ArticleGut and liver2018
Subclassification and Detection of New Markers for the Discrimination of Primary Liver Tumors by Gene Expression Analysis Using Oligonucleotide Arrays.
Article in Gut and liver, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Leveraging weak complementary labels enhances semantic segmentation of hepatocellular carcinoma and intrahepatic cholangiocarcinoma.Scientific reports · 2024Article
- Panel of potential lncRNA biomarkers can distinguish various types of liver malignant and benign tumors.Journal of cancer research and clinical oncology · 2021Article
- Impact of a deep learning assistant on the histopathologic classification of liver cancer.NPJ digital medicine · 2020Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimsThe failure to correctly differentiate between intrahepatic cholangiocarcinoma (CC) and hepatocellular carcinoma (HCC) is a significant clinical problem, particularly in terms of the different treatment goals for both cancers. In this study a specific gene expression profile to discriminate these two subgroups of liver cancer was established and potential diagnostic markers for clinical use were analyzed.
methodsTo evaluate the gene expression profiles of HCC and intrahepatic CC, Oligonucleotide arrays (
results695 genes/expressed sequence tags (ESTs) in HCC (245 up-/450 down-regulated) and 552 genes/ESTs in CC (221 up-/331 down-regulated) were significantly dysregulated (p＜0.05, fold change >2, ≥70%). Using a supervised learning method, and one-way analysis of variance a specific 270-gene expression profile that enabled rapid, reproducible differentiation between both tumors and nonmalignant liver tissues was established. A panel of 12 genes (e.g., HSP90β, ERG1, GPC3, TKT, ACLY, and NME1 for HCC; SPT2, T4S3, CNX43, TTD1, HBD01 for CC) were detected and partly described for the first time as potential discrimination markers.
conclusionsA specific gene expression profile for discrimination of primary liver cancer was identified and potential marker genes with feasible clinical impact were described.
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