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Record W2117125640 · doi:10.1186/1471-2407-10-41

Cellular processes of v-Src transformation revealed by gene profiling of primary cells - Implications for human cancer

2010· article· en· W2117125640 on OpenAlexafffund
Bart M. Maślikowski, Benjamin Néel, Ying Wu, Lizhen Wang, Natalie Rodrigues, Germain Gillet, Pierre‐André Bédard

Bibliographic record

VenueBMC Cancer · 2010
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreMcMaster University
FundersCanadian Institutes of Health ResearchAssociation pour la Recherche sur le Cancer
KeywordsProto-oncogene tyrosine-protein kinase SrcGeneRous sarcoma virusBiologyGene expressionGene expression profilingFusion geneMolecular biologyCancer researchGeneticsKinase

Abstract

fetched live from OpenAlex

BACKGROUND: Cell transformation by the Src tyrosine kinase is characterized by extensive changes in gene expression. In this study, we took advantage of several strains of the Rous sarcoma virus (RSV) to characterize the patterns of v-Src-dependent gene expression in two different primary cell types, namely chicken embryo fibroblasts (CEF) and chicken neuroretinal (CNR) cells. We identified a common set of v-Src regulated genes and assessed if their expression is associated with disease-free survival using several independent human tumor data sets. METHODS: CEF and CNR cells were infected with transforming, non-transforming, and temperature sensitive mutants of RSV to identify the patterns of gene expression in response to v-Src-transformation. Microarray analysis was used to measure changes in gene expression and to define a common set of v-Src regulated genes (CSR genes) in CEF and CNR cells. A clustering enrichment regime using the CSR genes and two independent breast tumor data-sets was used to identify a 42-gene aggressive tumor gene signature. The aggressive gene signature was tested for its prognostic value by conducting survival analyses on six additional tumor data sets. RESULTS: The analysis of CEF and CNR cells revealed that cell transformation by v-Src alters the expression of 6% of the protein coding genes of the genome. A common set of 175 v-Src regulated genes (CSR genes) was regulated in both CEF and CNR cells. Within the CSR gene set, a group of 42 v-Src inducible genes was associated with reduced disease- and metastasis-free survival in several independent patient cohorts with breast or lung cancer. Gene classes represented within this group include DNA replication, cell cycle, the DNA damage and stress responses, and blood vessel morphogenesis. CONCLUSION: By studying the v-Src-dependent changes in gene expression in two types of primary cells, we identified a set of 42 inducible genes associated with poor prognosis in breast and lung cancer. The identification of these genes provides a set of biomarkers of aggressive tumor behavior and a framework for the study of cancer cells characterized by elevated Src kinase activity.

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 score0.011
Threshold uncertainty score0.342

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)0.0000.000

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 head0.041
GPT teacher head0.333
Teacher spread0.292 · 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

Citations17
Published2010
Admission routes2
Has abstractyes

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