Bcl2-interacting killer CpG methylation in multiple myeloma: a potential predictor of relapsed/refractory disease with therapeutic implications
Bibliographic record
Abstract
BIK (bcl2-interacting killer) is the founding member of the BH3-only bcl-2 family of pro-apoptotic proteins, which is suppressed in various cancers. In multiple myeloma (MM), BIK has been shown to be epigenetically silenced in vitro, but there is a lack of clinical data. We investigated the CpG methylation status of the BIK promoter in a well-characterized clinical series of patients with MM and investigated its clinical relevance. Forty patients with MM (21 male, 19 female; mean age 66) were studied. According to the International Staging System (ISS) they were classified as 16 patients with stage I, 12 patients with stage II and 12 patients with stage III disease. Methylation in the BIK CpG island was assessed by methylation-specific polymerase chain reaction (MSP) assay. Logistic regression analysis was used to investigate associations between gene methylation and age, ISS stage, performance status, extramedullary disease, bone disease, anemia (hemoglobin ≤10 mg/dL), serum albumin, β(2)-microglobulin level and relapsed/refractory disease. Methylation in the BIK CpG island was detected in 16 patients (40%), with a trend favoring male gender (odds ratio [OR] = 3.08, p = 0.09) and development of bone disease and extramedullary disease (OR = 1.6, p = 0.35 and OR = 3, p = 0.14, respectively). Patients with MM with methylated BIK CpG island had a statistically significant risk for disease evolution to relapsed/refractory disease (OR = 5.4, p = 0.03). This study provides clinical evidence that methylation-induced transcriptional silencing of the BIK pro-apoptotic gene may occur in MM, which might serve as a predictor of the development of relapsed/refractory MM. These findings warrant validation in larger cohorts of patients and suggest therapeutic utility for agents that enhance BIK expression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".