Abstract AP12: CYSTEINE METABOLISM IN CLEAR CELL OVARIAN CANCER
Notice bibliographique
Résumé
Abstract Our past research has used genomic screens to identify unique features of ovarian cancer subtypes. This has resulted in the description of frequent mutations in ARID1A in both clear cell (CCOC) and endometrioid (ENOC) ovarian cancers and patterns of genomic rearrangements indicative of each subtype. While genomic and RNA expression profiling have been extremely informative, they do not provide a view of the protein expression landscape of cancers. We therefore set out to perform proteomic profiling to better define the key features of the different subtypes and to understand the biology that underpin these diseases. We have developed a novel mass spectrometry proteomic profiling technique based on para–magnetic bead technology called SP3–Clinical Tumor Proteomics (SP3–CTP). This technique is able to perform sensitive proteomic profiling off of a single formalin–fixed paraffin–embedded (FFPE) section. Using this platform, we performed proteomic profiling of three subtypes of ovarian cancer: high grade serous (HGS), ENOC and CCOC. Many proteins known to be enriched in a particular subtype were validated by our screen. WT1 levels were higher in HGS and HNF1B levels were higher in CCOC, as expected. Perhaps more importantly, this screen also revealed that several proteins were enriched in one subtype, which had not previously been described. One such protein was cystathionine gamma lyase (CTH), which was enriched in CCOC compared to the other two subtypes. We validated these results on an ovarian tumor tissue microarray, which confirmed that the majority of CCOC (75%) express high levels of CTH. Conversely, only 10% ENOCa and less than 2% of HGS express high levels of CTH. CTH is a transulfuration enzyme which, along with cystathione beta lyase, form the biosynthetic pathway in which methionine is converted to cysteine. High levels of CTH activity can lead to the generation of hydrogen sulfide (H2S), which has been increasingly implicated as a gaseous intracellular signaling molecule. Overexpression of CTH in CCOC could explain the unique metabolism and other clinical features of this disease. We have found that CTH exhibits a unique staining pattern in the normal endometrium, staining some cells very dark while the rest exhibit little or no CTH staining. It is well documented that endometriosis is the presumed precursor lesion of both CCOC and ENOC. It is not known, however, how such phenotypically different cancers arise from the same precursor. It may be that the metabolic state of cells in the endometrium determines whether it becomes a CCOC or and ENOCa upon receiving a genetic hit. Our initial findings from our proteomic screen have highlighted CTH overexpression as being a feature common in CCOC and comparatively rare in ENOC and HGS. We believe that high CTH expression could provide a unique perspective into the initiation and pathology of CCOC. Citation Format: Dawn R. Cochrane, Christopher S. Hughes, Tayyebeh Nazeran, Anthony N. Karnezis, Melissa K. McConechy, Gregg B. Morin and David G. Huntsman. CYSTEINE METABOLISM IN CLEAR CELL OVARIAN CANCER [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr AP12.
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 | 0,000 | 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) | 0,001 | 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 ».