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Molecular Quantitation of Minimal Residual Disease in Multiple Myeloma Patients Achieving Complete Remission after Treatment with Revlimid or Velcade.

2005· article· en· W2557413597 on OpenAlexaff
Kyle J. Thulien, Andrew R. Blech, Tony Reiman, Linda M. Pilarski

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLenalidomideMinimal residual diseaseMultiple myelomaBortezomibThalidomideMedicineProteasome inhibitorCancer researchMolecular biologyOncologyInternal medicineBiologyBone marrow

Abstract

fetched live from OpenAlex

Abstract In multiple myeloma (MM), new therapeutic strategies utilize the proteasome inhibitor bortezomib (Velcade) and the thalidomide immunomodulatory analog lenalidomide (Revlimid). While promising, MM invariably recurs, necessitating a better understanding of the malignant cells that persist during periods of complete remission (CR). In MM, minimal residual disease (MRD) is a valuable prognostic indicator for predicting time to relapse. There are no published studies to quantify the MRD or malignant cells that resist Velcade or Revlimid. In MM, the uniquely rearranged IgH VDJ gene provides a molecular signature. PCR strategies incorporating amplification of genomic DNA using patient specific primers provide a means to quantify MRD in MM patients. To date, the patient cohort tested included three MM patients achieving CR as part of a randomized trial for Revlimid plus dexamethasone, one MM patient with CR in response to dexamethasone (dex) alone, and two MM patients achieving CR after Velcade. All of the CR patients had clonotypic VDJ mRNA transcripts in BM by RT-PCR. Analysis of genomic DNA (gDNA) quantifies the number of malignant cells, as each cell has only one copy of the MM IgH VDJ. Three strategies were employed to quantify the extent of minimal disease during CR to these agents: semi-quantitative PCR analysis of purified gDNA from BM aspirates, quantitative realtime PCR using SYBR Green, and PCR analysis of cells captured from BM aspirate slides (laser pressure catapulting). 1) The semi-quantitative method measures the amount of gDNA template in the PCR reaction required to attain a positive signal, independent of cell type or morphology. 2) The quantitative PCR confirms method 1 by plotting rate of amplification of gDNA for a control sequence as compared to the clonotypic sequence, to calculate the frequency of all clonotypic MM cells in BM. 3) Laser pressure catapulting of BM cells from slide preparations provides a measure that most closely approximates the in vivo situation because it does not introduce potential artifacts arising from purification of cells and DNA that could confound interpretation of the results, and enables morphological identification of the cell types harboring clonotypic IgH VDJ genes. BM aspirate slides were viewed and numerous small patches of cells (8–15 cells) were captured into individual tubes for PCR analysis. Overall, we found that CR patients treated with Revlimid+ Dex have a 100 fold lower frequency of clonotypic MM cells (requiring 1.59e5 cells to detect a positive signal) than did the MM patient in CR from dex (detectable in 1.01e3 cells), indicating that Revlimid substantially reduced, but did not eradicate the malignant clone. Furthermore, for one patient, for whom sequential BM samples were available, the clonal frequency continued to decrease over time. Patients in CR after Velcade treatment have MM cells detectable in 1.32e4 cells. Both therapies exert more depletion as compared to dex alone. Larger patient cohorts are being analyzed to further quantify levels of MRD achieved in response to these agents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.293
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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