ArticleBiology2012
Next-generation sequencing: application in liver cancer-past, present and future?
Article in Biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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.
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
13 citing papers in PubMed.
- Histological and Molecular Evaluation of Liver Biopsies: A Practical and Updated Review.International journal of molecular sciences · 2025Review
- Review
- Advances and challenges in molecular understanding, early detection, and targeted treatment of liver cancer.World journal of hepatology · 2025Review
- The Role ofMicroorganisms · 2023Review
- Therapeutic options for intrahepatic cholangiocarcinoma.Hepatobiliary surgery and nutrition · 2017Review
- Hepatocellular Carcinoma: a Comprehensive Review of Biomarkers, Clinical Aspects, and TherapyAsian Pacific journal of cancer prevention : APJCP · 2017Article
- Frequently mutated genes/pathways and genomic instability as prevention targets in liver cancer.Carcinogenesis · 2017Review
- The landscape of targeted therapies for cholangiocarcinoma: current status and emerging targets.Oncotarget · 2016Review
- Article
- Next-generation sequencing and personalized genomic medicine in hepatobiliary malignancies.Hepatic oncology · 2015Review
- Personalized medicine in hematology - A landmark from bench to bed.Computational and structural biotechnology journal · 2014Review
- A perspective on molecular therapy in cholangiocarcinoma: present status and future directions.Hepatic oncology · 2014Article
- Linking MLL and the HGF-MET signaling pathway in liver cancer.The Journal of clinical investigation · 2013Article
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.
Funding
Abstract
Hepatocellular Carcinoma (HCC) is the third most deadly malignancy worldwide characterized by phenotypic and molecular heterogeneity. In the past two decades, advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. More recently, improvements of sophisticated next-generation sequencing (NGS) technologies have enabled complete and cost-efficient analyses of cancer genomes at a single nucleotide resolution and advanced into valuable tools in translational medicine. Although the use of NGS in human liver cancer is still in its infancy, great promise rests in the systematic integration of different molecular analyses obtained by these methodologies, i.e., genomics, transcriptomics and epigenomics. This strategy is likely to be helpful in identifying relevant and recurrent pathophysiological hallmarks thereby elucidating our limited understanding of liver cancer. Beside tumor heterogeneity, progress in translational oncology is challenged by the amount of biological information and considerable "noise" in the data obtained from different NGS platforms. Nevertheless, the following review aims to provide an overview of the current status of next-generation approaches in liver cancer, and outline the prospects of these technologies in diagnosis, patient classification, and prediction of outcome. Further, the potential of NGS to identify novel applications for concept clinical trials and to accelerate the development of new cancer therapies will be summarized.
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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.