| Literature DB >> 30282914 |
Gianluca Lopez1, Francesca Boggio2, Stefano Ferrero3,4, Nicola Fusco5,6, Alessandro Del Gobbo7.
Abstract
Despite the significant recent achievements in the diagnosis and treatment of colorectal cancer (CRC), the prognosis of these patients has currently plateaued. During the past few years, the opportunity to consider multiple treatment modalities (including surgery and other locoregional treatments, systemic therapy, and targeted therapy) led to the research of novel prognostic and predictive biomarkers in CRC liver metastases (CRCLM) patients. In this review, we seek to describe the current state of knowledge of CRCLM biomarkers and to outline impending clinical perspectives, in particular focusing on the cutting-edge tools available for their characterization.Entities:
Keywords: biomarkers; colorectal cancer; immunohistochemistry; liver metastases; molecular markers; predictive; prognostic
Mesh:
Substances:
Year: 2018 PMID: 30282914 PMCID: PMC6213422 DOI: 10.3390/ijms19103014
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
Figure 1Oncoprint visualization of highly recurrent somatic molecular alterations by frequency in colorectal cancer liver metastases (313 patients, 319 samples from cBioPortal). Each row represents a gene, as reported on the left; types of alterations are color-coded on the basis of the legend on the bottom.
Figure 2Domain structure and gene alterations of the 12 most frequently altered genes in colorectal cancer liver metastases (312 patients, 318 samples from cBioPortal). Mutation types are color-coded on the basis of the legend at the bottom.
Figure 3Network of the interactions between the most frequently altered genes in colorectal cancer liver metastases (highlighted in bold) and other cancer genes. Interaction types (arrows and lines) are color-coded on the basis of the legend at the top right.
Figure 4Overall survival of 312 colorectal cancer patients with liver metastases based on SMAD4 (A) and BRAF (B) gene alterations. Survival curves are built according to the Kaplan–Meier method. Data from The Cancer Genome Atlas Network are publicly available at cbioportal.org.
Figure 5Flowchart of study design.