Abstract PO-32: NFKBIZ 3′ UTR mutations confer selective growth advantage and affect drug response in diffuse large B-cell lymphoma
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Introduction: The activated B cell-like (ABC) molecular subgroup of diffuse large B-cell lymphoma (DLBCL) is characterized by activation of NF-κB signaling. Recurrent mutations affecting genes such as MYD88, CD79A/B, and TNFAIP3 contribute to this in some cases, but there remain tumors with no known genetic basis for this pathway activation. This suggests that our understanding of ABC DLBCL drivers remains incomplete. Previously, NFKBIZ was shown to be amplified in 10% of ABC DLBCLs and to contribute to activation of NF-κB signaling. We recently described a novel pattern of mutations affecting the 3′ UTR of NFKBIZ resulting in an overall mutation rate of 30% (UTR or AMP) in ABC DLBCL. These NFKBIZ UTR mutations are mutually exclusive with MYD88 mutations, thus suggesting they may also lead to activation of NF-κB signaling. The NFKBIZ protein interacts with NF-κB transcription factors and is thought to regulate canonical NF-κB signaling. We hypothesized that NFKBIZ UTR mutations affect the normally rapid degradation of this mRNA by disrupting secondary structures recognized by RNA-binding proteins such as ribonucleases. The resulting elevated NFKBIZ mRNA levels would lead to accumulation of protein and may be a novel mechanism to promote cell growth and survival in ABC DLBCL. Methods: NFKBIZ 3′ UTR mutations were introduced into a DLBCL cell line using the CRISPR-Cas9 system. A competitive growth assay with wild-type (WT) and CRISPR-mutant lines was performed to assess whether UTR mutations provide a growth advantage in culture (in vitro) and in mouse xenografts (in vivo). RNA-sequencing was then performed on WT and a subset of CRISPR-mutant lines and analyses were performed to identify genes upregulated by IκB-ζ in mutant lines. The IC50 of relevant drugs was determined by WST-1 assays after drug treatment on WT and mutant lines. Results: Introduction of NFKBIZ mutations into a DLBCL cell line confirmed that UTR deletions lead to increased mRNA and protein levels. NFKBIZ UTR deletions give DLBCL cells a selective growth advantage over WT both in vitro and in vivo. RNA-sequencing of mutant and WT lines revealed possible transcriptional targets of NFKBIZ, including NF-κB targets and genes commonly overexpressed in ABC DLBCL. Novel candidate NFKBIZ targets were also discovered through this analysis, including CD274, the gene encoding PD-L1. Mutant cell lines had significantly higher IC50 compared to WT for the drugs ibrutinib, idelalisib, and masitinib, but not bortezomib, suggesting that NKFBIZ UTR mutations make cell lines more resistant to specific NF-κB pathway-targeted drugs. Conclusions: This work directly establishes a role for NFKBIZ amplifications and 3′ UTR mutations in driving ABC DLBCL through NF-κB signaling. We demonstrate that these mutations can lead to overexpression of NFKBIZ and provide a selective growth advantage to cells both in vitro and in vivo. In addition, we found that these mutant lines were more resistant to some targeted lymphoma drugs but not others. Citation Format: Sarah E. Arthur, Nicole Thomas, Jeffrey Tang, Christopher K. Rushton, Miguel Alcaide, Adèle Telenius, Shannon Healy, Anja Mottok, David W. Scott, Christian Steidl, Ryan D. Morin. NFKBIZ 3′ UTR mutations confer selective growth advantage and affect drug response in diffuse large B-cell lymphoma [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr PO-32.
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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) | 0.000 | 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) | 0.000 | 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 it