Bibliographic record
Abstract
Abstract The complexity of gene expression regulation is the result of a composite interplay between promoters, enhancers and other cis-acting regulatory elements bound by transcription factors (TFs) that controls the transcriptional activity of genes. Primary tumor cells, in comparison to their healthy counterparts, are known to display altered enhancer repertoires that are associated with tumor-specific transcription. Large groups of transcriptional enhancers cluster together to form super-enhancers (SEs). These elements have been shown to control genes that are important for maintaining cell identity but are also frequently associated with oncogenes as well as translocations that result in aberrant gene expression in cancer. Immunoglobulin (IGH, IGL, IGK) and non-immunoglobulin (PVT1, FAM46C, DUSP22, etc.) enhancers hijacking by variable genes (MYC, MAF, CCND1/2/3, MMSET, IRF4) is a recognized oncogenic driver event in multiple myeloma (MM). However, the identity of the TFs or transcriptional regulatory complexes binding and regulating the activity of these enhancers remains to be fully elucidated and may yield valuable therapeutic targets. In this regard, the bromodomain and extra-terminal (BET) inhibitors have emerged as promising molecules for the treatment of hematologic malignancies. BET family proteins are chromatin adaptors, functionally linked to important pathways for cellular viability and cancer signaling. In particular, BRD4 has a direct role in the transcription regulation of different genes involved in the cell cycle progression and cellular viability. The BET inhibitor JQ1 selectively inhibits BRD4 by competitively binding to the acetyl-lysine recognition pocket of BET bromodomains from chromatin leading to the inhibition of MYC transcription in a dose- and time-dependent manner. Thus, BRD4 has been recently described as a therapeutic target for MM, among other hematologic diseases. Constitutive activation of MYC signaling is detected in more than 60% of patient-derived MM cells and can be involved in the pathogenesis of MM through different mechanisms. One of the most common somatic genomic aberrations in early and late-stage MM is rearrangement or translocation of MYC. Regardless of whether MYC rearrangements occur at early or late stages of MM pathogenesis, MYC rearrangements may provide one of several critical events contributing to increased autonomy and a more aggressive phenotype. Moreover promiscuous rearrangements of the MYC locus are known to hijack enhancers and super-enhancers to dysregulate MYC expression in MM and are involved in its pathogenesis. The development of the immunomodulatory drugs (IMiDs) has contributed significantly to improve the outcomes of MM patients. They possess pleiotropic anti-MM properties and through CRBN binding they induce Ikaros and Aiolos ubiquitylation and proteasomal degradation with an ensuing transcriptional repression of MYC and IRF4, two essential factors for myeloma cells survival. However, is not clear how IKZF1/IKZF3 regulate MYC transcription and how myeloma cells acquire resistance to IMIDs, "beyond CRBN". In addition, acquired resistance to IMIDs and the loss of the transcriptional repression of MYC are nearly universal and occur in spite of sustained IKZF1/3 degradation suggesting that transcriptional rewiring may be sustaining hijacked enhancers activity and transcription of driver oncogenes. In this contest we have recently demonstrated that IMiDs are repressors of IKZF1/3-depedent oncogenic enhancers. Transcriptional plasticity with expression of extra-lineage TFs such as the ETS family member ETV4 sustains oncogenic enhancers in MM overcoming IKAROS and AIOLOS dependency and promoting IMiDs resistance. Therefore defining TFs occupancy and their circuitry at enhancers identifies "non-canonical" (aberrant) myeloma TFs dependency that may be linked to potential therapeutic targets. Disclosures Neri: Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".