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Enregistrement W2023617697 · doi:10.1158/1535-7163.targ-11-b25

Abstract B25: Emerging role of heterogeneous ribonucleoproteins (hnRNPs) as early predictive marker and prognosticator for head and neck oral squamous cell carcinoma.

2011· article· en· W2023617697 sur OpenAlexaff
S. C. Tripathi, Manish Kumar, Jasbir Kaur, Shyam S. Chauhan, Nootan Kumar Shukla, Alok Thakkar, Ritu Duggal, Siddhartha Dutta Gupta, Ranju Ralhan, KW Michael Siu

Notice bibliographique

RevueMolecular Cancer Therapeutics · 2011
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueRNA modifications and cancer
Établissements canadiensYork University
Organismes subventionnairesnon disponible
Mots-clésBiomarkerImmunohistochemistryHeterogeneous ribonucleoprotein particleRibonucleoproteinMalignancyBiologyPathologyCancer researchHead and neck squamous-cell carcinomaTissue microarrayCancerMedicineRNAHead and neck cancerBiochemistry

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Recently using iTRAQ-tagging and multidimensional liquid chromatography tandem mass spectrometry (LC-MS/MS), we identified a panel of proteins differentially expressed in head and neck/oral squamous cell carcinoma (HNOSCC) as compared to the non-malignant tissues. Heterogeneous ribonucleoprotein K (hnRNPK) and Heterogeneous ribonucleoprotein D (hnRNPD) are among few of the proteins identified in this panel. These are nuclear protein belonging to the RNA binding protein family. Here, we report the verification of these proteins in an independent set of clinical samples by immunohistochemistry, and investigate their potential as a prognostic biomarker for HNOSCC. The present study also explores their clinical relevance and potential as a biomarker in identification of oral lesions in early stages of malignancy. Experimental Design: Two hundered HNOSCCs, 100 leukoplakias and 100 non-malignant archived tissues were retrieved from the research tissue bank to determine the expression of hnRNPK using immunohistochemistry (IHC). The IHC data were subjected to statistical analyses using the SPSS 15.0 software (Chicago). Receiver operating characteristic (ROC) analysis was used to determine the sensitivity and specificity as a biomarker. The expression in oral lesions was further validated by immunoblotting and RT-PCR analyses in the same tissue and serum samples as used for IHC. Results: hnRNPK and hnRNPD expression was found to be significantly increased from normal mucosa to leukoplakia with or without dysplasia to HNOSCC (ptrend<0.001). Abberant cytoplasmic expression of hnRNPK was also observed in HNOSCCs. ROC curve showed high potential of these proteins as a biomarker for HNOSCC. Cytoplasmic hnRNPK overexpression was significantly associated with dedifferentiation of tumors whereas nuclear hnRNP D was significantly associated with tumor size. In univariate analysis, nuclear as well as cytoplasmic localization of hnRNPK and nuclear hnRNPD were found to be associated with poor survival. There was no correlation between hnRNPK and hnRNPD expression, however, significant reduced disease free survival was obtained for the patients harboring hnRNP D+hnRNP K (p = 0.005; median survival = 11 months) as compared with median disease-free survival of 55 months in the patients showing varied hnRNP D+hnRNP K expression. Cox regression model confirmed that this combination can be a better prognosticator for HNOSCC patients as revealed by multivariate analysis (p=0.013; HR = 2.2, 95% CI = 1.2–4.1). RTPCR and western blotting confirmed our IHC results. hnRNPK was also detected in serum samples of HNOSCC patients. Conclusion: This is the first large scale study that suggests overexpression of hnRNPK and hnRNPD as an early event in development of HNOSCC. Furthermore, their subcellular localization suggests that they may be associated with increased risk of transformation of oral premalignant lesions and recurrence in HNOSCC. As detected in biological fluid, the potential of hnRNPK as a biomarker should be verified on a large scale. The enhanced performance of the combination of hnRNP D and hnRNP K versus either protein individually, in prognosticating the clinical outcome of HNOSCCs needs to be further explored for its implementation in patient care. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B25.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,045
Score d'incertitude au seuil0,831

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,018
Tête enseignante GPT0,259
Écart entre enseignants0,241 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2011
Routes d'admission1
Résumé présentoui

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