Abstract 1168: Integrated genomic, microRNA (miRNA) and proteomic profiling by stable isotope labeling with amino acids in cell culture (SILAC) of ovarian carcinoma for biomarker discovery
Notice bibliographique
Résumé
Abstract Ovarian cancer (OCa) is the fifth leading cause of cancer-related deaths in North American women, and the first for gynecologic malignancies. The long-term effectiveness of standard therapy is poor. Thus, there is a need for developing markers for diagnosis, prognosis, and for predicting therapeutic response. Transformation, malignancy and therapy resistance are consequences of changes at the DNA, RNA and protein levels, requiring an integrative approach for biomarker discovery. We, and others, have previously demonstrated that elevated protein levels of Kallikrein 6 (KLK6) in OCa are clinically relevant; and that copy-number gains of the KLK locus (19q13.3/13.4) is associated with elevated levels of KLKs, increasing grade and genomic instability. Recent work has indicated KLK6 protein expression is also regulated by microRNAs (miRNAs). Our profiling of OCa cell lines and primary tumours showed the differential expression of miRNAs, consistent with other published studies. Moreover, miRNAs predicted to target KLK6 were shown to be decreased in a KLK6-overexpressing OCa cell line (OVCAR-3), in comparison to a KLK6-non-expressing cell line (TOV21G) or to miRNAs derived from normal ovarian tissue. Among these are members of the hsa-let-7 family of miRNAs, found also to be in regions of copy-number loss in OVCAR-3. Since miRNAs can affect the protein expression of many genes, the identification of differentially expressed proteins, in addition to KLK6 not only suggests putative biomarkers, but may help elucidate pathways for therapeutic interventions. To identify differentially expressed proteins upon the transient transfection of hsa-let-7 family members into the OVCAR-3 cell line, we utilized Stable Isotope Labelling with Amino Acids in Cell Culture (SILAC) coupled to mass spectrometry. OVCAR-3 cultures were labeled separately in light-Arg/Lys and heavy-Arg/Lys isotopes, such that “light” and “heavy” peptides of the same proteins will generate spectra that are different due to a mass shift, thus enabling relative quantification. In control experiments, equal Light/OVCAR3 and Heavy/OVCAR3 total protein mixtures were profiled with 2,800 proteins identified, and 2,465 quantified. Over 94% of these quantified proteins showed a heavy:light ratio between 0.8 and 1.2, making this a robust system for distinguishing differentially expressed proteins. Light/OVCAR-3 was transfected with hsa-let-7a or hsa-let-7e while heavy/OVCAR-3 was transfected with a scrambled miRNA control. KLK6-specific ELISA confirmed its decrease by 50% in transfected cultures over controls. Preliminary SILAC profiling has identified a number of differentially expressed proteins upon transfection with the miRNAs, which will be discussed in the context of OCa pathogenesis and implications for novel biomarker panels and proteomic signatures. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1168. doi:10.1158/1538-7445.AM2011-1168
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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 ».