ArticleTranslational cancer research2026
Bioinformatics analysis of the expression and prognostic significance of depression-related genes in lung adenocarcinoma.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Depression plays a crucial role in lung adenocarcinoma (LUAD) occurrence, progression, and prognosis. However, the impact of depression-related genes (DRGs) on the prognosis of LUAD patients is unclear. Thus, a prognosis prediction model was constructed to assess the potential impact of depression on LUAD prognosis. Methods: The gene expression profiles from The Cancer Genome Atlas (TCGA)-LUAD and GSE68465 were collected for model training and validation. By identifying the intersection of DRGs and differentially expressed genes (DEGs) in LUAD, a risk score model was constructed to stratify patient risk based on univariate and multivariate analyses. The immune infiltration status and therapeutic potential of different risk groups were further explored. The correlation between key genes and clinical outcomes was evaluated in Kaplan-Meier (KM) analysis. Finally, the expression and mechanism of key genes were verified by Results: We identified 2,222 DEGs and 385 DRGs-DEGs, and DRGs-DEGs were closely related to nervous system function and cell signaling. Nine DRGs-DEGs were identified to construct the risk score model for risk stratification. The model's predictive accuracy for patient survival was confirmed by receiver operating characteristic (ROC) curve analysis. LUAD patients with high-risk had significantly higher levels of CD8 T cells, B cells memory, and macrophages M1, which may affect the prognosis of LUAD patients. Furthermore, low-risk patients responded better to immunotherapy. KM analysis revealed that ACSS3 was significantly associated with poor prognosis in LUAD patients. oe-ACSS3 inhibits LUAD cell proliferation, migration, and invasion, and also promotes apoptosis. Conclusions: The nine-gene risk score model proposed in our study demonstrated promising prognostic performance, highlighting the significant role of depression in LUAD prognosis. ACSS3 was demonstrated to play a critical role in regulating LUAD progression and may be a potential therapeutic target for LUAD treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.