Abstract 4056: Determining the role of ZNF687, an uncharacterized zinc finger transcription factor, in lung adenocarcinoma (LUAD)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".