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Record W4282917982 · doi:10.1158/1538-7445.am2022-1694

Abstract 1694: Cytotoxic conditions alter cell free DNA concentration and fragment size in cancer cells

2022· article· en· W4282917982 on OpenAlexaff
Prisca Bustamante, Thupten Tsering, Julia V. Burnier

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsCytotoxic T cellApoptosisColorectal cancerCancerCancer researchCell cycleProgrammed cell deathBiomarkerLung cancerCancer cellMedicineBiologyMolecular biologyImmunologyPathologyIn vitroInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction: Detection of circulating free DNA (cfDNA) is a promising tool to monitor and predict tumor progression and treatment efficacy. Our group has shown the clinical relevance of cfDNA as a biomarker of tumor development and progression in several cancer models, including colorectal carcinoma and melanoma. cfDNA may stem from a combination of apoptosis, necrosis, and cellular secretions. However, the source and mechanism of cfDNA release in cancer cells are still unclear. Indeed, while some data state that cfDNA is derived from apoptosis, other studies report it is mainly a product of cellular secretions. To better understand cfDNA release and its correlation with tumor biology, this study aimed to assess cfDNA kinetics under cell death, cell cycle arrest, and senescence by using an in vitro cancer model. Methods: Colorectal (HTC116 and HT29), lung (A549), and melanoma (MP41 and OMM2.5) cancer cells underwent cytotoxic conditions by drugs: TRIAL/APO2L, Roscovitine, and valproic acid (VAP), as well as environmental stress by heat and irradiation. Cell death and cell cycle were evaluated by FACS. β-galactosidase staining assessed senescence. cfDNA was extracted from 3 mL supernatant using QIAamp nucleic acid kit and evaluated by digital droplet PCR through hot spot mutations (Mut), and a mitochondrial gene (mt-cfDNA). Isolated cfDNA was visualized by fragment size using Bioanalyzer 2100. Results: Mut and mt-cfDNA increased during cytotoxic conditions in a dose-dependent manner. Cells under apoptosis released greater mut and mt-cfDNA compared to necrotic and untreated cells. Similarly, cell cycle disturbances by VAP were associated with an increase in Mut and mt-cfDNA. Moreover, β-galactosidase positive cells (5D post-irradiation) showed lower Mut and mt-cfDNA levels than control conditions. Electropherogram images showed that cytotoxic conditions alter fragment size distribution. While fragments about 100-200 bp were observed in apoptosis, necrosis showed more abundant fragments about >1000 bp. Conclusions: The release of cfDNA is influenced by cytotoxic and stress conditions. Knowing the biology of cfDNA can help understand its role in cancer development and how best to utilize this marker clinically, especially post cytotoxic agents that induce different cell death mechanisms. These findings have major implications in the interpretation of ctDNA in liquid biopsy as a biomarker of treatment response and tumor progression. Citation Format: Prisca Bustamante, Thupten Tsering, Julia Valdemarin Burnier. Cytotoxic conditions alter cell free DNA concentration and fragment size in cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1694.

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 score0.003
Threshold uncertainty score0.011

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 head0.026
GPT teacher head0.342
Teacher spread0.316 · 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
Published2022
Admission routes1
Has abstractyes

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