Cancer-Specific Nuclear Positioning of Translocation Prone Gene Loci In Non-Malignant B-Cells From Patients with Multiple Myeloma
Bibliographic record
Abstract
Abstract Abstract 783 Malignant plasma cells from patients with multiple myeloma (MM) display recurrent chromosome translocations involving the immunoglobulin heavy chain locus (IGH) and CCND1 [t(11;14)] or FGFR [t(4;14)]. It is poorly understood why recombination events between chromosomes recur at specific breakpoints in the human genome, but spatial proximity of translocation-prone gene loci (TPGL) is influential. Utilizing 3D fluorescent in situ hybridization and 3D analysis techniques, we have measured the spatial and radial positioning of translocation-prone and control loci in the nuclei of non-malignant cells to determine a propensity to translocate. Purified CD34+ progenitors and CD19+ B cells were analyzed; none had translocations. Utilizing these cell subsets (n=900 cells) from MM patients having recurrent IGH translocations in autologous plasma cells, and comparable subsets (n=300 cells) from healthy donors, we show that spatial genome organization contributes to the formation of recurrent translocations. We show that IGH, CCND1, and FGFR3 are preferentially positioned in close proximity relative to each other in presumptively normal CD34+ progenitors and CD19+ B-cells from these MM patients, and that the clinical frequency of IGH translocations correlates with relative positioning (p=0.002 for CD34+ cells; p=0.017 for CD19+ cells), and with radial positioning (p=0.05 for CD34+ cells; p=0.043 for CD19+ cells). We also show that non-malignant CD19+ B-cells from MM patients display cancer-specific radial positioning of TPGL in the nucleus (p≤0.008), suggesting a predisposition to translocate. In addition to preferred positions within the nucleus, genes also localize to favoured locations within their respective chromosome territory (CT). Genes have been shown to position outside of their respective chromosome territory. Although proximity of potential translocation partners is necessary for translocation events to occur, others have shown that translocation events between adjacent chromosomes take place at CT boundaries, or in the space of intermingling between adjacent CTs. Active transcription ‘factories' are also present within the area of intermingling. We observed that at least one of the two alleles of CCND1 and FGFR3, is positioned outside of its chromosome territory in 59% of CD19+ cells from MM patients, whereas a control locus TGFBR2, is positioned outside its chromosome territory in only 25% of the same cells. We find myeloma-specific positioning of TPGL in a subset of B-cells that lack translocations and are predominantly polyclonal, defining them as non-malignant. It seems likely that the original parent B-cell that gave rise to MM also harboured spatially proximal TPGL prior to the formation of physically translocated loci. Together, these observations support the likelihood that translocations occur only in specific sites within the nucleus. Recent reports indicate that ongoing transcription is necessary for functional activity of IGH recombination enzymes, and that these same enzymes have off-target effects on proximal genes. IGH and its translocation partners FGFR3 and CCND1 may come together briefly to a transcription ‘factory' outside of their respective CTs and be acted upon by IGH recombination enzymes. We speculate that cancer-specific positioning of active TPGL in B-cells from MM patients promotes the formation of clinically important IGH translocations, perhaps through co-localization of TPGL to nuclear transcription ‘factories' outside of CTs. The strong correlation between locus positioning and the clinical frequency of recurrent IGH translocations involving these loci is consistent with the idea that spatial proximity in the nucleus is an important contributor to the high frequency of recurrent translocations. CCND1 and FGFR3 are positioned outside their CT and in close proximity to IGH as compared to TGFBR2 and c-MAF, both of which are more peripheral in the nucleus and position out of their respective CTs at lower frequency. This is consistent with the fact that c-MAF/IGH translocations are relatively infrequent and TGFBR2/IGH translocations have not been reported. Our results suggest that the formation of recurrent IGH translocations in MM is determined not only by spatial proximity of gene loci and radial positioning in the cell nucleus, but also by positioning of loci outside of their chromosomal territories. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.001 | 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 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".