ArticleDiscover oncology2026
Deciphering RNA and protein expression discordance identifies TOP2A as a prognostic biomarker and potential therapeutic target in lung adenocarcinoma.
Article in Discover oncology, 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveUnderstanding the discordance between RNA and protein expression can help elucidate underlying disease mechanisms that cannot be fully explained using transcriptomic information alone. Unveiling novel mechanisms of tumorigenesis through multi-omics data using real-world data is central to advancing precision in oncology and tumor prevention. In this study, we investigated the expression discordance between non-tumor and tumor patient samples to elucidate the underlying mechanism of tumorigenesis in lung adenocarcinoma (LUAD).
methodsWe performed a correlation analysis of RNA and protein using normal tissue adjacent to tumor and tumor samples to identify distinct expression profiles to unveil tumorigenesis. Publicly available multi-omics data, including RNA, proteins, phosphoproteins, and acetyl proteins, were obtained from the Clinical Proteomic Tumor Analysis Consortium. Gene expression analysis at the single-cell level was performed using single-cell RNA sequencing data. A transformer model was used for in silico drug screening.
resultsMost genes in tumors showed a positive correlation between RNA and protein expression. DNA topoisomerase II alpha (TOP2A) and Cyclin-dependent kinase 1 showed a drastic correlation during tumorigenesis in patient with LUAD. TOP2A gene and protein expression were associated with overall survival in patients with LUAD. Single-cell RNA sequencing revealed that highly correlated genes were clustered as distinct subpopulations. TOP2A expression was associated with TP53 genomic status and miR-26A1 expression, which targets TOP2A gene. In silico screening identified novel drugs that could specifically target TOP2A.
conclusionsOur findings elucidated the multi-layer expression profiles of LUAD, revealing its tumorigenesis and potential clinical implications and interventions.
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.