ArticleCancer informatics2022
Bioinformatics Analysis of Differential Gene and MicroRNA Expression in Lung Adenocarcinoma: Genetic Effects on Patient Prognosis, as Indicated by the TCGA Database.
Article in Cancer informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 3 citations in OpenAlex.
- A Multi-Gene Signature Associated with 1-Year Survival in Patients with Stage I Liver Cancer: Integration of Preclinical and TCGA Data.Current issues in molecular biology · 2026Article
- BRPF1 in cancer epigenetics: a key regulator of histone acetylation and a promising therapeutic target.Cell death discovery · 2025Review
- Integrative pan-cancer analysis reveals the importance of PAQR family in lung cancer.Journal of cancer research and clinical oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To investigate the differential expression of genes and microRNAs (miRNAs) in patients with lung adenocarcinoma and the relationship between such changes and patient prognosis. Methods: We analyzed the expression levels of genes and miRNAs in lung adenocarcinoma tissues and adjacent normal tissues using The Cancer Genome Atlas database (TCGA). We analyzed the function of the differentially expressed genes and miRNAs in a co-expression network. Finally, we performed survival analysis of differential genes and miRNAs in the co-expression network using clinical data from the TCGA database. Results: We successfully identified 6064 differentially expressed genes: 5324 upregulated genes and 740 downregulated genes. And we identified 161 differentially expressed miRNAs: 126 upregulated miRNAs and 35 downregulated miRNAs. We identified several genes that were related to each other in the co-expression network. Further analysis revealed that the high expression levels of Conclusions: Our data showed that
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.