ArticleOncotarget2017
Identification and functional analysis of differentially expressed genes in poorly differentiated hepatocellular carcinoma using RNA-seq.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Transcriptome analysis creates a new era of precision medicine for managing recurrent hepatocellular carcinoma.World journal of gastroenterology · 2023Review
- [Bioinformatics analysis of key genes and prognosis-related genes during the onset of hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2020Article
- Genome-wide Analyses on Single Disease Samples for Potential Biomarkers and Biological Features of Molecular Subtypes: A Case Study in Gastric Cancer.International journal of biological sciences · 2018Article
- DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates.Bioinformatics (Oxford, England) · 2017Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Poorly differentiated (PD) hepatocellular carcinoma (HCC) has a worse prognosis compared to moderately differentiated (MD) and well differentiated (WD) HCC. We aimed to identify differentially expressed genes (DEGs) to explore the mechanism of PD HCC. Transcriptome sequencing was performed on tumor and adjacent non-tumorous tissues of PD, MD and WD HCC patients (3 for each group). DEGs were thus identified and functionally analyzed. Further RT-PCR was performed to validate DEGs specific for PD HCC in 47 pairs of samples (15 for PD, 18 for MD, 14 for WD). A total of 681 PD DEGs were detected, including 368 up-regulated and 313 down-regulated genes. Less DEGs were found for MD and especially for WD HCC. Through bioinformatics analysis, PD HCC DEGs were enriched in liver tissue and liver cancer cells, and in biological process and pathway including metabolism, cell cycle, translation and blood coagulation. Potential drugs and genetic perturbations were found to reverse the cancer condition. The RT-PCR results showed consistency with RNA-seq in the validation of 4 DEGs specific for PD HCC. This study detected and validated DEGs of PD HCC, which provides useful information on molecular mechanism of PD HCC for development of new biomarkers, therapeutic targets and 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.