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Abstract PO5-25-02: Microenvironment based co-culture dependence of breast cancer and immune cell interactions on functional outcomes

2024· article· en· W4396587289 on OpenAlexaff
Karen Norek, Jacob Kennard, Kenneth F. Fuh, Robert K. Shepherd, Kristina D. Rinker, Olesya A. Kharenko

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsImmune systemBreast cancerTumor microenvironmentCancerMedicineCancer researchOncologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract The tumour microenvironment (TME) includes physical forces from interstitial fluid flow and cell-cell interactions that modulate cancer development and progression through activation of multiple oncogenic pathways leading to tumor growth and metastatic spreading. We previously reported on the role of physical forces on epithelial to mesenchymal transition (EMT) and S100 gene family expression and cell to cell adhesion properties with implications to normal breast development and cancer. Signals from the tumor exit the local tumor environment through interstitial fluid transport and cell migration where they can be found in the blood stream. We developed a whole blood RNA gene expression biomarker panel coupled with proprietary software capable of identifying the presence of an active breast cancer signature at early stages of disease with clinical study results previously reported. Here we report on results from transcriptomic and function studies with cell interaction models. Cancer cells can influence immune cells through direct contact or via secreted molecules causing the immune cells to undergo functional changes. To investigate mechanisms involved in the induction of these alterations in a model system, we performed co-culture studies with human monocytic cells and breast cancer cells. Interaction of human monocytic cells with the breast cancer cells caused significant changes in both behavior and transcriptomes. Moreover, using RNAseq and pathway analysis we demonstrated that the changes induced through the exposure to the more aggressive triple negative (TNBC) phenotype were distinct from the alterations triggered upon contact with an ER+ breast cancer cell line. We also show that cancer-immune crosstalk triggers EMT as well as activation of multiple oncogenic pathways associated with cell migration and invasion, cell chemotaxis and cell-to-cell interactions. As the interplay between cancer and immune cells plays an important role in cancer progression, these findings provide important insight into key mechanisms controlling these outcomes. Citation Format: Karen Norek, Jacob Kennard, Kenneth Fuh, Robert Shepherd, Kristina Rinker, Olesya Kharenko. Microenvironment based co-culture dependence of breast cancer and immune cell interactions on functional outcomes [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-25-02.

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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.058
GPT teacher head0.397
Teacher spread0.339 · 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
Published2024
Admission routes1
Has abstractyes

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