MétaCan
Menu
Back to cohort
Record W2113244288 · doi:10.1160/th03-05-0261

Expression analysis of the human kallikrein 7 (KLK7) in breast tumors: a new potential biomarker for prognosis of breast carcinoma

2003· article· en· W2113244288 on OpenAlexaff
Maroulio Talieri, Eleftherios P. Diamandis, Dimitrios Gourgiotis, Kostandina Mathioudaki, Andreas Scorilas

Bibliographic record

VenueThrombosis and Haemostasis · 2003
Typearticle
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsKallikreinBreast cancerCarcinogenesisMedicineCancerCancer researchBreast carcinomaBreast diseaseProteasesOncologyInternal medicineBiomarkerCA15-3Mammary glandBiologyGeneticsEnzyme

Abstract

fetched live from OpenAlex

Kallikreins are a subgroup of serine proteases that are involved in the post-translational processing of polypeptide precursors. Growing evidence suggests that many kallikreins are implicated in carcinogenesis. Human kallikrein gene 7 (KLK7; HSCCE) is a new member of the human kallikrein gene family. KLK7 is expressed in normal breast tissue and is up-regulated in breast cancer cells by estrogens and glucocorticoids. In the present study, expression of the KLK7 gene in 92 breast cancer tissues was analyzed by reverse transcription-PCR (RT-PCR) and direct sequencing of several samples. The results were correlated with other clinicopathological variables and patient outcome. KLK7 gene expression was significantly lower in breast cancer patients of low stage (I/II) (p = 0.011) and patients with positive progesterone receptors (p = 0.022). Survival analysis showed that breast cancer patients with KLK7 positive tumors have relatively shorter disease-free survival (DFS) and overall survival (OS) than patients with KLK7 negative tumors. These data suggest that KLK7 gene expression may be used as a marker of unfavorable prognosis for breast cancer patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.312
Teacher spread0.262 · 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.

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".

Quick stats

Citations84
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueThrombosis and HaemostasisSame topicCoagulation, Bradykinin, Polyphosphates, and AngioedemaFrench-language works237,207