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Background and AimsThe microbiome has long been suspected of a role in colorectal cancer (CRC) tumorigenesis. The mutational signature SBS88 mechanistically links CRC development with the strain ofEscherichia coliharboring thepksisland that produces the genotoxin colibactin, but the genomic, pathological and survival characteristics associated with SBS88-positive tumors are unknown.MethodsSBS88-positive CRCs were identified from targeted sequencing data from 5,292 CRCs from 17 studies and tested for their association with clinico-pathological features, oncogenic pathways, genomic characteristics and survival.ResultsIn total, 7.5% (398/5,292) of the CRCs were SBS88-positive, of which 98.7% (392/398) were microsatellite stable/microsatellite instability low (MSS/MSI-L), compared with 80% (3916/4894) of SBS88 negative tumors (p=1.5×10-28). Analysis of MSS/MSI-L CRCs demonstrated that SBS88 positive CRCs were associated with the distal colon (OR=1.84, 95% CI=1.40-2.42, p=1×10-5) and rectum (OR=1.90, 95% CI=1.44-2.51, p=6×10-6) tumor sites compared with the proximal colon. The top seven recurrent somatic mutations associated with SBS88-positive CRCs demonstrated mutational contexts associated with colibactin-induced DNA damage, the strongest of which was theAPC:c.835-8A>G mutation (OR=65.5, 95%CI=39.0-110.0, p=3×10-80). Large copy number alterations (CNAs) including CNA loss on 14q and gains on 13q, 16q and 20p were significantly enriched in SBS88- positive CRCs. SBS88-positive CRCs were associated with better CRC-specific survival (p=0.007; hazard ratio of 0.69, 95% CI=0.52-0.90) when stratified by age, sex, study, and by stage.ConclusionSBS88-positivity, a biomarker of colibactin-induced DNA damage, can identify a novel subtype of CRC characterized by recurrent somatic mutations, copy number alterations and better survival. These findings provide new insights for treatment and prevention strategies for this subtype of CRC.

The International Cancer Genome Consortium (ICGC)’s Pan-Cancer Analysis of Whole Genomes (PCAWG) project aimed to categorize somatic and germline variations in both coding and non-coding regions in over 2,800 cancer patients. To provide this dataset to the research working groups for downstream analysis, the PCAWG Technical Working Group marshalled ~800TB of sequencing data from distributed geographical locations; developed portable software for uniform alignment, variant calling, artifact filtering and variant merging; performed the analysis in a geographically and technologically disparate collection of compute environments; and disseminated high-quality validated consensus variants to the working groups. The PCAWG dataset has been mirrored to multiple repositories and can be located using the ICGC Data Portal. The PCAWG workflows are also available as Docker images through Dockstore enabling researchers to replicate our analysis on their own data.

In humans, most recombination events occur in a small fraction of the genome. These hotspots of recombination show considerable variation in intensity and/or location across species and, potentially, across human populations. On a larger scale, the patterns of recombination rates have been mostly investigated in individuals of European ancestry, and it remains unknown whether the results obtained can be directly applied to other human populations. Here, we investigate this question using genome-wide polymorphism data. We show that population recombination rates recapitulate a large part of the genetic map information, regardless of the population considered. We also show that the ratio of the population recombination rate estimate of two populations is overall constant along the chromosomes. These two observations support the hypothesis that large-scale recombination patterns are conserved across human populations. Local deviations from the overall pattern of conservation of the recombination rates can be used to select candidate regions with large polymorphic inversions or under local selection.

