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Record W2567545195 · doi:10.1158/1538-7445.am2015-484

Abstract 484: Fidelity of subclonal representation in human neuroblastoma-derived cell line and patient-derived xenograft models: A report from the NCI-TARGET project

2015· article· en· W2567545195 on OpenAlexaff
Maya Schonbach, Arnavaz Danesh, Jeff Bruce, Tito Woodburn, Tanja M. Davidsen, Leandro C. Hermida, Patee Gesuwan, Jaime Guidry Auvil, Oliver Hampton, David A. Wheeler, Julie M. Gastier‐Foster, Malcolm A. Smith, Daniela S. Gerhard, John M. Maris, Patrick Reynolds, Trevor J. Pugh

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsCancer researchNeuroblastomaExome sequencingBone marrowCell cultureProgenitor cellBiologyCancerSomatic cellGeneticsStem cellMutationImmunologyGene

Abstract

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Abstract Patient-derived xenografts and cell lines have been the underpinning of functional characterization and drug discovery efforts in cancer. The use of these models is often under the assumption that these systems are renewable, faithful representations of original progenitor tumor cell populations. To test this assumption, we performed whole exome (92X median coverage) and genome sequencing (36X median coverage) analysis of cell line and patient-derived mouse xenografts (PDXs) originating from 7 neuroblastoma patients. Data are from1 primary tumor, 3 PDXs, and 15 neuroblastoma cell lines cultured from tumor, bone marrow, or blood. The cell lines consisted of 4 pre-/post-therapy pairs and 3 pairs established and maintained in either hyperoxia (room air i.e. “standard” cell culture) or physiologic (bone marrow hypoxia = 5%) oxygen. 7 lymphoblastoid or fibroblast cell lines were used as matched normals to identify somatic mutations. Subclonal population structures were inferred from somatic mutation calls calibrated for copy number state and tumor purity. In all cell lines and xenografts, we observed 1-2 additional subclonal populations, primarily supported by deep coverage from exome sequencing. In nearly every case, we observed shifts in the proportional representation of genetic subclones and many subclones showed additional mutations not evident in the progenitor tissue or cancer line derived in parallel. Comparison of three cell line pairs established in bone marrow level hypoxia versus room air found only ∼40% of coding mutations in each line were shared (average 82 mutations per line), suggesting significant genetic impact of growing tumor cells in the two different culture conditions. Matched PDXs from these cases had only ∼17% of coding mutations shared across all three models. The greatest genetic similarity was seen between paired cell lines established from tissue obtained pre-/post-therapy from the same patient (36 coding mutations shared, 14 private to diagnosis and 13 private to progression). However, a second pre/post-therapy cell line pair did not share any coding mutations, although they did have 585 non-coding mutations in common (of 4,033 and 2,480 in each line), assuring that the relapse was derived from a diagnostic tumor clone. These results highlight a need for comprehensive subclonal analysis of human cancer laboratory models to better inform design and interpretation of biological and preclinical therapeutic studies. Citation Format: Maya Schonbach, Arnavaz Danesh, Jeff Bruce, Tito Woodburn, Tanja Davidsen, Leandro Hermida, Patee Gesuwan, Jaime Guidry Auvil, Oliver Hampton, David Wheeler, Julie Gastier-Foster, Malcolm Smith, Daniela Gerhard, John M. Maris, Patrick Reynolds, Trevor J. Pugh. Fidelity of subclonal representation in human neuroblastoma-derived cell line and patient-derived xenograft models: A report from the NCI-TARGET project. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 484. doi:10.1158/1538-7445.AM2015-484

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)0.002
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.186
GPT teacher head0.430
Teacher spread0.245 · 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
Published2015
Admission routes1
Has abstractyes

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