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Record W3011145000 · doi:10.1002/ijc.32967

Major multilevel molecular divergence between THP‐1 cells from different biorepositories

2020· article· en· W3011145000 on OpenAlexafffund
Nandita Noronha, Grégory Ehx, Marie‐Christine Meunier, Jean‐Philippe Laverdure, Catherine Thériault, Claude Perreault

Bibliographic record

VenueInternational Journal of Cancer · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersLeukemia and Lymphoma Society of Canada
KeywordsBiologyTHP1 cell lineMyeloid leukemiaCell cultureLoss of heterozygosityMonocytic leukemiaPhenotypeCancer researchLeukemiaMyeloidComputational biologyGeneticsMolecular biologyGeneCell biologyAllele

Abstract

fetched live from OpenAlex

The THP-1 cell line is broadly used as a model for acute myeloid leukemia (AML) with MLL fusion and to study monocyte differentiation and function. We studied THP-1 cells obtained from two major biorepositories. The two cell lines were closely related with a percentage match of short tandem repeat (STR) profiles ranging from 93.75% to 100%, depending on the algorithm used. Nevertheless, we found that the two cell lines presented discordant HLA type, cytogenetic aberrations and AML-related gene expression (including critical targets of MLL fusion). These discrepancies resulted mainly from loss of heterozygosity (LOH) involving five chromosomal regions. In view of their aberrant expression of key "leukemia" genes (e.g., LIN28B, MEIS1 and SPARC), we argue that one of the THP-1 cell lines may not be a reliable model for studying leukemia. Their defective expression of HLA molecules and abnormal adhesion properties is also a caveat for studies of antigen presentation. In a more general perspective, our findings show that seemingly minor discrepancies in STR profiles among cell lines may be the sign of major genetic drift, of sufficient magnitude to affect the reliability of cell line-based research.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.096
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.028
GPT teacher head0.340
Teacher spread0.312 · 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 teacher head, 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

Citations35
Published2020
Admission routes2
Has abstractyes

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