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Record W1988754465 · doi:10.1186/s12931-014-0160-8

Cell surface marker profiling of human tracheal basal cells reveals distinct subpopulations, identifies MST1/MSP as a mitogenic signal, and identifies new biomarkers for lung squamous cell carcinomas

2014· article· en· W1988754465 on OpenAlexafffund
Emily Van de Laar, Monica Clifford, Stefan Hasenoeder, Bo Ram Kim, Dennis Wang, Sharon Lee, Josh Paterson, Nancy Vu, Thomas K. Waddell, Shaf Keshavjee, Ming‐Sound Tsao, Laurie Ailles, Nadeem Moghal

Bibliographic record

VenueRespiratory Research · 2014
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of WaterlooUniversity of TorontoOntario Institute for Cancer Research
FundersOntario Ministry of Research and InnovationGovernment of OntarioOntario Institute for Cancer Research
KeywordsBiologyProgenitor cellStem cell markerPopulationCell typeStem cellCellCell biologyPathologyCellular differentiationRespiratory epitheliumEpitheliumMedicineGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: The large airways of the lungs (trachea and bronchi) are lined with a pseudostratified mucociliary epithelium, which is maintained by stem cells/progenitors within the basal cell compartment. Alterations in basal cell behavior can contribute to large airway diseases including squamous cell carcinomas (SQCCs). Basal cells have traditionally been thought of as a uniform population defined by basolateral position, cuboidal cell shape, and expression of pan-basal cell lineage markers like KRT5 and TP63. While some evidence suggests that basal cells are not all functionally equivalent, few heterogeneously expressed markers have been identified to purify and study subpopulations. In addition, few signaling pathways have been identified that regulate their cell behavior. The goals of this work were to investigate tracheal basal cell diversity and to identify new signaling pathways that regulate basal cell behavior. METHODS: We used flow cytometry (FACS) to profile cell surface marker expression at a single cell level in primary human tracheal basal cell cultures that maintain stem cell/progenitor activity. FACS results were validated with tissue staining, in silico comparisons with normal basal cell and lung cancer datasets, and an in vitro proliferation assay. RESULTS: We identified 105 surface markers, with 47 markers identifying potential subpopulations. These subpopulations generally fell into more (~ > 13%) or less abundant (~ < 6%) groups. Microarray gene expression profiling supported the heterogeneous expression of these markers in the total population, and immunostaining of large airway tissue suggested that some of these markers are relevant in vivo. 24 markers were enriched in lung SQCCs relative to adenocarcinomas, with four markers having prognostic significance in SQCCs. We also identified 33 signaling receptors, including the MST1R/RON growth factor receptor, whose ligand MST1/MSP was mitogenic for basal cells. CONCLUSION: This work provides the largest description to date of molecular diversity among human large airway basal cells. Furthermore, these markers can be used to further study basal cell function in repair and disease, and may aid in the classification and study of SQCCs.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.378
Teacher spread0.296 · 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.

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

Citations30
Published2014
Admission routes2
Has abstractyes

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