<i>TRAF3</i> Loss Drives Alternative NF-κB Pathway Activation in Diffuse Large B-Cell Lymphoma
Bibliographic record
Abstract
Introduction: Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is a transcription factor family that regulates gene expression programs contributing to inflammation and cell survival. NF-κB signaling occurs via two branches: classical and alternative, and is often enriched in somatic mutations of key pathway members in several lymphoid malignancies. Here, we reveal deregulation and constitutive activation of the alternative NF-κB pathway in a subset of DLBCL patients with recurrent genomic loss of the gene encoding tumor necrosis factor receptor-associated factor 3 (TRAF3), a regulator of the NF-κB signaling pathway. Methods and Results: To uncover novel driver mutations of DLBCL pathogenesis and tumor maintenance, we performed Affymetrix SNP6.0 copy number analysis on 347 de novo DLBCL samples from patients uniformly treated with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP). We observed frequent, focal genomic loss of chr:14q32.31-32 which included TRAF3 and RCOR1 (7%, 22/313) in the minimally deleted region and an enrichment of activated B-cell-like (ABC) subtype cases over germinal center B-cell-like (GCB) subtype cases, confirming previously published data (Chan et al, Blood 2014). RNAseq of these DLBCL samples revealed a significant reduction of TRAF3 mRNA in chr:14q32.31-32 deleted cases compared to copy number neutral cases (p=0.002). Next, we focused on characterizing the phenotypic consequences of TRAF3 loss in DLBCL. We used CRISPR/Cas9 gene editing to knock out TRAF3 in 2 GCB-DLBCL (DOHH2, OCI-LY1) and 2 ABC-DLBCL (HBL1, OCI-LY3) cell lines. We performed immunoblotting analysis of NF-κB pathway members on cell fractionated samples of TRAF3 knockout cells and found increased levels of the NF-κB inducing kinase NIK (a direct target of TRAF3-mediated ubiquitin-proteasome degradation) and a concomitant increased nuclear translocation of NF-κB transcription factor complex subunits RelB and p52. Proteasome blockade restored RelB cytoplasmic localization and reduced processed p52 protein in TRAF3 knockout GCB-DLBCL lines only, indicating other factors may contribute to alternative NF-κB activation in ABC-DLBCL. Moreover, classical NF-κB activation remained unaffected, highlighting the specific role of TRAF3 regulation on the alternative NF-κB pathway in DLBCL. Consistent with these findings, TRAF3 knockout cells exhibited NF-κB-dependent transcriptional upregulation by luciferase reporter activity and elevated pro-inflammatory cytokine production (IL-6, TNF-β) by Luminex and ELISA. To study transcriptome changes as a result of TRAF3 loss-of-function, we performed RNAseq and differential gene expression analysis on wildtype and TRAF3 knockout DLBCL cell lines as well as primary DLBCL samples (N=347). We found enrichment of NIK and NF-κB associated pathways in TRAF3 deficient DLBCL and uncovered additional enriched gene sets including those involved in cell cycle regulation, cell division and metabolism, suggesting a potential proliferative and survival advantage. Conclusion: Our findings link TRAF3 loss-of-function to clinical and gene expression phenotypes in DLBCL and highlight alternative NF-κB activation as a pathogenically important pathway in both GCB and ABC subtypes. Future studies will be directed towards comprehensive evaluation of NF-κB inhibitors for effective blockade of constitutive alternative NF-κB activation in DLBCL. Disclosures Scott: NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Janssen: Consultancy, Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding. Steidl:Roche: Consultancy; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; AbbVie: Consultancy.
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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 | 0.000 | 0.000 |
| 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".