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Record W2740705692 · doi:10.1158/1538-7445.am2017-795

Abstract 795: The capacity of high-grade serous ovarian cancer cells to form spontaneous multicellular structures (SMCS) <i>in vitro</i> predicts their <i>in vivo</i> tumorigenicity

2017· article· en· W2740705692 on OpenAlexaff
Alicia A. Goyeneche, Zu‐Hua Gao, Carlos M. Telleria

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsAscitesSerous fluidOvarian cancerMedicineCancerPathologyCancer cellCancer researchInternal medicine

Abstract

fetched live from OpenAlex

Abstract High grade serous ovarian cancer (HGSOC) is the most frequent histopathological subtype among epithelial ovarian cancers (OC). While an increase in concentration of CA125 in the blood anticipates clinical remission following standard of care, we lack biomarker/s to diagnose early disease stage or predict progression speed. In this work we question whether the capacity of HGSOC cells to form Spontaneous Multi-Cellular Structures (SMCS) when incubated under culture conditions that promote, not prevent, adherence to a plastic surface, correlates with their degree of tumorigenicity. We studied 3 HGSOC cell lines developed from the same patient’s ascites: longitudinally along disease progression—established at platinum-sensitive relapse (PEO1); from further progressive disease 10 months (mo.) later (PEO4); and after failure to respond to high-dose cisplatin 3 mo. later (PEO6). We noticed all cell types developed an adherent phenotype and a differential capacity to form SMCS. This capacity was more evident in PEO6 cells having high SMCS forming ability, followed by PEO4 cells denoting some SMCS forming capacity, while PEO1 cells depicted no apparent capability to form SMCS. Next, 2x106 PEO1, PEO4 or PEO6 cells were implanted into the abdominal cavity of nude mice; the animals were sacrificed either after having met an end-of-wellness endpoint criterion, or after a maximum of 14 mo. if no such criteria were met. PEO6-injected mice reached the humane endpoint due to accumulation of ascites 6-7 mo. following injection, and presented discrete yet visible solid tumors in the omentum, pancreatic-spleen region, liver base and diaphragm. Animals injected with PEO4 or PEO1 cells, however, did not develop any apparent disease 14 mo. following injection. Yet, when a 10-fold higher load of PEO4 cells but not PEO1 cells (i.e., 20x106) were injected, animals met euthanasia criteria due to ascites accumulation 6 mo. later and displayed macroscopic disease similar to that caused by 1/10 of the load of their successors (PEO6 cells) within the same timeframe. Furthermore, the anatomical localization and histopathological aspect of the lesions generated with PEO6 cells were similar from that generated with PEO4 cells, suggesting that the more aggressive PEO6 cells were likely present, although in fewer quantities, within the less aggressive PEO4 cell population. Our data demonstrate, then, that the in vitro SMCS forming capacity of HGSOC cells has a positive correlation to their capacity to sicken the animals. Moreover, this study suggests that the in vitro SMCS forming capacity of epithelial OC cells obtained from ascites of patients diagnosed with HGSOC may be used to predict their aggressiveness and, consequently, guide prognosis. Citation Format: Alicia A. Goyeneche, Zu-hua Gao, Carlos M. Telleria. The capacity of high-grade serous ovarian cancer cells to form spontaneous multicellular structures (SMCS) in vitro predicts their in vivo tumorigenicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 795. doi:10.1158/1538-7445.AM2017-795

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 score0.002
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)0.0020.000

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 head0.039
GPT teacher head0.338
Teacher spread0.299 · 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
Published2017
Admission routes1
Has abstractyes

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