Abstract 3842: Identification of distinct apoptosis and myeloid signaling profiles within acute myeloid leukemia (AML) blast subpopulations
Bibliographic record
Abstract
Abstract Background: AML is a disease with significant molecular and clinical heterogeneity and dismal prospects for disease-free survival. We hypothesize that it is likely that this heterogeneity is reducible to a limited number of functional intracellular signaling phenotypes that can classify the disease into biological, and clinical subgroups that could guide treatment regimens. The current study was undertaken to define the diversity of modulated intracellular signaling responses in AML patient samples. Objectives: Single network profiling (SCNP) using multiparameter flow cytometry was used to characterize intracellular pathway responses to treatment with myeloid cytokines and growth factors in addition to apoptosis-inducing agents in individual AML patients. Identification of unique signaling profiles in sub-groups may inform the choice of specific therapeutic regimens. Methods: The responses of JAK/STAT, PI3K/S6 and apoptosis signaling pathways were measured after in vitro exposure of 34 diagnostic non-M3 AML samples to a panel of myeloid growth factors (e.g Flt3L, SCF), cytokines (e.g G-CSF, GM-CSF) interleukins (e.g IL-6, IL-27) and apoptosis-inducing agents (etoposide, staurosporine). Samples processed for cytometry were incubated with cocktails of fluorochrome-conjugated antibody against cell surface proteins to delineate cell subsets and against intracellular signaling molecules. Results: Analysis of JAK/STAT and PI3K/S6 pathways in individual patient samples identified blast subgroups with distinct pathway profiles: A) high JAK/STAT activity B) high PI3K/S6 activity C) high activity in both pathways D) low activity in both pathways. In vitro exposure of samples to staurosporine and etoposide revealed three distinct “apoptosis” profiles: 1) responsive to both agents 2) refractory to both agents 3) refractory to etoposide, but responsive to staurosporine. Further, the pattern of elevated SCF, Flt3L and SDF1alpha-induced PI3K/S6 pathway activity and elevated IL-27 and G-CSF-induced JAK/STAT pathway activity was associated with in vitro refractoriness to apoptosis inducing agents. Analysis of JAK/STAT, PI3K/S6 and apoptosis pathway activities characterized biologically distinct patient-specific signatures, even within cytogenetically and phenotypically uniform patient subgroups. Strikingly, individual patient samples would “present” as composed of, a priori, cell subsets with unique signaling and apoptosis responses. Conclusions: SCNP revealed cell subsets with distinct signaling responses between AML samples and within AML samples. This information could be used for selecting a therapeutic agent, understanding mechanisms of resistance, allowing accurate monitoring of AML disease over time as well as guiding the choice of a targeted agent to be used alone or in combination with chemotherapy to improve patient response rates. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3842.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".