Abstract PR03: Genome-wide 5-hydroxymethylcytosine profiles in circulating cell-free DNA and survival in patients with multiple myeloma
Bibliographic record
Abstract
Abstract Background: Biomarkers currently used for prognostic stratification or predicting survival in patients with newly diagnosed multiple myeloma (MM) either lack good sensitivity and specificity or require invasive bone marrow biopsies. Aberrant DNA methylation has been associated with poor prognosis and survival in MM. We recently identified a gene panel modified with 5-hydroxymethylcotosine (5hmC), a mark of gene activation, in circulating cell-free DNA (cfDNA) that is associated with relapse or death in patients with diffuse large B-cell lymphoma, another lymphoproliferative disorder. To date, no study has investigated 5hmC in cfDNA for its prognostic significance in MM. Methods: Starting in 2010, we prospectively enrolled patients who were newly diagnosed with MM at The University of Chicago Medical Center. Blood samples were collected at the time of diagnosis. The current report includes data from 184 MM patients. Mortality was ascertained using medical records and the National Death Index. Follow-up was through December 2017, with an average follow-up length of 41.64 months (deceased, n=31; alive, n=153). We profiled genome-wide 5hmC in cfDNA by first using the nano-hmC-Seal technique to construct DNA libraries, which were subjected to next-generation sequencing, mapped to the human genome, and annotated to ~22,000 gene bodies. Cox proportional hazards model and the elastic net regularization, controlling for age, gender, and population, were used to detect 5hmC marker genes associated with overall survival (OS) after diagnosis. Results: For the 184 patients, median age at diagnosis was 61.7 years and 48% (n=88) were males. The differential 5hmC enrichment levels of a preliminary eight-gene marker panel were used to compute a weighted prognostic score (wp-score). In multivariate Cox models, patients with high wp-score had worse OS (Hazard Ratio [HR] = 8.2; 95% Confidence Interval [CI], 2.9-23.4, p < 0.0001), compared with those in the low risk group. Some of the eight 5hmC-midified marker genes have been previously implicated in MM survival. For example, GTF2I (encoding general transcription factor IIi), a known prosurvival gene in MM, showed a single-gene HR of 0.3 (95% CI, 0.1-0.7, p=0.002). The 5hmC-based wp-score outperformed (sensitivity=0.74, specificity=0.84) standard prognostic indices (e.g., albumin, beta-2 microglobulin, and risk classification by cytogenetics) in predicting patients at risk for inferior survival. We are validating the gene panel in an independent cohort of ~150 MM patients. The results will be presented. Conclusions: These findings suggest that 5hmC in cfDNA at the time of diagnosis correlate with OS and outperform standard clinical prognostic indices. Our novel findings, if confirmed, suggest that a plasma-derived cfDNA 5hmC-modified gene panel holds promise as a noninvasive approach for predicting prognosis in MM and may be integrated in clinical practice to improve precision care of MM. This abstract is also being presented as Poster A40. Citation Format: Brian C.-H. Chiu, Zhou Zhang, Jason Karpus, Benjamin Derman, Chang Zeng, Elizabeth Stepniak, Rudy Chiu, John Spinelli, Andrzej Jakubowiak, Chuan He, Wei Zhang. Genome-wide 5-hydroxymethylcytosine profiles in circulating cell-free DNA and survival in patients with multiple myeloma [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr PR03.
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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 | 0.000 | 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".