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Aichler, M. ; Luber, B.* ; Lordick, F.* ; Walch, A.K.

Proteomic and metabolic prediction of response to therapy in gastric cancer.

World J. Gastroenterol. 20, 13648-13657 (2014)
Verlagsversion DOI PMC
Open Access Gold
Several new treatment options for gastric cancer have been introduced but the prognosis of patients diagnosed with gastric cancer is still poor. Disease prognosis could be improved for high-risk individuals by implementing earlier screenings. Because many patients are asymptomatic during the early stages of gastric cancer, the diagnosis is often delayed and patients present with unresectable locally advanced or metastatic disease. Cytotoxic treatment has been shown to prolong survival in general, but not all patients are responders. The application of targeted therapies and multimodal treatment has improved prognosis for those with advanced disease. However, these new therapeutic strategies do not uniformly benefit all patients. Predicting whether patients will respond to specific therapies would be of particular value and would allow for stratifying patients for personalized treatment strategies. Metabolic imaging by positron emission tomography was the first technique with the potential to predict the response of esophago-gastric cancer to neoadjuvant therapy. Exploring and validating tissue-based biomarkers are ongoing processes. In this review, we discuss the status of several targeted therapies for gastric cancer, as well as proteomic and metabolic methods for investigating biomarkers for therapy response prediction in gastric cancer.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Gastric Cancer ; Matrix-assisted Laser Desorption-ionization ; Positron Emission Tomography ; Response Prediction ; Therapy
Sprache englisch
Veröffentlichungsjahr 2014
HGF-Berichtsjahr 2014
ISSN (print) / ISBN 1007-9327
e-ISSN 2219-2840
Zeitschrift World Journal of Gastroenterology
Quellenangaben Band: 20, Heft: 38, Seiten: 13648-13657 Artikelnummer: , Supplement: ,
Verlag WJG Press
Begutachtungsstatus Peer reviewed
Institut(e) Research Unit Analytical Pathology (AAP)
Institute of Pathology (PATH)
POF Topic(s) 30205 - Bioengineering and Digital Health
30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-500390-001
G-500300-001
PubMed ID 25320503
DOI 10.3748/wjg.v20.i38.13648
WOS ID WOS:000343882100002
Scopus ID 84910002215
Erfassungsdatum 2014-10-18
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