Abstract 3765: Somatic JAK-STAT mutations in subtypes of aggressive B-cell lymphomas with DLBCL morphology
Bibliographic record
Abstract
Abstract Aberrant activation of the JAK-STAT pathway is a hallmark of a variety of lymphomas and can alter the lymphoma cells secretome and the composition of the tumor microenvironment (TME). The up-regulation of the immune regulatory chemokine CCL17 has been shown to be mediated by STATs-dependent mechanism in primary mediastinal B cell lymphoma (PMBCL). Here, we assembled a cohort of 340 R-CHOP-treated aggressive lymphomas with diffuse large B cell lymphoma (DLBCL) morphology to investigate JAK-STAT mutations (targeted gene sequencing), copy number (CN) alterations (SNP arrays), gene expression (RNAseq) and TME composition (IHC). The cohort was evaluated using FISH for BCL2, BCL6 and MYC rearrangements and the molecular classification assay, Lymph2Cx, to distinguish ABC vs GBC vs double-hit lymphomas with DLBCL morphology (DH-DLBCL). Among the 317 evaluable cases, 26 were DH-DLBCLs, 101 ABC, 155 GCB and 35 unclassified. In addition, we used the recently published Lymph3Cx assay (Mottok A. et al., Blood 2018) to identify cases with a molecular PMBCL (mPMBCL) expression signature within the GCB-DLBCL group (6.5%, 10/155 cases). Twenty-five of 155 GCB cases (16.1%) were classified as ‘uncertain PMBCL/DLBCL’. Mutational analysis of all cases (n=340) revealed the presence of JAK-STAT pathway mutations at the following frequencies: SOCS1 21.6%, STAT6 4.8%, IL4R 5.3% and 9p24 amplification 11.3%. These mutations were significantly enriched in the mPMBCL (n=10) group compared to the bona fide GCB (n=118) and intermediate phenotype group (uncertain PMBCL/DLBCL) (n=25) (p<0.05). The relative frequency of any JAK-STAT mutations was 100% (10/10) in mPMBCL, 29.2% (35/118) in bona fide GCB and 56% (14/25) in uncertain PMBCL/DLBCL. Among the GCB samples with follow-up data (n=107, incl. bona fide GCB and mPMBCL), cases carrying mutations in IL4R (n=11, 10.3%) had an inferior disease-specific survival (p=0.011) and time to progression (p=0.0048) after R-CHOP therapy. Interestingly, IL4R mutations were also detected in the DH-DLBCL group with an incidence of 11.5% (3/26 cases). Mutations in the extracellular and transmembrane domains of IL4R resulted in gain-of-function mutations leading to constitutive activation of the JAK-STAT pathway in vitro. IL4R gain-of-function increased CCL17 expression through a STAT6-dependent mechanism in vitro. Similarly, gene expression analysis of primary patient samples carrying activating IL4R mutations displayed increased CCL17expression (p<0.05), which positively correlated with the level of the T-regulatory marker FOXP3 (p<0.05) by IHC. In summary, aberrant JAK-STAT activation driven by alterations, such as activating IL4R mutations, plays a significant role in altering chemokine expression profiles and TME changes. Our data strongly suggest the biological and clinical relevance of Lymph3Cx to define a subgroup of aggressive lymphoma harboring a molecular PMBCL signature. Citation Format: Elena Vigano, Gerben Duns, Daisuke Ennishi, Clementine Sarkozy, Bruce Woolcock, Faith Cheung, Elizabeth Chavez, Stacy S. Hung, Katsuyoshi Takata, Anja Mottok, Randy Gascoyne, Kerry J. Savage, Ryan Morin, David W. Scott, Christian Steidl. Somatic JAK-STAT mutations in subtypes of aggressive B-cell lymphomas with DLBCL morphology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3765.
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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 | 0.001 |
| 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 | 0.001 | 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".