ArticleJapanese journal of clinical oncology2023
Classification and characterization of alternative promoters in 26 lung adenocarcinoma cell lines.
Article in Japanese journal of clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 5 citations in OpenAlex.
- Metabolic disease variants rewire gene regulation through disruption of DNA G-quadruplex structures.Genome biology · 2026Article
- G-quadruplex structures as modulators of alternative promoter usage.NAR genomics and bioinformatics · 2025Article
- Alternative Promoters Drive Transcriptomic Reprogramming and Prognostic Stratification in TNBC.NPJ systems biology and applications · 2025Article
- mRNA isoform switches during mouse zygotic genome activation.Cell proliferation · 2024Article
- Genome-wide analyses reveal the regulatory roles of DNA methylation-regulated alternative promoter transcripts in breast cancer.Human genetics · 2024Article
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 at 2 institutions in 1 country.
Funding
Abstract
backgroundGenome-wide landscape of alternative promoter use remains unknown. We determined expression profiles of promoters in 26 lung adenocarcinoma cell lines using the transcriptional start site-sequencing data and proposed an index 'canonical promoter usage' to quantify the diversity of alternative promoter usage.
methodsTranscriptional start site-sequencing and other datasets were obtained from the DataBase of Transcriptional Start Sites. Transcriptional start site-sequencing read clusters were mapped onto RefGene to determine the promoters. Commonly used promoters were designated as canonical promoters. The sequence logos, CpG islands, DNA methylation and histone modifications of canonical and non-canonical promoters were examined. Canonical promoter usage was calculated by dividing 'read counts of a canonical promoter' by 'read counts of all the units of promoters' on each gene. The expressed genes were subjected to hierarchical clustering according to their canonical promoter usage.
resultsAmong 104 455 promoters for 14 297 genes, 8659 canonical and 68 197 non-canonical promoters were identified. Corresponding to higher expression, canonical promoters showed core promoter sequences, higher CpG island positivity, less DNA methylation and higher transcription-promoting histone modifications. Gene ontology enrichment analysis revealed that the clusters with lower canonical promoter usage were related to signalling pathways, whereas clusters of tightly regulated genes with higher canonical promoter usage were related to housekeeping genes.
conclusionCanonical promoters were regulated by conventional transcriptional machinery, while non-canonical promoters would be targets of 'leaky' expression. Further investigation is warranted to analyse the correlation between alternative promoter usage and biological characteristics contributing to carcinogenesis.
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.