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Record W1958260647 · doi:10.1002/hon.2160

PARP1 expression in mantle cell lymphoma: the utility of PARP1 immunohistochemistry and its relationship with markers of DNA damage

2014· article· en· W1958260647 on OpenAlexafffund
Etienne Mahé, Ariz Akhter, Anne Le, Lelsey Street, Payam Pournaziri, Farid Kosari, Meer‐Taher Shabani‐Rad, Douglas A. Stewart, Adnan Mansoor

Bibliographic record

VenueHematological Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
FundersAlberta Cancer Foundation
KeywordsPARP1DNA damageCancer researchBiomarkerImmunohistochemistryPoly ADP ribose polymeraseDNA repairBiologyReal-time polymerase chain reactionMedicineMantle cell lymphomaLymphomaPathologyGeneDNAPolymeraseGenetics

Abstract

fetched live from OpenAlex

Mantle cell lymphoma (MCL) is an aggressive disease with poor overall survival, attributable in part to frequent defects of the DNA repair genes. In such malignancies, additional inhibition of the ubiquitous DNA damage repair protein, poly-ADP ribose polymerase-1 (PARP1) has shown enhanced cytotoxicity (so-called synthetic lethality). We studied PARP1 expression in a series of clinical cases of MCL, with the secondary aim to ascertain the relationship between PARP1 expression and DNA repair gene expression (namely ATM and p53) by immunohistochemical methods. We also examined the relationship between PARP1 expression and the well-established prognostic biomarker Ki-67, in addition to correlating PARP1 expression with the overall survival. From amongst our series of 79 unselected cases of MCL, we detected PARP1 expression in all but two cases with variable intensity. We also noted correlations between PARP1 expression and ATM and p53 expression. As described in previous studies, we identified a significant survival difference on the basis of Ki-67 and p53 expression. When digital H-score analysis of PARP1 expression was performed, there was a distinct survival advantage noted in patients with lower levels of expression. When our biomarker data were assessed by Cox regression, furthermore, the dominant effects of p53 and PARP1 expression were highlighted. Our data support the need for further research into the potential utility of PARP1 as a biomarker in MCL and for the potential direction of future PARP1 inhibitor-targeted therapy studies.

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 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 score0.056
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.323
Teacher spread0.293 · 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 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".

Quick stats

Citations5
Published2014
Admission routes2
Has abstractyes

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