ArticleScientific reports2019
Characterization of cancer omics and drug perturbations in panels of lung cancer cells.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 17 citations in OpenAlex.
- Pharmacomultiomics suggests new off-targets for targeted anti-cancer agents.Journal of pharmaceutical analysis · 2026Article
- Article
- Classification and characterization of alternative promoters in 26 lung adenocarcinoma cell lines.Japanese journal of clinical oncology · 2023Article
- Article
- Phasing analysis of lung cancer genomes using a long read sequencer.Nature communications · 2022Article
- Cell Painting predicts impact of lung cancer variants.Molecular biology of the cell · 2022Article
- Single-Cell Analyses Reveal Diverse Mechanisms of Resistance to EGFR Tyrosine Kinase Inhibitors in Lung Cancer.Cancer research · 2021Article
- Untargeted metabolomics and transcriptomics identified glutathione metabolism disturbance and PCS and TMAO as potential biomarkers for ER stress in lung.Scientific reports · 2021Article
- Next Generation Imaging Techniques to Define Immune Topographies in Solid Tumors.Frontiers in immunology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To better understand the disruptions of transcriptional regulations and gene expression in lung cancers, we constructed a multi-omics catalogue of the responses of lung cancer cells to a series of chemical compounds. We generated and analyzed 3,240 RNA-seq and 3,393 ATAC-seq libraries obtained from 23 cell lines treated with 95 well-annotated compounds. To demonstrate the power of the created multi-omics resource, we attempted to identify drugs that could induce the designated changes alone or in combination. The basal multi-omics information was first integrated into co-expression modules. Among these modules, we identified a stress response module that may be a promising drug intervention target, as new combinations of compounds that could be used to regulate this module and the consequent phenotypic appearance of cancer cells have been identified. We believe that the multi-omics profiles generated in this study and the strategy used to stratify them will lead to more rational and efficient development of anticancer drugs.
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.