ArticleThe EPMA journal2018
Liquid biopsy and multiparametric analysis in management of liver malignancies: new concepts of the patient stratification and prognostic approach.
Article in The EPMA journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 36 citations in OpenAlex.
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- Machine Learning Can Predict Total Death After Radiofrequency Ablation in Liver Cancer Patients.Clinical Medicine Insights. Oncology · 2021Article
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- Biobanks in the era of big data: objectives, challenges, perspectives, and innovations for predictive, preventive, and personalised medicine.The EPMA journal · 2020Review
- Optimal multiparametric set-up modelled for best survival outcomes in palliative treatment of liver malignancies: unsupervised machine learning and 3 PM recommendations.The EPMA journal · 2020Article
- Flavonoids against the Warburg phenotype-concepts of predictive, preventive and personalised medicine to cut the Gordian knot of cancer cell metabolism.The EPMA journal · 2020Review
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- Carotenoids in Cancer Apoptosis-The RoadCancers · 2020Review
- Liquid Biopsy is Instrumental for 3PM Dimensional Solutions in Cancer Management.Journal of clinical medicine · 2020Review
- Label-free quantitative identification of abnormally ubiquitinated proteins as useful biomarkers for human lung squamous cell carcinomas.The EPMA journal · 2020Article
- Thirty-Day Mortality After Curative and Palliative Anti-Cancer Treatment: Data Interpretation and Lessons for Clinical Implementation.Cancer management and research · 2020Article
- Comparing Quality of Life in Breast Cancer Patients Who Underwent Mastectomy Versus Breast-Conserving Surgery: A Meta-Analysis.International journal of environmental research and public health · 2019Article
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Corrections and comments
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe annually recorded incidence of primary hepatic carcinomas has significantly increased over the past two decades accounting for over 800 thousand of annual deaths caused by hepatocellular carcinoma (HCC) alone globally. Further, secondary liver malignancies are much more widespread compared to primary hepatic carcinomas: almost all solid malignancies are able to metastasise into the liver. The primary tumours most frequently metastasising to the liver are breast followed by colorectal carcinomas. Given the increased incidence of both primary and metastatic liver cancers, a new, revised approach is needed to advance medical care based on predictive diagnostics, innovative screening programmes, targeted preventive measures, and patient stratification for treatment algorithms tailored to individualised patient profile. ADVANTAGES OF THE APPROACH TAKEN: The current pilot study took advantage of systemic alterations characteristic for liver malignancies, utilising liquid biopsy (blood samples) and specific biomarker patterns detected. Key molecular pathways relevant for pathomechanisms of liver cancers have been considered opening a perspective for both-individualised diagnostics and targeted treatment. Systemic alterations have been analysed prior to the therapy application avoiding molecular biological effects potentially diminishing predictive power of the biomarker-panel proposed. Multi-omics at DNA and protein (both expression and activity) levels has been applied. An established biomarker panel is considered as a powerful tool for individualised patient profiling and improved multi-level diagnostics-both predictive and prognostic ones. RESULTS AND
conclusionsBiomarker panels have been created for the patient stratification, prediction of a more optimal therapy and prognosis of survival based on the individualised patient profiling. Although there are some limitations of the pilot study performed, the results are encouraging, as it may be possible, through further research along these lines, to find a clinically and cost-effective means of stratifying liver cancer patients for personalised care and therapy. The benefits to the patient and society of accurate treatment stratification cannot be overemphasised.
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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.