Potentiated Phospho-Protein Network Profiling of Multiple Myeloma Cell Lines and Primary Patient Samples by Multi-Parameter Flow Cytometry.
Bibliographic record
Abstract
Abstract The importance of aberrant signal transduction in the development and progression of cancers including multiple myeloma (MM) is well recognized, although the detailed regulation of signaling networks in relation to oncogenic mutations remains incompletely understood. However, this subject is becoming increasing relevant to clinical oncology due the rapid development of biological-based therapies that can target signaling pathways. Analytical methods that can be applied to clinical samples to measure complex populations of cells and phenotype them for multiple activation states are now feasible due to the recent advances in intracellular signal techniques, flow cytometry and phospho-antibodies. Using multi-parameter flow cytometry, we monitored phospho-protein responses to activators/cytokines and signal transduction inhibitors in a panel of 14 extensively characterized human MM cell lines with heterogeneous molecular abnormalities. A panel of 4-phospho-specific antibodies: anti-pS6, anti-ERK1/2, anti-pAKT and anti-pSTAT3 that represent downstream target genes of signaling pathways known to play central roles in myelomagenesis were used in the initial analysis. Sixteen conditions (basal, inhibitor, activator alone, activator and inhibitor) were studied to generated 64 readouts designed to survey altered signal transduction in the 14 cell lines. We collected data on unstimulated cells and cells stimulated for 7–10 min with IL-6, IGF-1 or FGF or cells inhibited with the signal transduction inhibitors U0126 (MEK), rapamycin (mTOR) or LY294002 (PI3-K). Repeat measurements were collected and the technique and monoclonal antibodies displayed a high level of reproducibly. In contrast, the basal, cytokine and inhibitor responses between cell lines varied considerably reflecting the molecular heterogeneity at the level of signaling responses. The protocols that have been refined and validated in myeloma cell lines are now being applied to primary bone marrow samples from MM patients. Although the same size thus far is small, phospho-protein responses among primary CD138 positive myeloma cells show considerable induction and variance of AKT, MAPK, STAT3 and pS6 phosphorylation. In some MM tumor samples treatment with inhibitors suggest constitutive activation of these signaling pathways while in others the nodes remain activable with phosphorylation above the basal state following stimulation. The data further suggests that MAPK phosphorylation following aFGF stimulation displays significant variance among MM samples and correlates with the detection of t(4;14) translocation by FISH analysis. Additional samples are being assessed and correlation of phospho-protein responses with clinical parameters and cytogenetics will be reported. The data demonstrate that multi-parameter flow cytometry can be applied to myeloma tumor samples to study the phospho-proteome and that considerable heterogeneity exists at the level of signaling responses.
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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".