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Abstract LB-89: Germ-line and somatic SMARCA4 mutations characterize small cell carcinoma of the ovary, hypercalcemic type

2014· article· en· W2095422041 on OpenAlexaff
Leora Witkowski, Jian Carrot‐Zhang, Steffen Albrecht, Nancy Hamel, Eva Tomiak, David Grynspan, Emmanouil Saloustros, Catherine Gilpin, Rachel Silva‐Smith, François Plourde, Bárbara Rivera, Ester Castellsagué, Mona K. Wu, Somayyeh Fahiminiya, Javad Nadaf, Avi Saskin, Madeleine Arseneault, Rouzan G. Karabakhtsian, Elizabeth Reilly, Frederick R. Ueland, Anna Margiolaki, Kitty Pavlakis, Sharon M. Castellino, Janez Lamovec, Lawrence M. Roth, Thomas M. Ulbright, Tracey A Bender, Michel Longy, Andrew Berchuck, Marc Tischkowitz, Reiner Siebert, Inga Nagel, Vassilis Georgoulias, Colin J.R. Stewart, Glenn McCluggage, Jocelyne Arseneau, Blaise Clarke, Yasser Riazalhosseini, Martin Hasselblatt, Jacek Majewski, William D. Foulkes

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsUniversity Health NetworkConcordia UniversityMcGill UniversityChildren's Hospital of Eastern OntarioJewish General HospitalUniversity of OttawaMcGill University Health CentreMontreal Children's HospitalMcGill University and Génome Québec Innovation Centre
Fundersnot available
KeywordsSMARCA4BiologyExome sequencingGermlineGermline mutationExomeGeneticsMutationEpigeneticsChromatin remodelingGene

Abstract

fetched live from OpenAlex

Abstract Small-cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is an aggressive tumor and the most common type of undifferentiated ovarian malignancy presenting at less than 40 years of age. Its cause and histogenesis remain unknown. We sequenced the exomes of individuals from three familial cases of SCCOHT. Subsequently, we used whole exome sequencing, Sanger sequencing and immunohistochemistry to analyze germline and tumor DNA from three additional familial cases, 35 non-familial cases and one SCCOHT cell line (BIN-67). DNA sequencing revealed likely deleterious germ-line mutations in the chromatin remodeling gene SMARCA4 in all four familial cases of SCCOHT where DNA was available. This was accompanied by either a somatic mutation or loss of the wild-type allele in the tumor. BIN-67 contained bi-allelic deleterious mutations in SMARCA4. Sequencing of 24 non-familial pathologically-confirmed SCCOHT cases revealed at least one germ-line or somatic likely deleterious SMARCA4 mutation in 22 cases. Immunohistochemical (IHC) analyses of these and an additional 11 tumors showed loss of BRG1 protein in 38/40 cases. Our findings identify alterations in SMARCA4 as a major cause of SCCOHT, which could pave the way for genetic counseling and new treatment approaches. Citation Format: Leora Witkowski, Jian Carrot-Zhang, Steffen Albrecht, Nancy Hamel, Eva Tomiak, David Grynspan, Emmanouil Saloustros, Catherine Gilpin, Rachel Silva-Smith, François Plourde, Barbara Rivera, Ester Castellsagué, Mona Wu, Somayyeh Fahiminiya, Javad Nadaf, Avi Saskin, Madeleine Arseneault, Rouzan G. Karabakhtsian, Elizabeth A. Reilly, Frederick R. Ueland, Anna Margiolaki, Kitty Pavlakis, Sharon M. Castellino, Janez Lamovec, Lawrence M. Roth, Thomas M. Ulbright, Tracey Bender, Michel Longy, Andrew Berchuck, Marc Tischkowitz, Reiner Siebert, Inga Nagel, Vassilis Georgoulias, Colin J.r. Stewart, Glenn McCluggage, Jocelyne Arseneau, Blaise A. Clarke, Yasser Riazalhosseini, Martin Hasselblatt, Jacek Majewski, William D. Foulkes. Germ-line and somatic SMARCA4 mutations characterize small cell carcinoma of the ovary, hypercalcemic type. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-89. doi:10.1158/1538-7445.AM2014-LB-89

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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.057
GPT teacher head0.334
Teacher spread0.277 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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