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Record W2980122607 · doi:10.1182/blood.v110.11.770.770

Ex Vivo Graft Purging and Expansion of Autologous Mobilized Peripheral Blood Progenitor Cell (PBPC) Products from Patients with Multiple Myeloma (MM).

2007· article· en· W2980122607 on OpenAlexaboutno aff
Hong Yang, Simon N. Robinson, Yago Nieto, Sergio Giralt, Roy B. Jones, William K. Decker, Dongxia Xing, David Steiner, Richard E. Champlin, Jingjing Ng, Michael W. Thomas, Marcos de Lima, Elizabeth J. Shpall

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsEx vivoProgenitor cellStem cellMedicineCD34TransplantationBortezomibPopulationBone marrowAutologous stem-cell transplantationRituximabHaematopoiesisCancer researchImmunologyMultiple myelomaIn vivoBiologyAntibodyInternal medicineCell biology

Abstract

fetched live from OpenAlex

Abstract Introduction: Autologous PBPC transplantation has become the treatment of choice for selected MM patients. Autografts are often contaminated with MM cells which could be a source of post-transplant relapse. We elected to develop a graft manipulation procedure to purge tumor cells from the autograft without compromising its normal reconstituting activity. Previous studies have shown that bortezomib (Velcade, Millenium Pharmaceuticals, Inc., Cambridge, MA) can kill CD138+ MM cells, with little effect on CD138− B cells. However, the anti-CD20 monoclonal antibody, rituximab (Rituxan, Genentech, Inc., San Francisco, CA) has been shown to kill CD138− B cells, the putative MM “stem cells” population. Therefore we investigated whether an optimized combination of bortezomib and rituximab might effectively eradicate tumor cells from PBPC products. Previous studies1 have also suggested that tumor cells can also be selectively purged by ex vivo culture while expanding the normal hematopoietic progenitors. Thus, we incorporated an ex vivo culture step to optimize MM cell depletion and expansion of the reconstituting normal progenitors. Methods: CD138+ cells were depleted from the thawed PBPC of MM patients using the midiMACS device (Miltenyi Inc, Auburn, CA). The CD138− cells were treated for 24 hrs with 10 or 20 μg/ml rituximab followed by 20nM or 80nM bortezomib for 16hrs. Cells were then washed and ex vivo-expanded using an allogeneic normal marrow donor-derived mesenchymal stem cell (MSC) co-culture technique as previously reported.2 At the end of culture, cells were evaluated for total viable cells, expression of CD138, CD20, CD19, CD34, CD45 by flow cytometry and colony-forming cell (CFC) content in methylcellulose assays (StemCell Technologies, Vancouver, BC). Results: CD138+, CD138−/CD20+ or CD138−/CD20+/CD19+ cells were depleted in the MM PBPC products from patients when treated with bortezomib (20nM) and rituximab (20 μg/ml) followed by ex vivo culture.(Fig 1) Compared with input control, TNC increased by 6–72 fold and absolute numbers of CD34+ cells increased by approximately 3–9 fold. (See representative data Fig 2) Conclusion: Treating CD138-depleted MM PBPC products with bortezomib, rituximab and 2 weeks of ex vivo culture depleted CD138+ malignant plasma cells and CD138− B cells (MM “stem cells”). An estimated >4 log tumor depletion from a mobilized PBPC product was achieved, while the use of ex vivo expansion culture not only preserved but increased the number of normal hematopoietic progenitors. Further refinements of this procedure are in progress and will be tested clinically. Figure Figure Figure Figure

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.239
Teacher spread0.229 · 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 designBench or experimental
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
Published2007
Admission routes1
Has abstractyes

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