FUNCTIONAL CHARACTERIZATION OF <i>NFKBIZ</i> 3′ UTR MUTATIONS IN DIFFUSE LARGE B‐CELL LYMPHOMA
Bibliographic record
Abstract
Introduction: The activated B-cell-like (ABC) subtype of diffuse large B-cell lymphoma (DLBCL) is characterized by activation of NF-kB signaling and an increased risk of mortality. Recurrent somatic mutations affecting genes such as MYD88, CD79A/B and TNFAIP3 have been shown to constitutively activate the NF-kB pathway through B-cell receptor signaling in ABC DLBCL; however, there still remain cases with no known genetic basis for this pathway activation (Arthur et al. Nat Com 2018). We recently published a meta-analysis of DLBCL genome and targeted sequencing data identifying non-coding mutations. We described novel mutations affection the 3′ untranslated region (UTR) of NFKBIZ in 18% of ABC DLBCLs. Overall, NFKBIZ is mutated (amplifications and UTR mutations) in 34% of ABC DLBCLs. These NFKBIZ mutations are mutually exclusive with MYD88 mutations, implicating them in activation of the NF-kB signaling pathway. NFKBIZ encodes the IkB-ζ protein, which interacts with NF-kB transcription factors and is thought to regulate canonical NF-kB signaling. We hypothesized that these mutations affect the ability of regulatory mechanisms to target this transcript for degradation through disruption of UTR secondary structures. This leads to enhanced mRNA stability and elevated protein levels and represents a novel mechanism of promoting NF-kB signaling in ABC DLBCL. Methods: NFKBIZ 3′ UTR mutations were introduced in a DLBCL cell line using CRISPR-Cas9. NFKBIZ mRNA and protein levels were evaluated using custom designed droplet digital PCR assays and western blot. RNA-sequencing was performed on mutant and wild-type (WT) cell lines to identify genes up-regulated by IkB-ζ. A competitive growth assay with WT and CRISPR mutant lines was set up to assess whether UTR mutations provide a growth advantage in culture. The pool composition was determined by DNA sequencing and comparison of WT and mutant DNA sequences. Results: Introduction of NFKBIZ mutations into DLBCL cell lines confirmed that UTR deletions lead to increased levels of mRNA and protein. Stimulation with LPS revealed that mRNA levels stay elevated for longer in mutant lines. NFKBIZ UTR deletions also give DLBCL cells a selective growth advantage over WT when grown together in culture. RNA-sequencing of mutant and WT lines revealed possible transcriptional targets of IkB-ζ, including TNFRSF14B, HCK, GNAZ, BATF and CD274. These targets are either involved in activation of NF-kB signaling, associated with decreased survival in other lymphomas or potential new drug targets in NFKBIZ mutant DLBCL. Conclusions: This work highlights the role of NFKBIZ and 3′ UTR mutations in driving ABC DLBCL. We demonstrate that these UTR mutations can lead to over-expression of NFKBIZ and activate potentially novel drug targets in ABC DLBCL. These findings contribute to a better understanding of the genetic basis of DLBCL, which is necessary to guide personalized therapeutic strategies. Keywords: activated B-cell-like (ABC); molecular genetics; NF-kB.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 teacher head, 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".