Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Perakis, SO; Thomas, JE; Pichler, M.
Non-coding RNAs Enabling Prognostic Stratification and Prediction of Therapeutic Response in Colorectal Cancer Patients.
Adv Exp Med Biol. 2016; 937(4):183-204
Doi: 10.1007/978-3-319-42059-2_10
Web of Science
PubMed
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- Führende Autor*innen der Med Uni Graz
- Hasenleithner Samantha
- Co-Autor*innen der Med Uni Graz
- Pichler Martin
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- Abstract:
- Colorectal cancer (CRC) is a heterogeneous disease and current treatment options for patients are associated with a wide range of outcomes and tumor responses. Although the traditional TNM staging system continues to serve as a crucial tool for estimating CRC prognosis and for stratification of treatment choices and long-term survival, it remains limited as it relies on macroscopic features and cases of surgical resection, fails to incorporate new molecular data and information, and cannot perfectly predict the variety of outcomes and responses to treatment associated with tumors of the same stage. Although additional histopathologic features have recently been applied in order to better classify individual tumors, the future might incorporate the use of novel molecular and genetic markers in order to maximize therapeutic outcome and to provide accurate prognosis. Such novel biomarkers, in addition to individual patient tumor phenotyping and other validated genetic markers, could facilitate the prediction of risk of progression in CRC patients and help assess overall survival. Recent findings point to the emerging role of non-protein-coding regions of the genome in their contribution to the progression of cancer and tumor formation. Two major subclasses of non-coding RNAs (ncRNAs), microRNAs and long non-coding RNAs, are often dysregulated in CRC and have demonstrated their diagnostic and prognostic potential as biomarkers. These ncRNAs are promising molecular classifiers and could assist in the stratification of patients into appropriate risk groups to guide therapeutic decisions and their expression patterns could help determine prognosis and predict therapeutic options in CRC.
- Find related publications in this database (using NLM MeSH Indexing)
- Adenocarcinoma - blood
- Adenocarcinoma - diagnosis
- Adenocarcinoma - drug therapy
- Adenocarcinoma - genetics
- Antineoplastic Agents - pharmacology
- Antineoplastic Agents - therapeutic use
- Biomarkers, Tumor - blood
- Biomarkers, Tumor - genetics
- Colorectal Neoplasms - blood
- Colorectal Neoplasms - diagnosis
- Colorectal Neoplasms - drug therapy
- Colorectal Neoplasms - genetics
- Drug Monitoring -
- Drug Resistance, Neoplasm - genetics
- Early Detection of Cancer -
- Forecasting -
- Gene Expression Regulation, Neoplastic -
- Humans -
- MicroRNAs - blood
- MicroRNAs - genetics
- Prognosis -
- RNA, Long Noncoding - biosynthesis
- RNA, Long Noncoding - blood
- RNA, Long Noncoding - genetics
- RNA, Neoplasm - blood
- RNA, Untranslated - biosynthesis
- RNA, Untranslated - blood
- RNA, Untranslated - genetics
- Find related publications in this database (Keywords)
- MicroRNAs
- Long non-coding RNAs
- Colorectal cancer
- Prognosis
- Therapeutic response