Three-Dimensional Telomere Analysis Using Teloview® Technology Identifies Smouldering Myeloma Patients with High Risk of Progression to Full Stage Multiple Myeloma in a Proof of Concept Cohort
Bibliographic record
Abstract
Multiple Myeloma (MM) remains incurable in spite of the recent development of several advanced therapeutic modalities. Similar to other incurable diseases, the early diagnosis and treatment of MM patients may lead to better prognosis and increased survival rates. Multiple myeloma follows two asymptomatic precursor lesions, monoclonal gammopathy of undetermined significance (MGUS) and smouldering myeloma (SMM) [1]. In current clinical practice patients diagnosed with MGUS or SMM are monitored but not treated. MGUS and SMM may progress to the full stage of multiple myeloma at any time without clinically detectable signals. While 1% of MGUS patients progress to full stage MM every year, 10% of SMM patients progress to full stage MM every year [1]. In this study, we report for the first time that the 3-dimensional telomeres analysis using the TeloView® software platform is able to identify SMM patients with high risk of progression to full stage MM. The prospective study we conducted included a proof of concept cohort of total 21 SMM patients, 16 patients that remained stable for over 5 years, and 5 patients progressed to full stage multiple myeloma within 1 to 3 years from point of diagnosis. The disease progression of high risk SMM patients was confirmed clinically by MM caused morbidity. TeloView® analysis of the 2 SMM patient-groups revealed with high significance (p <0.001) distinct telomeres profiles of the stable patients versus the patients who progressed to full stage MM across 5 independent telomeric parameters measured by TeloView®. The study was conducted blindly on the diagnostic specimens suggesting the ability of TeloView® analysis to stratify SMM patients at point of diagnosis. The results we report have the potential, for the first time, to guide evidence-based decisions to treat SMM patients with high risk of progression, addressing a critical unmet clinical need in the management of MM. Follow up studies including expanded cohorts are needed to validate the results of this study, and to confirm the utility of TeloView® technology to predict the progression of SMM patients on the level of the individual patient. References: Boutros M. et al Genomic Profiling of Smouldering Multiple Myeloma Identifies Patients at a High Risk of Disease Progression. J Clin Oncol. 2020 Jul 20;38(21):2380-2389 Disclosures Louis: Telo Genomics Corp.: Consultancy, Current equity holder in publicly-traded company. Knecht:Telo Genomics Corp.: Consultancy, Current equity holder in publicly-traded company. Mai:Telo Genomics Corp.: Consultancy, Current equity holder in publicly-traded company.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".