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Abstract A079 Mechanisms of chemotherapy resistance in rhabdomyosarcoma

2024· article· en· W4402266831 on OpenAlexaboutno aff
Sabateeshan Mathavarajah, Yueyang Wang, Yun Wei, Diego Antelo, David M. Langenau

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsRhabdomyosarcomaMedicineChemotherapyResistance (ecology)OncologyInternal medicineCancer researchSarcomaBiologyPathologyEcology

Abstract

fetched live from OpenAlex

Abstract Background: Rhabdomyosarcoma (RMS) is a childhood cancer that originates from soft tissue and shares features with skeletal muscle. RMS patients are treated with a combination of radiation, surgical resection, and chemotherapy (VAC; vincristine, actinomycin D and cyclophosphamide). Unfortunately, 30% of patients eventually develop relapsed tumors due to resistance to VAC or radiation, of whom have an abysmal 17% five-year survival rate. To date, the mechanisms underlying resistance to VAC is poorly understood in RMS tumors, which are desperately needed for devising new therapeutic avenues to target VAC chemoresistance and improve the outcomes for these patients. Methods: We have recently generated long-term VAC-resistant RMS cell lines (from RD and Rh41 parental lines) to model chemoresistance. These cell lines were acclimated to high dose VAC over a 3-month period. Afterwards, single clones were isolated from these chemoresistant cell lines and assessed for upregulation of the PIK3CA/AKT/ABC transporter pathway by Western blot analysis. Results: We find that within the pool of resistant clones, there are two distinct pathways that are upregulated to promote VAC-resistance, one that elevates the PIK3CA/AKT/ABC transport pathway to rapidly efflux drugs from RMS cells. Astonishingly, this same drug resistance pathway is activated in both fusion-positive and fusion-negative RMS. The upregulated ABC transporters are well known drug efflux pumps and include ABCB1/MDR1, ABCC1/MRP1 and ABCG2/BCRP. We next show that the increased transcription of these ABC transporters occurs through an AKT-dependent mechanism – akin to that described by our group for an investigational chemotherapy that combines DNA damaging agent temozolomide with Olaparib PARP-inhibitor (OT). Using an inhibitor of PIK3CA signaling, Alpelisib, we show that we can resensitize these chemoresistant cell lines to VAC and OT. Conclusions: VAC-resistance occurs in part through PIK3CA/AKT signaling to promote drug efflux. The PIK3CA/AKT pathway can be therapeutically targeted to resensitize tumors to VAC. Future studies will focus on determining the mechanisms of drug resistance in tumors that fail to upregulate the PIK3CA/AKT/ABC transport pathway. Citation Format: Sabateeshan Mathavarajah, Yueyang Wang, Yun Wei, Diego Antelo, David M. Langenau. Mechanisms of chemotherapy resistance in rhabdomyosarcoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A079.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

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 integrity0.0000.000
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 head0.074
GPT teacher head0.425
Teacher spread0.351 · 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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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