Abstract 2445: Integrative genetic analysis identifies therapeutic relevance of cell of origin-specific genetic alterations in diffuse large B-cell lymphoma
Bibliographic record
Abstract
Abstract Introduction: Diffuse large B-cell lymphoma (DLBCL) comprises two distinct cell-of-origin (COO) subtypes: the germinal center B-cell-like (GCB) and the activated B-cell-like (ABC) subtypes. Several sequencing studies have informed on DLBCL biology and identified numerous candidate genes implicated in pathogenesis. However, comprehensive analysis of recurrent genetic alterations, and related prognostic significance according to COO subtypes has not yet been performed. To understand the molecular distinctions and their therapeutic relevance specific to COO subtype in DLBCL, we performed a comprehensive genetic analysis on a population registry-based cohort of 347 patients with de novo DLBCL uniformly treated with R-CHOP. Methods: Tissue biopsies from 347 patients were analyzed using deep amplicon sequencing of 58 genes, Affymetrix SNP 6.0 arrays, and RNAseq. Immunohistochemical staining was performed on tissue microarrays. COO subtype was assigned by Lymph2Cx assay. Results: We detected COO-specific mutations, copy number alterations (CNAs) and gene fusions. Furthermore, integrative analysis showed COO-specific trans gene expression effects on CNAs, demonstrating that CNAs in GCB-DLBCL are tightly linked to the deregulation of networks associated with PI3K-AKT signaling. We also identified the significant prognostic impact of recurrent genetic alterations within each COO subtype, including deletions of MIR15a/16-1 and TP53 and NFATC1 gain in ABC-DLBCL, TP53 and CREBBP mutations, PRAME deletions and MYC gain in GCB-DLBCL. In addition, deletions of PTEN and INPP4B, which are negative regulators of PI3K-AKT signaling, were individually associated with poor outcome in GCB-DLBCL (p=0.01 and p=0.045, respectively). Furthermore, patients whose tumors harbored both genetic alterations had an even worse prognosis (p=0.004), suggesting the clinical importance of PI3K-AKT signaling in GCB-DLBCL. Based on these genetic data, we found that the PI3K-AKT signaling pathway was more commonly altered in GCB-DLBCL than in ABC-DLBCL (64% vs 23%, p<0.0001). We also confirmed frequent genetic alterations involved in the BCR-NFκB signaling pathway in ABC-DLBCL (80%), while this pathway was less frequently altered in GCB-DLBCL (54%; p<0.0001). In addition, epigenetic modification and immune recognition pathways were more commonly altered in GCB-DLBCL compared to ABC-DLBCL (70% vs 44%; p<0.0001, 71% vs 56%; p=0.015, respectively). Finally, we demonstrated that the majority of DLBCL cases are altered for at least two of the four pathways mentioned above (86% of ABC-DLBCL and 87% GCB-DLBCL). Conclusion: we describe the landscape of common genetic aberrations in a population-based uniformly-treated DLBCL cohort, broadly representative of patients treated with curative intent, providing the genetic foundation for implementing precision medicine in this disease. Citation Format: Daisuke Ennishi, Ali Bashashati, Saeed Saberi, Anja Mottok, Barbara Meissner, Merrill Boyle, Susana Ben-Neriah, Robert Kridel, Kerry J. Savage, Laurie H. Sehn, Joseph M. Connors, Ryan D. Morin, Marco A. Marra, Sohrab P. Shah, Christian Steidl, David W. Scott, Randy D. Gascoyne. Integrative genetic analysis identifies therapeutic relevance of cell of origin-specific genetic alterations in diffuse large B-cell lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2445. doi:10.1158/1538-7445.AM2017-2445
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".