Defining the Incidence and Clinical Impact of Genomic Alterations Across Different Histologic Types of Lymphoma Using a Clinically Validated Comprehensive Targeted Sequencing Assay
Authors: Batlevi Connie , Rapaport Franck , Intlekofer Andrew M. , Reiner Anne , Moskowitz Craig H , Horwitz Steven M , Zelenetz Andrew D , Palomba Lia , Moskowitz Alison J , Gerecitano John F. , Hamlin Paul A , Copeland Amanda R. , Matasar Matthew J , Sauter Craig S. , Kumar Anita , Noy Ariela , Straus David J. , Portlock Carol S. , Criscuolo Frederick , He Jie , Royston Daniel , Balasubramanian Sohail , Reznikovskaya Yekaterina , Pichardo Janine D. , Stephens Phil , Miller Vincent , Levine Ross L. , Seshan Venkatraman , Dogan Ahmet , Younes Anas 
Published: October 2019

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.

Table 1. Total Specimens N = 183 Median Age at Diagnosis 57 Range 21 - 84 Median Age at Biopsy 61 Range 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

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.