Objective: Omega-3 polyunsaturated fatty acids (PUFAs) have anticolorectal cancer (CRC) activity. The intestinal microbiota has been implicated in colorectal carcinogenesis. Dietary omega-3 PUFAs alter the mouse intestinal microbiome compatible with antineoplastic activity. Therefore, we investigated the effect of omega-3 PUFA supplements on the faecal microbiome in middle-aged, healthy volunteers (n=22). Design: A randomised, open-label, cross-over trial of 8 weeks’ treatment with 4 g mixed eicosapentaenoic acid/docosahexaenoic acid in two formulations (soft-gel capsules and Smartfish drinks), separated by a 12-week ‘washout’ period. Faecal samples were collected at five time-points for microbiome analysis by 16S ribosomal RNA PCR and Illumina MiSeq sequencing. Red blood cell (RBC) fatty acid analysis was performed by liquid chromatography tandem mass spectrometry. Results: Both omega-3 PUFA formulations induced similar changes in RBC fatty acid content, except that drinks were associated with a larger, and more prolonged, decrease in omega-6 PUFA arachidonic acid than the capsule intervention (p=0.02). There were no significant changes in α or β diversity, or phyla composition, associated with omega-3 PUFA supplementation. However, a reversible increased abundance of several genera, including Bifidobacterium , Roseburia and Lactobacillus was observed with one or both omega-3 PUFA interventions. Microbiome changes did not correlate with RBC omega-3 PUFA incorporation or development of omega-3 PUFA-induced diarrhoea. There were no treatment order effects. Conclusion: Omega-3 PUFA supplementation induces a reversible increase in several short-chain fatty acid-producing bacteria, independently of the method of administration. There is no simple relationship between the intestinal microbiome and systemic omega-3 PUFA exposure. Trial registration number: ISRCTN18662143.

HER2 overexpression/amplification is linked to trastuzumab response in breast/gastric cancers. One suggested anti‐EGFR resistance mechanism in colorectal cancer (CRC) is aberrant MEK–AKT pathway activation through HER2 up‐regulation. We assessed HER2‐amplification/overexpression in stage II–III and IV CRC patients, assessing relationships to KRAS/BRAF and outcome. Pathological material was obtained from 1914 patients in the QUASAR stage II–III trial and 1342 patients in stage IV trials (FOCUS and PICCOLO). Tissue microarrays were created for HER2 immunohistochemistry. HER2‐amplification was assessed using FISH and copy number variation. KRAS/BRAF mutation status was assessed by pyrosequencing. Progression‐free survival (PFS) and overall survival (OS) data were obtained for FOCUS/PICCOLO and recurrence and mortality for QUASAR; 29/1342 (2.2%) stage IV and 25/1914 (1.3%) stage II–III tumours showed HER2 protein overexpression. Of the HER2‐overexpressing cases, 27/28 (96.4%) stage IV tumours and 20/24 (83.3%) stage II–III tumours demonstrated HER2 amplification by FISH; 41/47 (87.2%) also showed copy number gains. HER2‐overexpression was associated with KRAS/BRAF wild‐type (WT) status at all stages: in 5.2% WT versus 1.0% mutated tumours (p < 0.0001) in stage IV and 2.1% versus 0.2% in stage II–III tumours (p = 0.01), respectively. HER2 was not associated with OS or PFS. At stage II–III, there was no significant correlation between HER2 overexpression and 5FU/FA response. A higher proportion of HER2‐overexpressing cases experienced recurrence, but the difference was not significant. HER2‐amplification/overexpression is identifiable by immunohistochemistry, occurring infrequently in stage II–III CRC, rising in stage IV and further in KRAS/BRAF WT tumours. The value of HER2‐targeted therapy in patients with HER2‐amplified CRC must be tested in a clinical trial. © 2015 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Colorectal carcinoma (CRC) is a common cause of mortality¹, but a comprehensive description of its genomic landscape is lacking^2–9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichiacoli^pks+ colibactin in rectal cancers¹⁰ and the importance of the SBS93 signature^11–13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations¹⁴ are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care.

Motivation: Comparison of read depths from next-generation sequencing between cancer and normal cells makes the estimation of copy number alteration (CNA) possible, even at very low coverage. However, estimating CNA from patients' tumour samples poses considerable challenges due to infiltration with normal cells and aneuploid cancer genomes. Here we provide a method that corrects contamination with normal cells and adjusts for genomes of different sizes so that the actual copy number of each region can be estimated. Results: The procedure consists of several steps. First, we identify the multi-modality of the distribution of smoothed ratios. Then we use the estimates of the mean (modes) to identify underlying ploidy and the contamination level, and finally we perform the correction. The results indicate that the method works properly to estimate genomic regions with gains and losses in a range of simulated data as well as in two datasets from lung cancer patients. It also proves a powerful tool when analysing publicly available data from two cell lines (HCC1143 and COLO829). Availability: An R package, called CNAnorm, is available at http://www.precancer.leeds.ac.uk/cnanorm or from Bioconductor. Contact:a.gusnanto@leeds.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.