Control genes, commonly defined as genes that are ubiquitously expressed at stable levels in different biological contexts, have been used to standardize quantitative expression studies for more than 25 yr. We analyzed a group of large mammalian microarray datasets including the NCI60 cancer cell line panel, a leukemia tumor panel, and a phorbol ester induction time course as well as human and mouse tissue panels. Twelve housekeeping genes commonly used as controls in classical expression studies (including GAPD, ACTB, B2M, TUBA, G6PD, LDHA, and HPRT) show considerable variability of expression both within and across microarray datasets. Although we can identify genes with lower variability within individual datasets by heuristic filtering, such genes invariably show different expression levels when compared across other microarray datasets. We confirm these results with an analysis of variance in a controlled mouse dataset, showing the extent of variability in gene expression across tissues. The results show the problems inherent in the classical use of control genes in estimating gene expression levels in different mammalian cell contexts, and highlight the importance of controlled study design in the construction of microarray experiments.[Supplemental material available online athttp://genome.mcgill.ca/∼pdlee/control_genes and andhttp://www.genome.org.]

We have investigated previously the utility of oligonucleotide expression microarray technology in an analysis of four spontaneously transformed epithelial ovarian cancer (EOC) cell lines, TOV-21G, TOV-81D, OV-90, and TOV-112D. Here, we examine the expression of 290 expressed sequence tags (ESTs) that map to human chromosome 3 in a primary culture derived from normal ovarian surface epithelium (NOSE), NOV-31, and the four spontaneously transformed EOC cell lines. One of these cell lines, OV-90, harbors a deletion of an entire chromosome 3p arm. Whereas the most aggressive cell lines (OV-90, TOV-112D, and TOV-21G) exhibited the highest levels of expression, assessed by the mean of expression values of all ESTs, OV-90 showed the lowest mean of expression of ESTs that map to the 3p arm in comparison with TOV-112D and TOV-21G. This difference in expression profile of 3p ESTs in OV-90 is also reflected in the ratio of expression of ESTs on 3p versus the 3q arm and in that the expression values of ESTs that map to 3p were more often lower than higher in OV-90 in two-way comparisons with NOV-31, TOV-21G, and TOV-112D. The loss of a 3p arm does not affect the pattern of differential expression in analyses based on the range of numeric expression values of each EST or fold differences in expression for each EST in comparison with NOV-31. However, 25 differentially expressed ESTs were identified on the basis of threefold differences in expression values between NOV-31 and any EOC cell line; and six of these ESTs were differentially expressed uniquely in OV-90. The investigation of these ESTs could facilitate the identification of novel chromosome 3 genes implicated in ovarian tumorigenesis.

The emergence of next generation DNA sequencing technology is enabling high-resolution cancer genome analysis. Large-scale projects like the International Cancer Genome Consortium (ICGC) are systematically scanning cancer genomes to identify recurrent somatic mutations. Second generation DNA sequencing, however, is still an evolving technology and procedures, both experimental and analytical, are constantly changing. Thus the research community is still defining a set of best practices for cancer genome data analysis, with no single protocol emerging to fulfil this role. Here we describe an extensive benchmark exercise to identify and resolve issues of somatic mutation calling. Whole genome sequence datasets comprising tumor-normal pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, were shared within the ICGC and submissions of somatic mutation calls were compared to verified mutations and to each other. Varying strategies to call mutations, incomplete awareness of sources of artefacts, and even lack of agreement on what constitutes an artefact or real mutation manifested in widely varying mutation call rates and somewhat low concordance among submissions. We conclude that somatic mutation calling remains an unsolved problem. However, we have identified many issues that are easy to remedy that are presented here. Our study highlights critical issues that need to be addressed before this valuable technology can be routinely used to inform clinical decision-making.

Cat eye syndrome (CES) is typically associated with a supernumerary bisatellited marker chromosome derived from human chromosome 22pter to 22q11.2. The region of 22q duplicated in the typical CES marker chromosome extends between the centromere and locus D22S36. We have constructed a long-range restriction map of this region using pulsed-field gel electrophoresis and probes to 10 loci (11 probes). The map covers -3.6 Mb. We have also used 15 loci to construct a yeast artificial chromosome contig, which encompasses about half of the region critical to the production of the CES phenotype (centromere to D22S57). Thus, the CES critical region has been mapped and a substantial portion of it cloned in preparation for the isolation of genes in this region.