Abstract 4028: Therapeutic relevance of two novel cancer candidate genes, <i>RASAL2</i> and <i>NENF</i>, activated by DNA hypomethylation
Notice bibliographique
Résumé
Abstract DNA hypomethylation, a process of losing DNA methylation marks, plays an important role in cancer, particularly through activating genes that promote metastasis. We used a whole genome approach of mapping promoters that are hypomethylated in hepatocellular carcinoma (HCC), in order to identify novel candidate genes that play a critical role in cancer metastasis. We focused on two genes that were not previously assigned a role in cancer or cancer metastasis: Ras-GTPase-activating protein (RASAL2) and neuron derived neurotrophic factor (NENF) genes. We tested whether these genes play a causal role in cellular transformation and cancer invasiveness and are therefore candidate targets for anticancer drugs. siRNA depletion of RASAL2 and NENF expression in HepG2 HCC, SkHep1 liver adenocarcinoma, and T24 bladder cancer cell lines was performed and confirmed by QPCR. Following siRNA knockdowns, the effects on cell viability, anchorage-independent growth, and invasive capacities were assessed as measured by trypan blue exclusion test, soft agar, and Boyden chamber assays, respectively. We also evaluated phosphorylation of several serine/threonine kinases by western blot. RASAL2 and NENF depletion effectively inhibits cancer cell growth and cell invasive capacities. siRNA knockdowns resulted in 70-90% reduction of cell viability compared with cells treated with control siRNA. Cell invasion through an extracellular matrix in vitro was impeded by 80-98% after depletion of these proteins with the most profound effect seen in SkHep1 cell line. Anchorage independent growth, an indicator of the transformed state of cancer cells, was almost completely suppressed (97-100%) in SkHep1 and T24 cells with siRNA depletion whereas control cells grew in soft agar forming approximately 300 colonies/well on a 6-well plate. Interestingly, the observed effects seem to be cancer cell-specific as no significant changes were found in normal hepatocytes after knockdowns of the tested genes. The analysis of phosphorylation level of a set of kinases demonstrated the implication of the tested genes in PI3K/AKT and MAPK signaling pathways, functionally linked to cancer. After RASAL2 and NENF depletion in SkHep1 cells, we observed a decrease in phosphorylation of AKT, JNK, MKK6, p70S6 kinases by 60%, 50%, 50-80% and 50-70%, respectively. The knockdown of RASAL2 and NENF also led to changes in expression of genes involved with the DNA methylation machinery, including DNMT1 and MBD2 down-regulation. Our results established for the first time the role of two novel candidate genes in cancer and defined the potential functional role of DNA hypomethylation in activation of these genes.This study was supported by a grant from the MDEIE program of the government of Quebec and the National Cancer Institute of Canada to MS. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4028. doi:1538-7445.AM2012-4028
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 | 0,000 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».