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Record W2566328755 · doi:10.1158/1538-7445.am2015-3193

Abstract 3193: Expression analysis reveals candidate genes involved in highly invasive high-hyaluronan binding subpopulations of prostate cancer cell lines

2015· article· en· W2566328755 on OpenAlexaff
Sean J. Leith, Ann F. Chambers, James B. McCarthy, Joseph L. Chin, Eva A. Turley

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFibroblast Growth Factor Research
Canadian institutionsWestern University
Fundersnot available
KeywordsBiologyCancer researchMetastasisCell sortingProstate cancerCell cultureFlow cytometryAngiogenesisCancerMolecular biologyCell growthGenetics

Abstract

fetched live from OpenAlex

Abstract Tumour heterogeneity is one of the hallmarks of aggressive cancers, which can be detected by differential gene expression, DNA mutation patterns, and ligand binding profiles. Hyaluronan (HA) is an extracellular matrix polysaccharide whose elevated accumulation is associated with tumour recurrence in colon and breast carcinomas. Previously, we reported that triple-negative breast cancer cell lines exhibit heterogeneous binding of HA, with high and low binding subpopulations showing differences in proliferation and invasion. Here we assessed whether or not a similar binding heterogeneity detects prostate cancer cell subsets with differential invasive capability. Flow cytometry HA-binding profiles reveal heterogeneous binding of a fluorescent HA probe to the PC3M-LN4 prostate cancer cell line. Fluorescence-activated cell sorting (FACS) was used to isolate low and high hyaluronan binding subpopulations. Sorted cells were cultured and, after one week of growth, were analyzed for cell proliferation and invasion using alamar blue, transwell invasion and gelatin degradation assays. Results confirmed that HAhigh tumor cells displayed reduced growth but increased invasion and degradation relative to HAlow subpopulations. We then employed human gene 2.0 expression arrays to assess transcriptome changes between these two subpopulations. The expression of 7 genes was significantly elevated or lowered in HAhigh vs. HAlow cells, and these were linked to inflammation, angiogenesis, MMP9 regulation and metastasis. These results identify a novel form of heterogeneity common to both breast and prostate cancer cell lines and suggest that subpopulations binding high levels of HA can be used as indicators of aggressive tumors. Citation Format: Sean J. Leith, Ann F. Chambers, James B. McCarthy, Joseph L. Chin, Eva A. Turley. Expression analysis reveals candidate genes involved in highly invasive high-hyaluronan binding subpopulations of prostate cancer cell lines. [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 3193. doi:10.1158/1538-7445.AM2015-3193

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)0.001
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 score0.173
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.071
GPT teacher head0.382
Teacher spread0.311 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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