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Record W4391886344 · doi:10.1093/jcag/gwad061.158

A158 DEVELOPMENT OF MODELS TO SUDY THE INTERACTION BETWEEN CANCER STEM CELLS AND THE MICROENVIRONMENT IN COLON CANCER

2024· article· en· W4391886344 on OpenAlexaffabout
M G Sedeuil, Alexis Gonneaud, Véronique Giroux

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCancerColorectal cancerCancer researchOncologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Colon cancer affects 1 in 15 people and is the 3rd deadliest cancer worldwide. The standard of care consists of surgical resection combined with 5-fluorouracil (5-FU) chemotherapy. However, relapses remain frequent due to a partial or complete loss of sensitivity to treatment, also known as chemoresistance. Over the last decades, studies have revealed the importance of intratumoral heterogeneity in this phenomenon, and in particular of two components: cancer stem cells (CSCs) and the microenvironment. CSCs are cells with a high capacity of self-renewal, potency (ability to give rise to different cell types) and resistance to anti-cancer treatments. The microenvironment, for its part, comprises all the components surrounding tumour cells, such as cancer-associated fibroblasts (CAFs). Although their respective importance in resistance has been well studied, it is important to better understand their respective modulation during resistance as well as their interactions. Aims Identify the specific changes occurring in CSCs and CAFs, as well as their interactions, during the induction of 5-FU resistance in colon cancer. Methods To achieve this goal, we are establishing 5-FU resistant models using organoid lines from colon cancer patients. First, we validated that parental organoids maintain their expected cellular heterogeneity by immunofluorescence. We also confirmed that our parental organoids are sensitive to 5-FU by measuring the survival through a WST1 assay. Results Indeed, we showed the presence of CSCs (ALDH1+) and proliferative cells (Ki67+), among others. With a baseline IC50 of 5µM, we concluded that they can be used to generate a 5-FU resistant line. In addition, our initial findings suggest that the conditioned media of CAF cultures decreases the sensitivity of parental organoids to 5-FU, emphasizing the need to study deeper the interaction between these two tumor components Conclusions In summary, our preliminary results suggest that the interaction between tumor cells and CAFs modulates the response to chemotherapy. We are currently exploring whether CSCs are particularly involved in this phenomenon. In addition, we are developing patient-derived xenograft models (PDX) sensitive or resistant to 5-FU in order to study in vivo the interactions between CAFs and CSCs. At the end, this project will provide a better understanding of the changes required for resistance, paving the way for new targeted therapies Funding Agencies Canada foundation for innovation, Canada Research Chairs

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.261
Teacher spread0.239 · 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 designSimulation or modeling
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 routes2
Has abstractyes

Explore more

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