Abstract 4056: Determining the role of ZNF687, an uncharacterized zinc finger transcription factor, in lung adenocarcinoma (LUAD)
Notice bibliographique
Résumé
Abstract Introduction: ZNF687, a relatively understudied ZnTF, has been identified as a potential biomarker for lung adenocarcinoma (LUAD) through bioinformatic analysis of The Cancer Genome Atlas (TCGA) database, revealing its frequent upregulation in early-stage LUAD patients. This study aims to elucidate the molecular mechanisms that explain the role of ZNF687 in LUAD using liquid chromatography-mass spectrometry (LC/MS)-based proteomics approaches. Methods: LUAD cell lines NCI-H1437 and Hcc2935 were obtained from ATCC. lentiviral system was employed to deliver shRNA targeting ZNF687 into the LUAD cells. An inducible expression system for tagged ZNF687 was generated in LUAD cells using the PiggyBac transposon system. Proteomics samples were processed with S-Trap and analyzed with LC/MS. Results: We began by analyzing protein interactions of ZNF687. Compared to a control purification, several interaction candidates were significantly enriched in ZNF687 purifications. Among the top candidates identified were ZMYND8 and ZNF592, two ZnTFs previously reported to form the co-regulatory “Z3” complex with ZNF687. Other notable candidates included TSPYL2, a nucleosome assembly protein; KDM5C, a histone H3 lysine 4-specific demethylase; and the casein kinase 2 (CK2) complex. Next, whole proteome profiling was conducted for each LUAD cell line, with or without ZNF687 knockdown via shRNA. Using a data-independent acquisition and label-free quantification approach, we quantified over 5, 000 proteins. With a fold-change cutoff of 2 and a Q-value threshold of 0.05, more than 500 proteins showed significant abundance changes upon ZNF687 knockdown in Hcc2935 cells, while over 700 proteins were significantly altered in NCI-H1437 cells. Notably, the whole proteome analysis revealed an upregulation of epithelial-mesenchymal transition (EMT)-associated proteins following ZNF687 knockdown in both cell lines, suggesting an unexpected repressive role of ZNF687 in EMT. Further examination of common EMT markers, CDH1 and CDH2, in cells overexpressing ZNF687 revealed changes opposite to those observed with ZNF687 knockdown. Conclusions: Given that both LUAD cell lines used in this study were derived from stage I patients and primarily exhibited epithelial characteristics, these findings suggest that the upregulation of ZNF687 in early-stage LUAD may play a role in preventing disease progression. Based on the identification of KDM5C as a potential ZNF687 interactor, we proposed the following model: ZNF687 recruits KDM5C to EMT related genes; subsequently, the expression of EMT genes are down regulated due to the loss of H3K4me3 from those chromatin regions, resulting in suppression of the EMT process. Citation Format: Xingyu Liu, Yixuan Xie, Zongtao Lin, Patrick Pribil, Benjamin Garcia. Determining the role of ZNF687, an uncharacterized zinc finger transcription factor, in lung adenocarcinoma (LUAD) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4056.
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 | 0,000 |
| 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 | 0,000 |
| 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 ».