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Quantitative Detection Using SYBR Green of Residual Disease in Myeloma Patients Treated with Revlimid or Velcade.

2006· article· en· W2558240189 on OpenAlexaff
Kyle J. Thulien, Tony Reiman, Andrew R. Belch, Johnathan Booth, Linda M. Pilarski

Bibliographic record

VenueBlood · 2006
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMinimal residual diseaseclone (Java method)Multiple myelomaTaqManLenalidomideMelting curve analysisGene rearrangementBiologyMedicinePolymerase chain reactionCancer researchImmunologyGeneLeukemiaGenetics

Abstract

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Abstract The treatment of multiple myeloma (MM) with new drugs like Velcade and Revlimid shows promise in the clinic. These two drugs give excellent partial to complete remissions, but the disease invariably returns indicating escape of the malignant clone. The current clinical practices for quantifying minimal residual disease (MRD), such as plasma cell counts, lack needed sensitivity. PCR based assays amplify the clonotypic IgH VDJ gene rearrangement in myeloma and identify all compartments of the malignant clone, providing a unique molecular signature to monitor disease. Every myeloma cell carries one copy of the specific IgH VDJ rearrangement and provides a quantitative measure of the number of malignant cells remaining in each patient. No previous work has quantified MRD after treatment with either Revlimid or Velcade. TaqMan real-time quantitative PCR (rqPCR) assays are able to quantify the level of disease burden but probes are expensive and difficult to design, making this assay unsuitable for routine clinical use. SYBR green, however, is an inexpensive alternative to probes and utilizes the same unique molecular VDJ signature with consistency and reliability (r2=0.9997). PCR product specificity is confirmed using melting curve analysis. This is the first report of the successful use of SYBR green in quantifying the level of malignant disease in MM. The specific clonal rearrangement is identified for each patient. Patient specific primers are designed and verified as being present in the majority of plasma cells using single cell PCR. A cloned IgH VDJ product for each patient provides a standard curve for each patient-specific rqPCR. A cloned B2Microglobulin PCR product provides an independent standard curve to quantify cell number. After correcting for copy number differences, the percentage of malignant cells is calculated by dividing the number of VDJ molecules by the number of B2M molecules. For all tests, the level of residual disease in bone marrow was measured using 150ng of DNA. In patients achieving complete clinical remission during treatment with Revlimid, the SYBR green method detected 0.104% clonal cells with a range of 0.014%–0.26%. In patients with a partial remission, 3.034% clonal cells were detected, with a range of 0.62%–7.79%. A subsequent bone marrow from one Revlimid treated patient revealed no clonal cells this using SYBR Green method. In patients treated with Velcade at the time of relapse, the remaining clonal cells averaged 1.042% with a range of 0.00075%–3.11%. When Velcade was used as a frontline therapy followed by a stem cell transplant, 0.10% clonal cells remained with a range of 0%–0.287%. In one dexamethasone treated patient who achieved a complete remission, 0.018% clonal cells were found. The SYBR green rqPCR assay for patient specific clonal VDJ was shown to reliably quantify residual disease. To date, our results suggest that frontline treatment with Velcade may lead to lower levels of residual disease than treatment at the time of relapse. In Revlimid treated patients, the extent of residual disease correlates with clinical classifications of complete or partial remission. The significance of these low numbers of malignant cells remains to be established, but the persistent occurrence of relapse suggests they are clinically relevant.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.034
GPT teacher head0.301
Teacher spread0.267 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

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