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Record W1979822673 · doi:10.1158/1538-7445.am10-3171

Abstract 3171: Expression of PKC iota in breast cancer

2010· article· en· W1979822673 on OpenAlexaff
J. Paget, Manijeh Daneshmand, Md Shahrier Amin, Shahidul Islam, Ian A.J. Lorimer

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsBreast cancerCarcinogenesisCancer researchImmunohistochemistryBreast carcinomaMyoepithelial cellProtein kinase CTissue microarrayPKC alphaCancerPathologyBiologyMedicineSignal transductionMolecular biologyInternal medicineCell biology

Abstract

fetched live from OpenAlex

Abstract One in nine (11%) women is expected to develop breast cancer during their lifetime. Abnormal activation of the PI3K signaling cascade is common in breast cancer. The p110α catalytic subunit of PI3K is mutated in 20-40% of breast cancers. The two most common mutations are E545K in the helical domain and H1047R in the kinase domain; these mutations render PI3K constitutively active. PKC iota is a member of atypical class of PKC family serine/threonine kinases and a downstream effector in the PI3K signaling pathway. PKC iota has been implicated in carcinogenesis and oncogenic signaling in lung, colon and ovarian carcinomas but its role in breast cancer progression is unknown. Using immunohistochemistry (IHC), we have evaluated PKCι expression and localization in breast cancer tissue microarrays (TMA). Weak PKCι staining was detected in normal breast tissue. PKCι was over-expressed in subset of breast cancers with no staining in the surrounding stroma. Positive tumor staining was mainly cytoplasmic with nuclear staining in some cases. There was no significant correlation of positive PKCι staining with tumour type. PKCι overexpression was also seen in a subset of ductal carcinoma in situ samples. In vitro, we have also shown that PKCι is over-expressed and has higher levels of phosphorylation in a subset of breast cancer cell lines when compared to mammary epithelial cell lines. Stable cell lines expressing E545K or H1047R mutations were generated in the mammary myoepithelial cell line MCF-10A by retroviral transduction. Using Western blotting, we have shown that these mutations are sufficient to increase PKCι expression and activation. These results suggest a possible mechanism for the PKCι overexpression previously demonstrated by IHC. Two structurally independent PI3K inhibitors, Wortmannin and LY294-002, inhibited PKCι phosphorylation and activation in mutant PI3K expressing cells, confirming that the PKCι activation is PI3K-dependent. These inhibitors did not inhibit the low level of PKCι activation seen in MCF10A cells expressing wild-type PI3K control, suggesting that this activation occurs by a PI3K-independent mechanism. These results demonstrate that PKCι is overexpressed in some breast cancers, and that PI3KCA mutations may drive this overexpression. These results also indicate a potential role for PKCι in breast carcinogenesis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3171.

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 head0.054
GPT teacher head0.413
Teacher spread0.360 · 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
Published2010
Admission routes1
Has abstractyes

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