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Enregistrement W2461070381 · doi:10.1158/1557-3125.advbc-b110

Abstract B110: Characterization of the role of TRAF2 and TNFRSF14 in breast cancer

2013· article· en· W2461070381 sur OpenAlexaff
Sandrine Tchatchou, Lucine Bosnoyan-Collins, Dushanthi Pinnaduwage, Shelley B. Bull, Irene L. Andrulis

Notice bibliographique

RevueMolecular Cancer Research · 2013
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueNF-κB Signaling Pathways
Établissements canadiensMount Sinai HospitalLunenfeld-Tanenbaum Research Institute
Organismes subventionnairesnon disponible
Mots-clésCancer researchBreast cancerTumor necrosis factor alphaCancerBiologyCarcinogenesisMetastasisOncologyMedicineInternal medicineImmunology

Résumé

récupéré en direct d'OpenAlex

Abstract Human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. Our group recruited a multi-centre prospective cohort of over 1900 women with ANN breast cancer and followed them clinically. Tumors from 135 women in this group were selected for gene expression analysis on human cDNA microarrays to examine the molecular alterations in ANN patients that could be predictive of recurrence. From genes that demonstrated a statistically significant difference in expression in tumors from patients who have experienced an early recurrence versus who have remained disease free for over 10 years, TRAF2 (tumor necrosis factor (TNF) receptor-associated factor 2) was found to be highly expressed in early recurrence. TRAF2 is involved in immune system cytokine signaling pathways and interacts with many receptors in the TNF receptor superfamily and mediates the survival effects of these receptors including NF-κB, LTβR, JNK and MAPKs kinases. TRAF2 has been reported to be overexpressed or constitutively phosphorylated in some cancers, including lymphoma and pancreatic cancers. The tumor necrosis factor receptor TNFRSF14, also called LIGHTR or HVEM is located on the short arm of chromosome 1p36. Deletion of 1p36 is especially frequent in breast tumors and is associated with progression and lymph node metastasis, poor prognosis, higher rate of recurrence, larger tumor size, and DNA aneuploidy7. Cheung and al. (2010) have described somatic TNFRSF14 mutations in Follicular Lymphoma (FL) which are associated with worse prognosis. They identified 46 cases (18.3%) with non-synonymous mutations affecting TNFRSF14 in a cohort of 251 FL patients. The significance of such acquired mutations on the structure-function relationship of TNFRSF14 is still unknown, but it appears that TNFRSF14 can be considered as a potential candidate gene that might contribute to FL development. TNFRSF14 belongs to the TNF-receptor superfamily and contains multiple copies of a cysteine-rich motif in the extracellular region that is known to provide the ligand recognition motifs. Activation of TNF-receptor family members is induced by their cognate, trivalent, TNF-related ligand, clustering multiple receptors, which in turn recruits the cytosolic TNF receptor-associated factors (TRAFs) adaptors leading to serine kinase activation of the NFκB system. TNFRSF14 associated with TRAF2 and other members of the TRAF family and activates JNK as well as NF κB and AP-1, which control expression of multiple immune, inflammatory and acute phase action genes in response to infection or cellular stress. The short cytoplasmic regions are frequently capable of stimulating the transcription factors activator protein 1 (AP1) and NFKB1. This particular region of the TNFRSF14 gene interacts with members of the TNFR-associated factor (TRAF) family and mediates the signal transduction pathways that activate the immune response. Since TNFRSF14 interacts with TRAF2 and/or other TRAFs to mediate the NF-κB activation and TRAF2 is highly expressed in breast cancer early recurrence, we hypothesized that altered TRAF2 and TNFRSF14 could contribute to recurrence in ANN breast cancer. Single-strand conformation polymorphism (SSCP) and DNA Sequencing were performed to detect any small alteration in PCR-amplified product from 130 ANN breast cancer tumor samples and 48 germline breast cancer tumor samples. Known polymorphisms were excluded and direct sequencing revealed one new coding SNP (Pro262Leu; C>T) located at exon 8. The genotypes CC were observed in 177 of the 178 samples in total. Only one ANN breast cancer tumor sample (936A) revealed a heterozygote genotype (CT). According to algorithms ‘SIFT’ and PolyPhen-2, the Pro262Leu amino acid exchange alters the secondary structure of TNFRSF14 and is predicted to affect the function of the protein. Due to the impact of TNFRSF14 mutations associated with poor prognosis during carcinogenesis, this variant may play a role in the therapy outcome in breast cancer. Quantitative Real-time RT-PCR was performed to quantify TRAF2 expression in a subset of cell lines and tumor samples. Current studies include immunohistochemistry of tissue microarrays containing 888 ANN tumors to detect TRAF2 protein levels and localization and investigation of the association of TRAF2 expression with clinical outcome. In addition, the characterization of the importance of alterations in TRAF2 gene and its associated pathways is being performed using a combination of bioinformatics, to identify potential. Furthermore, the TNFRSF14 Pro262Leu_C>T SNP is being analysed using TaqMan allelic discrimination to investigate a putative association of this variant with breast cancer risk or recurrence. These studies could lead to the discovery of new prognostic markers that may improve our understanding of the molecular pathways responsible for breast cancer development and progression and identify novel targets for breast cancer therapeutics. Citation Format: Sandrine Tchatchou, Lucine Bosnoyan-Collins, Dushanthi Pinnaduwage, Shelley B. Bull, Irene L. Andrulis. Characterization of the role of TRAF2 and TNFRSF14 in breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr B110.

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 enseignants0,206
Score d'incertitude au seuil0,567

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 Opus0,015
Tête enseignante GPT0,302
Écart entre enseignants0,286 · 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

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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