Molecular differences in triple negative breast cancer between race/ethnicities.
Notice bibliographique
Résumé
Abstract Abstract #2089 Background: A disparity in prognosis of triple negative (TN) breast cancer (BC) has been observed between African American (AA) and Caucasian (CAU) race/ethnicities afflicted with this aggressive and invasive BC subtype. Etiological understanding of these differences involves accounting for several factors associated with phenotype and genotype. Here, we address the latter using the Illumina DASL (cDNA mediated, Annealing, Selection, Extension, and Ligation) assay to quantify mRNA expression of 512 breast cancer related genes in a cohort of 24 CAU and 56 AA TN BC tissues sourced from formalin-fixed, paraffin-embedded (FFPE) blocks. Material and Methods: The DASL assay was used to measure mRNA expression levels from FFPE sourced tissues in both cohorts of self-identified patients. CAU BC patients were obtained from St. Mary's Hospital, Montreal, Quebec and AA BC patients were obtained from Grady Hospital, Atlanta, Georgia. RNA extraction used the RNA High Pure Kit (Roche) and was taken from archival FFPE tissues either 5µm tissue sections or cores. Differential mRNA regulation was identified by Significance Analysis of Microarrays (SAM) software using a false discover rate (FDR) less than 1% and a two fold-change criteria to determine differential regulation. Results: In all, 33 genes were found differentially expressed between AA and CAU TN BC tumor samples, 32 of which were upregulated in the AA cohort, only 1 of which was upregulated in the CAU group. The upregulated gene in CAU TN BC was TFF1. Upregulated genes in the AA cohort (order of statistical significance according to SAM software) were KIF20A, EP300, AURKB, FGF4, C14orf155, USP22, EPOR, ZNF668, SCNN1G, MAPT, FLNB, EP400, LTA, ACOT11, RBP3, CSF3, E2F2, TGFB1, CCNE1, L1CAM, NDP, VWF, RHOB, FEN1, BIN1, KRT17, CDC42EP4, SERPINF1, CHI3L2, NES, BCL2, and RERG. Discussion: TFF1 upregulated in the CAU population, has been indicated as biomarker of favorable prognosis in endocrine therapy in clinical studies which is consistent with race/ethnicity disparities. The remaining genes upregulated in the AA cohort include transcription factors E2F2 and RBP3/E2F1 both with cyclin binding domains which may interact with CCNE1, extracellular and adhesion related genes KRT17, L1CAM and FGF4, genes associated with cell cycle AURKB, EP400, and EP300 (activator of HIF-1A). Several RAS related genes were also found differentially expressed in the AA cohort including RHOB, RERG, BIN1, and EPOR. Moreover, it is worth mentioning that BCL2 which is expressed in the aggressive mammary cancer cell line MCF-7 was also found upregulated in the AA cohort. These initial findings suggest that several differentially regulated genes between AA and CAU race/ethnicities may account for the disparity in outcomes resultant in these populations. These initial data warrant further investigation which is currently ongoing. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 2089.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».