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Record W2040663090 · doi:10.1158/1940-6207.prev-11-a11

Abstract A11: Loss of LKB1 is an early event in high-grade serous carcinoma

2011· article· en· W2040663090 on OpenAlexaff
Sophia George, Anca Milea, Mona L. Gauthier, Patricia A. Shaw

Bibliographic record

VenueCancer Prevention Research · 2011
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsOntario Institute for Cancer ResearchUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsSerous fluidSerous carcinomaOvarian cancerCancer researchCarcinogenesisCancerFallopian tubeBiologyMedicinePathologyOncologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: LKB1 is a ubiquitously expressed serine/threonine protein kinase recently ranked sixteenth on the list of top cancer genes. Inactivating germ-line mutations in LKB1 gene on chromosome 19p13.3 found in 60–70% of patients with Peutz-Jeghers syndrome (PJS), leading to increased risk of developing cancers of epithelial origin. Loss of LKB1 protein with underlying LKB1 gene methylation previously found in high-grade breast carcinoma – low expression associated with shorter relapse-free survival. Heterozygous mutations of LKB1 and p53 genes cooperate in the acceleration of tumorigenesis in mice. High-grade serous ovarian cancer (HGSC) is rarely diagnosed at an early and potentially curable stage, effective early detection and preventative strategies are few. In a previously published microarray study, we observed that LKB1 mRNA was significantly lower in Fallopian tube cancers and HGSC. Recently the discovery of occult invasive and intraepithelial tubal carcinomas in BRCA1 mutation carriers, who are at high risk of serous cancer, undergoing prophylactic surgery has focused attention on the fallopian tube epithelium as the cell of origin and has led to the reporting of putative serous cancer precursor lesions. We therefore, sought to determine the expression of LKB1 in different histological subtypes of ovarian cancer and in early lesions; and the effect of loss of LKB1 on fallopian tube epithelial cells in vitro. Methodology: Archived sections of ovarian tumors were reviewed, paraffin blocks selected, and tissue microarrays created using triplicate 0.6 mm cores. The major histological types included were: high grade serous (n=201), non-serous (n=87), and low grade (micropapillary) (n=12) carcinomas, serous tumors of low malignant potential (n=26) and STICS (n=15). Immunohistochemistry for LKB1 protein (Santa Cruz mouse mAb sc-32245) was performed using standard techniques. Percentage of tumor cells with positive cytoplasmic staining (0–3), staining intensity (0–3) and histoscores were determined by viewing digitalized images with Aperio ImageScope software. A combined score of > 4 was considered positive. Fishers exact test with 95% confidence intervals was used to determine the significance of results. Fallopian tube epithelial cells were established from freshly digested tissue and infected with shRNA targeting LKB1. In vitro assays to determine proliferation and malignant transformation were used. Results: Loss of cytoplasmic LKB1 protein expression is more frequently observed in sporadic and hereditary high-grade serous carcinomas compared to other histological types, including low-grade serous carcinoma and serous tumors of low malignant potential. LKB1 may be exclusively involved in the high-grade serous oncogenic pathway and not in the development of low-grade serous carcinoma. Loss of LKB1 in early lesions was observed in 15/15 cases and indicates a role for in sporadic HGSC tumorigenesis in corporation with previously identified oncogenes. The frequency of LKB1 loss in high-grade tumors (67–69%) is similar to frequency of p53 mutations previously observed (70%). Citation Information: Cancer Prev Res 2011;4(10 Suppl):A11.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.185
GPT teacher head0.429
Teacher spread0.244 · 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 teacher head, not a consensus.

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
Published2011
Admission routes1
Has abstractyes

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