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Record W1525973260

Differential proteomics of metastatic and non-metastatic lung carcinoma cell lines

2006· article· en· W1525973260 on OpenAlexaff
Cecile Paboeuf, Hongtao Qi, Cristina Draghici, Yasuo Konishi, Robert Ménard, Edmund Ziomek

Bibliographic record

VenueCancer Research · 2006
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAlexa FluorChemistryMolecular biologyFluorescenceCell cultureCytosolTrypan bluePolyacrylamide gel electrophoresisBiochemistryCellBiology
DOInot available

Abstract

fetched live from OpenAlex

4548 Two lung carcinoma cell lines, CL1-0 and CL1-5 [Chu, Y. W. et al. Am. J. Respir.Cell. Mol. Biol., 17: 353-360, 1997] are different in their invasive and metastatic potential. Both cell lines form tumors when injected to mice, but only CL1-5 cells lead to tumors capable of metastasizing to lungs. For the purpose of this work we used subcellular fractions obtained from CL1-0 and CL1-5 cells. Proteins in the cytosol were labeled with two different fluorescent dyes. We chose Alexa Fluor 555 and Alexa Fluor 647 C 2 maleimide derivatives (Invitrogen) for their stability, similar molecular weight and affordability. The cytosol proteins were labeled with the excess of the dye - each sample with a different dye. Equal amounts of labeled CL1-0 and CL1-5 cytosols were mixed and proteins resolved by 2D-gel electrophoresis. The 2D-gels were scanned (Typhoon, GE Healthcare) and protein spots belonging to either CL1-0, or to CL1-5 were identified. In addition to the fluorescence overlay image, proteins were visualized by silver staining, extracted from the gel and subjected to in-gel tryptic digestion and LC-MS/MS analysis. To verify reproducibility of labeling and separation by 2-D PAGE we inversed the labeling and repeated the proteomic analysis. Due to a higher molecular weight of Alexa Fluor 647 C 2 maleimide (approx.50 Da), saturation labeling of low-molecular-weight proteins resulted in a small, but easy to recognize shift of the spots on the overlay image. Importantly, isoelectric point was the same for proteins labeled either with Alexa Fluor 555, or Alexa Fluor 647. In both experiments we observed the same unique spots. Unique protein spots were observed mainly in CL1-0 and absent, or decreased in CL1-5 cytosol samples, i.e., down-regulated in more metastatic carcinoma cell line. Among the proteins down-regulated in CL1-5 cells were annexin I (ANX1), heat shock protein 27 (HSP 27) and down-regulated ovarian cancer 1 (DOC1), all three already established cancer markers. Somewhat unexpected was identification of the biliverdin IX beta reductase (AAB29537), a protein shown to have an antiapoptotic activity. Western blot analysis confirmed a high level of HSP27 and ANX1 in cytosols from CL1-0 cells, and a much lower signal for these proteins was observed in CL1-5 cells. In overall, we have demonstrated that Alexa Fluor dyes can be used successfully in the differential gel electrophoresis and subsequent proteomic identification of the cancer protein markers.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.035
GPT teacher head0.370
Teacher spread0.335 · 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 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
Published2006
Admission routes1
Has abstractyes

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