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Background: The ideal management for patients with intermediate and advanced stage hepatocellular carcinoma (HCC) is controversial. The main purpose of this systematic review is to examine the role of liver resection in patients with intermediate stage HCC (multinodular HCCs) and in advanced stage HCC [mainly patients with portal vein tumor thrombosis (PVTT)]. Methods: A systematic search of the literature was performed in Pud Med and the Cochrane Library from 01.01.2000 to 30.06.2016. Results: Twenty-three articles with 2412 patients with multinodular HCCs were selected. Also, 29 studies with 3659 patients with HCCs with macrovascular invasion were selected. In patients with multinodular HCCs the median post-operative morbidity was 25% and the 90-day mortality was 2.7%. The median survival was 37 months and the 5-year survival 35%. The 5-year survival was much better for patients with a number of HCCs ≤3 vs. HCCs >3 (49% vs. 23%). In patients with macrovascular invasion, who underwent hepatic resection, the median post-operative morbidity was 33% and the in-hospital mortality 2.7%. The median survival was 15 months. The 3 and 5year survival was 33% and 20% respectively. Moreover a significant difference in survival was noted according to PVTT stage: 5- year survival for distal PVTT, PVTT of the main intrahepatic PV branch and PVTT extending to the main PV was 45%, 19% and 14.5% respectively. Conclusions: Liver resection in patients with multinodular HCCs and HCCs with PVTT offers satisfactory long-term survival and should be considered in selected patients. © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology

Expert Rev Mol Diagn

Expert Rev Proteomics

Epigenomics

Expert Rev Med Devices

In a previous European prospective investigation into cancer and nutrition (EPIC) analysis, we found an inverse association between total intake of vegetables, onion and garlic, and risk of intestinal gastric cancer (GC) and between citrus fruit and risk of cardia GC. The aim of this study is to reanalyze the effect of fruit and vegetables (F&V), based on a longer follow-up and twice the number of GC cases. Subjects are 477,312 men and women mostly aged 35 to 70 years participating in the EPIC cohort, including 683 gastric adenocarcinomas with 11 years of follow-up. Information on diet and lifestyle was collected at baseline. A calibration study in a subsample was used to correct for dietary measurement errors. When comparing the highest vs. lowest quintile of intake, we found an inverse association between total intake of V&F and GC risk [hazard ratio (HR) 0.77; 95% confidence interval (CI) 0.57-1.04; p for trend 0.02], between fresh fruit and risk of the diffuse type (HR 0.59; 95% CI 0.36-0.97; p for trend 0.03) and an inverse association between citrus fruit and risk of cardia cancer (HR 0.61; 95% CI 0.38-1.00, p for trend 0.01). Although calibration revealed somewhat stronger inverse associations, none of the risks reached statistical significance. There was no association between total or specific vegetables intake and GC risk. The inverse association between fresh fruit and citrus fruits and risk of GC seems to be restricted to smokers and the Northern European countries. Fresh fruit and citrus fruit consumption may protect against diffuse and cardia GC, respectively. Copyright © 2012 UICC.

Expert Rev Mol Diagn

Womens Health (Lond Engl)

Expert Rev Mol Diagn

Expert Rev Med Devices

Pharmacogenomics

Expert Rev Mol Diagn

Expert Rev Anticancer Ther

Expert Rev Med Devices

Future Oncol

Biomark Med

Ann Surg Oncol

Life diversity can now be clearly explored with the next-generation DNA sequencing technology, allowing the discovery of genetic variants among individuals, patients and tumors. However, beyond causal mutations catalog completion, systems medicine is essential to link genotype to phenotypic cancer diversity towards personalized medicine. Despite advances with traditional single genes molecular research, including rare mutations in BRCA1/2 and CDH1 for primary prevention and trastuzumab for treating HER2-overexpressing breast and gastric tumors, overall, treatment failure and death rates are still alarmingly high. Revolution in sequencing reveals that, now both a huge number and widespread variability of driver mutations, including single-nucleotide polymorphisms, genomic rearrangements and copy-number changes involved in breast cancer development. All these genetic alterations result in a heterogeneous deregulation of signaling pathways, including EGFR, HER2, VEGF, Wnt/Notch, TGF and others.Cancer initiation, progression and metastases are driven by complex molecular networks rather than linear genotype-phenotype relationship. Therefore, clinical expectations by traditional molecular research strategies targeting single genes and single signaling pathways are likely minimal. This review discusses the necessity of molecular networks modeling to understand complex gene-gene, protein-protein and gene-environment interactions. Moreover, the potential of systems clinico-biological approaches to predict intracellular signaling pathways components networks and cancer heterogeneous cells within an individual tumor is described. A flowchart specific for three steps in cancer evolution separately tumorigenesis, early-stage and advanced-stage breast cancer is presented. Using reverse engineering starting with the integration of available established clinical, environmental, treatment and oncological outcomes (survival and death) data and then the still incomplete but progressively accumulating genotypic data into computational networks modeling may lead to bionetworks-based discovery of robust biomarkers and highly effective cancer drugs targets. Pharmacogenomics J

Expert Rev Anticancer Ther

Pharmacogenomics

Epigenomics

Expert Rev Anticancer Ther

Future Oncol

Surg Endosc

Epigenomics

Expert Rev Anticancer Ther

World J Surg

Pharmacogenomics

Although cancer heterogeneity, even within individual tumors with different treatment responses of subcloncal cells populations, suggests the need for personalized medicine, most funding and efforts go to conventional single gene-based research and comparative-effectiveness research. Cancer arises from changes in the DNA sequence in the genomes of cancer cells. These accelerating somatic mutations dysregulate signaling pathways, including EGFR, Wnt/Notch, Hedgehog and others, with a central role in cell growth, proliferation, survival, angiogenesis and metastasis. All of these genetic alterations can now be discovered using next-generation DNA sequencing technology. This high-throughput technology can achieve two major goals: first, to complete the catalogue of driver mutations, including point mutations, rearrangements and copy-number changes, by full and targeted sequencing; and second, to explore the functional role of cancer genes and their interactions by genome-wide RNA, serial analysis of gene expression, microRNAs, protein-DNA interactions, and comprehensive analyses of transcriptomes and interactomes. This review article discusses the challenges, including costs, in completing the catalogue of driver mutations for each cancer type and understanding how cancer genomes operate as whole biological systems. Now high-quality clinical treatment and outcomes (death or survival) data from biobanks, and extensive genetics and genomics data for some common tumors, including breast, colorectal and pancreatic cancer, are available. In this article, we will describe how all these clinical and genetics data could be integrated into reverse engineering-based network modeling to approach the extremely complex genotype-phenotype map. This clinico-genome systems model, published for the first time, opens the way for the discovery of new molecular innovations, both predictive markers and therapies, towards personalized treatment of cancer. Instead of the comparative-effectiveness research or personalized medicine debate, harmonization of both can revolutionize cancer management. Expert Rev Mol Diagn

Endoscopy

Ann Surg Oncol

Expert Rev Gastroenterol Hepatol