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Abstract MIP-059: MITOCHONDRIAL DYNAMICS AND DYSFUNCTION IN OVARIAN CANCER

2017· article· en· W2622153623 on OpenAlexaboutno aff
Dong‐Hui Shin, Usawadee Dier, Patrick Timmins, Joshua P. Kesterson, Rébécca Phaëton, Nadine Hempel

Bibliographic record

VenueClinical Cancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsMitochondrial fissionmitochondrial fusionBiologyCancer researchOvarian cancerMitochondrionDNM1LCancerProgrammed cell deathApoptosisCell biologyMitochondrial DNAGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Altered mitochondrial function remains a key feature of many tumor cells and drives pathways such gene expression, metabolic and stress responses, cell cycle progression and resistance to apoptosis. Many chemotherapeutics activate programmed cell death and it is thought that mitochondrial dysfunction may be one mechanism by which cancer cells evade killing by these compounds. Screening the metabolic profiles of ovarian cancer cell lines and patient ascites-derived tumor cells reveals that ovarian cancers fall into unique bioenergetic subgroups. For example, Ovarian Clear Cell Carcinomas (OCCC) display high oxygen consumption rate and glycolytic flux compared to the more common high grade serous adenocarcinoma (HGSA) subtype. In addition, we show that a portion of HGSAs have severe mitochondrial dysfunction, that is marked by a decrease in mitochondrial respiration, a lack of response to the uncoupler FCCP and a concomitant reliance on alternate metabolic pathways. Moreover, this is accompanied by enhanced chemoresistance to Cisplatin and Taxol. The cause of mitochondrial dysfunction has been attributed to a number of factors, including deregulation in mitochondrial fission/fusion dynamics. Moreover, fission is an integral component of apoptotic and authophagy pathways. Interestingly, the observed HGSA mitochondrial dysfunction correlates with aberrant fusion/fission dynamics and expression of a low molecular weight variant of the mitochondrial fission protein Drp1. The potential significance of Drp1 in ovarian cancer etiology is highlighted by TCGA data, where more than 15% of HGSA samples display significant increases in Drp1 mRNA levels, and associated amplification of the Drp1 gene DNM1L. Whether this represents the shorter, potentially dominant-negative Drp1 variant identified in our work is currently under active investigation. Our data suggest that compromised mitochondrial function and fission/fusion dynamics may be a hallmark of a previously unidentified subgroup of highly chemoresistant EOCs and that this is associated with aberrant expression of the fission protein Drp1. Studies are underway to identify the molecular identity and regulation of short Drp1, and the mechanistic links to alterations in fission, metabolic switching and chemoresistance. Citation Format: Dong-Hui Shin, Usawadee Dier, Patrick F. Timmins, Joshua Kesterson, Rebecca Phaeton and Nadine Hempel. MITOCHONDRIAL DYNAMICS AND DYSFUNCTION IN OVARIAN CANCER [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr MIP-059.

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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.127
GPT teacher head0.476
Teacher spread0.349 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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