Delineating the Secretome of Eleven Breast Cell Lines in the Quest for Novel Breast Cancer Biomarkers.
Bibliographic record
Abstract
Abstract Background: Close to 200,000 new cases of breast cancer are estimated in United States for 2009, rendering breast cancer the most frequently diagnosed cancer in women. Patients diagnosed with early stage breast cancer have significantly improved survival rates compared to late stage patients, underlining the need for identification of biomarkers for early detection. In this study the secretome of 11 breast cell lines was analyzed by tandem mass spectrometry to identify novel breast cancer biomarkers.Materials and Methods: To reflect disease heterogeneity, three cell lines for each breast cancer type (estrogen/ progesterone receptor positive, triple negative, HER2/neu amplified) along with two near-normal cell lines were selected (HCC-1428, BT483, MCF-7, MDA-MB-231, HCC-1143, HCC-38, SK-BR-3, HCC-202, UACC-812). The conditioned media were lyophilized to dryness and the proteins were denaturated, reduced and trypsin digested. The peptides were separated by strong cation chromatography and the resulted fractions were analyzed in a linear ion-trap coupled to an orbitrap mass analyser. All samples were run in duplicate and spectra were searched with Mascot and X!Tandem engines. Scaffold software was used to cross-validate Mascot and X!Tandem results.Results and Discussion: Over 800 unique proteins were identified in the conditioned media of each cell line, resulting in more than 4,000 proteins from the eleven breast cell lines. More than 40% of the proteins were identified with at least 2 unique peptides and the reproducibility between replicates of the same cell line was approximately 70-80%. Using an in-house developed program, we compared the proteomes of all the cell lines to distinguish unique and common proteins and we determined the cellular localization and the biological function for each protein. Then, we focused on extracellular and plasma membrane proteins, which constitute approximately 30% of total proteins, since secreted or shed proteins are more likely to enter the circulation and serve as potential biomarkers. This list of candidates was compared to the existing nipple aspirate fluid proteome to select proteins that have been also detected in breast microenvironment. These proteins were further analyzed based on Unigene database and appropriate literature to select the final list of 10 candidates for validation by immunoassays. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2137.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".