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Record W4409629099 · doi:10.1158/1538-7445.am2025-5542

Abstract 5542: A novel approach for establishing clinically relevant models of chemoresistance

2025· article· en· W4409629099 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Research and Treatment
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineCancerComputational biologyIntensive care medicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract This study provides a novel methodology for generating in vitro chemoresistance models that maximize clinical relevance, aimed at improving the translatability of downstream experimental insights to clinical contexts. Our approach prioritizes an accurate translation of clinical chemotherapy treatment regimens to in vitro applications. We present our methodology in this study using canine osteosarcoma (OS), but our approach is designed to broadly apply to other cancer types. Chemoresistance poses a significant challenge to improving cancer treatment outcomes, as the underlying mechanisms driving it are not well understood. One approach to studying these mechanisms is generating in vitro chemoresistance models. However, there has yet to be a consensus on the optimal method for developing clinically relevant chemoresistance models. Many existing guidelines either produce levels of chemoresistance that are not clinically achievable or offer incomplete strategies for producing clinically relevant models. To establish a clinically relevant model of chemoresistance, we treated canine OS cell lines with carboplatin under conditions designed to precisely mimic the standard-of-care (SOC) treatment regimen used in clinical practice. To translate this clinical regimen to our in vitro application, we utilized numerous pharmacokinetic parameters derived from serum concentration curves for carboplatin in dogs treated in accordance with the SOC regimen, including area under the curve (AUC), peak serum concentration (Cmax), time to peak serum concentration (Tmax), and time from treatment initiation to when the serum concentration falls below detectable levels. Utilizing these pharmacokinetic parameters, a biphasic treatment protocol was developed to provide a SOC-equivalent treatment regimen for in vitro application. Before commencing model generation, the baseline chemosensitivity of each parental canine OS cell line was determined in triplicate via its respective half-maximal inhibitory concentration (IC50) of carboplatin. These parental cell lines were then split into two identical plates each, with one plate from each cell line treated periodically with our SOC-equivalent regimen, administered every twenty-one days for six cycles, in accordance with the SOC regimen. Untreated cell lines were passaged alongside their treated counterparts as model controls. Twenty-one days after the final treatment, the IC50s of all treated cell lines and their respective controls will be re-assessed in triplicate to quantify the fold change in chemoresistance induced by our SOC-equivalent regimen. We anticipate that treated cell lines will exhibit appreciable increases in chemoresistance, highlighting the potential of our methodology to establish clinically relevant in vitro models of chemoresistance that support future investigations into the underlying mechanisms of chemoresistance. Citation Format: Jared R. Fischbach, Geoffrey A. Wood, Courtney R. Schott. A novel approach for establishing clinically relevant models of chemoresistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5542.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.313
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.208
GPT teacher head0.491
Teacher spread0.283 · 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