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Cancer Diagnostic and Predictive Biomarkers

Authors: Franco M. Buonaguro; David Pauza; Maria Lina Tornesello; Pierre Hainaut; Renato Franco; Francesco M. Marincola;

Cancer Diagnostic and Predictive Biomarkers

Abstract

The new high-throughput “omics” technologies have recently opened the possibility to identify molecular changes and metabolic pathways in each cancer type with the possibility of molecular tumor subclassification and identification of a more reliable prognosis and appropriate treatment [1–3]. A further result is the reduction of overtreatment of those with higher responsivity and better prognosis. Furthermore, such studies do have the possibility of identifying specific cancer targets, with higher effectiveness of chemotherapy and much lower general toxicity. The whole field is in a current turmoil, and this specific issue, focused on the clinical validation of newly identified biomarkers, has been able to bridge molecular mechanisms with clinical diagnosis and therapeutic responsivity touching different aspects of this topic. The two major topics have been (a) characterization of biomarkers for more specific cancer diagnosis and prognosis; (b) identification of biomarkers for progression evaluation and therapeutic responsivity. Biomarkers of cancer susceptibility have been also reported.

Keywords

Editorial, Neoplasms, Biomarkers, Tumor, Humans, Prognosis, Biomarkers, Pharmacological

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Average
Green
gold