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Abstract A64: Mast cell expressed FcεR beta subunit (MS4A2) is prognostic in lung adenocarcinoma

2017· article· en· W2592537573 on OpenAlexaff
Dalam Ly, Chang‐Qi Zhu, Michael Cabanero, Ming‐Sound Tsao, Zhang Li

Bibliographic record

VenueCancer Immunology Research · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsAdenocarcinomaGene signatureLung cancerImmune systemBiologyCancer researchCarcinogenesisMicroarray analysis techniquesGene expression profilingCancerImmunologyMedicineOncologyGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

Abstract Background: The context of immune cell infiltrates within the tumor is associated with cancer prognosis. The type of immune cells and their activation state can provide mediators that either promote or inhibit tumor growth. A growing body of evidence suggest the presence of innate immune cells play a role in shaping early tumor growth. In attempts to gain insight into the immune networks that regulate tumorigenesis, we used genome wide expression datasets of patients with resected early stage non-small cell lung cancer (NSCLC) to identify immune-related genes associated with patient survival. Methods: Gene expression analysis was conducted on microarray datasets from 128 early-stage NSCLC adenocarcinoma resected tumor samples. Limiting analysis to immune-related genes, we identified a minimum gene set that is prognostic for lung adenocarcinoma and validated the gene signature in additional published microarray NSCLC datasets. Using pathway analysis and immunohistochemistry (IHC), we identified a role for mast cell-expressed IgE receptor beta subunit, MS4A2, in lung adenocarcinoma progression. Results: From an immune-related gene list, we identified a minimal gene signature that was able to separate patients into high or low-risk survival groups. This gene signature was shown to be prognostic for NSCLC adenocarcinoma in nine validation datasets (n=1264, hazard ratio 2.07, 95% confidence interval 1.69-2.53, p<0.0001). Pathway analysis of differentially expressed genes within high or low-risk survival subgroups reveals gene ontologies and immune signatures that are enriched for IgE receptor signaling and mast cells in patients with favourable prognosis. Univariate analysis shows that the IgE receptor complex genes, as well as mast cell specific protease, mast cell carboxypeptidase A, are highly prognostic for survival. We are currently using IHC of matched patient samples to validate receptor localization. Conclusion: By limiting gene expression analysis to immune-related genes, we identified a minimal gene set that indicate an important role for IgE receptor signaling and mast cells in favourable lung cancer prognosis. Our data highlights the importance of innate immune cells in shaping lung cancer development. Citation Format: Dalam Ly, Chang-Qi Zhu, Michael Cabanero, Ming-Sound Tsao, Li Zhang. Mast cell expressed FcεR beta subunit (MS4A2) is prognostic in lung adenocarcinoma. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr A64.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.340
Teacher spread0.281 · 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 designObservational
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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