Straus: Millenium Pharmaceuticals: Research Funding. He: Foundation Medicine, Inc.: Employment, Equity Ownership. Balasubramanian: Foundation Medicine: Employment, Equity Ownership. Stephens: Foundation Medicine, Inc.: Employment, Equity Ownership. Miller: Foundation Medicine: Employment. Levine: Loxo Oncology: Membership on an entity's Board of Directors or advisory committees; CTI BioPharma: Membership on an entity's Board of Directors or advisory committees; Foundation Medicine: Consultancy. Younes: Celgene: Honoraria; Johnson and Johnson: Research Funding; Novartis: Research Funding; Bayer: Honoraria; Bristol Meyer Squibb: Honoraria; Sanofi-Aventis: Honoraria; Seattle Genetics: Honoraria, Research Funding; Curis: Research Funding; Janssen: Honoraria; Takeda Millenium: Honoraria; Incyte: Honoraria.

  • * Asterisk with author names denotes non-ASH members.