Analysis of 10,478 cancer genomes identifies candidate driver genes and opportunities for precision oncology.

Tumor genomic profiling is increasingly seen as a prerequisite to guide the treatment of patients with cancer. To explore the value of whole-genome sequencing (WGS) in broadening the scope of cancers potentially amenable to a precision therapy, we analysed whole-genome sequencing data on 10,478 patients spanning 35 cancer types recruited to the UK 100,000 Genomes Project. We identified 330 candidate driver genes, including 74 that are new to any cancer. We estimate that approximately 55% of patients studied harbor at least one clinically relevant mutation, predicting either sensitivity or resistance to certain treatments or clinical trial eligibility. By performing computational chemogenomic analysis of cancer mutations we identify additional targets for compounds that represent attractive candidates for future clinical trials. This study represents one of the most comprehensive efforts thus far to identify cancer driver genes in the real world setting and assess their impact on informing precision oncology.

T-cell receptor determinants of response to chemoradiation in locally-advanced HPV16-driven malignancies.

Background: The effect of chemoradiation on the anti-cancer immune response is being increasingly acknowledged; however, its clinical implications in treatment responses are yet to be fully understood. Human papillomavirus (HPV)-driven malignancies express viral oncogenic proteins which may serve as tumor-specific antigens and represent ideal candidates for monitoring the peripheral T-cell receptor (TCR) changes secondary to chemoradiotherapy (CRT). Methods: We performed intra-tumoral and pre- and post-treatment peripheral TCR sequencing in a cohort of patients with locally-advanced HPV16-positive cancers treated with CRT. An in silico computational pipeline was used to cluster TCR repertoire based on epitope-specificity and to predict affinity between these clusters and HPV16-derived epitopes. Results: Intra-tumoral repertoire diversity, intra-tumoral and post-treatment peripheral CDR3ß similarity clustering were predictive of response. In responders, CRT triggered an increase peripheral TCR clonality and clonal relatedness. Post-treatment expansion of baseline peripheral dominant TCRs was associated with response. Responders showed more baseline clustered structures of TCRs maintained post-treatment and displayed significantly more maintained clustered structures. When applying clustering by TCR-specificity methods, responders displayed a higher proportion of intra-tumoral TCRs predicted to recognise HPV16 peptides. Conclusions: Baseline TCR characteristics and changes in the peripheral T-cell clones triggered by CRT are associated with treatment outcome. Maintenance and boosting of pre-existing clonotypes are key elements of an effective anti-cancer immune response driven by CRT, supporting a paradigm in which the immune system plays a central role in the success of CRT in current standard-of-care protocols.

Clonality of erythromycin resistance in Francisella tularensis.

OBJECTIVES: We analysed diverse strains of Francisella tularensis subsp. holarctica to assess if its division into biovars I and II is associated with specific mutations previously linked to erythromycin resistance and to determine the distribution of this resistance trait across this subspecies. METHODS: Three-hundred and fourteen F. tularensis subsp. holarctica strains were tested for erythromycin susceptibility and whole-genome sequences for these strains were examined for SNPs in genes previously associated with erythromycin resistance. Each strain was assigned to a global phylogenetic framework using genome-wide canonical SNPs. The contribution of a specific SNP to erythromycin resistance was examined using allelic exchange. The geographical distribution of erythromycin-resistant F. tularensis strains was further investigated by literature search. RESULTS: There was a perfect correlation between biovar II strains (erythromycin resistance) and the phylogenetic group B.12. Only B.12 strains had an A → C SNP at position 2059 in the three copies of the rrl gene. Introducing 2059C into an rrl gene of an erythromycin-susceptible F. tularensis strain resulted in resistance. An additional 1144 erythromycin-resistant strains were identified from the scientific literature, all of them from Eurasia. CONCLUSIONS: Erythromycin resistance in F. tularensis is caused by an A2059C rrl gene mutation, which exhibits a strictly clonal inheritance pattern found only in phylogenetic group B.12. This group is an extremely successful clone, representing the most common type of F. tularensis throughout Eurasia.

Long-range dispersal moved Francisella tularensis into Western Europe from the East.

For many infections transmitting to humans from reservoirs in nature, disease dispersal patterns over space and time are largely unknown. Here, a reversed genomics approach helped us understand disease dispersal and yielded insight into evolution and biological properties of Francisella tularensis, the bacterium causing tularemia. We whole-genome sequenced 67 strains and characterized by single-nucleotide polymorphism assays 138 strains, collected from individuals infected 1947-2012 across Western Europe. We used the data for phylogenetic, population genetic and geographical network analyses. All strains (n=205) belonged to a monophyletic population of recent ancestry not found outside Western Europe. Most strains (n=195) throughout the study area were assigned to a star-like phylogenetic pattern indicating that colonization of Western Europe occurred via clonal expansion. In the East of the study area, strains were more diverse, consistent with a founder population spreading from east to west. The relationship of genetic and geographic distance within the F. tularensis population was complex and indicated multiple long-distance dispersal events. Mutation rate estimates based on year of isolation indicated null rates; in outbreak hotspots only, there was a rate of 0.4 mutations/genome/year. Patterns of nucleotide substitution showed marked AT mutational bias suggestive of genetic drift. These results demonstrate that tularemia has moved from east to west in Europe and that F. tularensis has a biology characterized by long-range geographical dispersal events and mostly slow, but variable, replication rates. The results indicate that mutation-driven evolution, a resting survival phase, genetic drift and long-distance geographical dispersal events have interacted to generate genetic diversity within this species.

Complete Genome Sequence of Francisella guangzhouensis Strain 08HL01032T, Isolated from Air-Conditioning Systems in China.

We present the complete genome sequence of Francisella guangzhouensis strain 08HL01032(T), which consists of one chromosome (1,658,482 bp) and one plasmid (3,045 bp) with G+C contents of 32.0% and 28.7%, respectively.

Complete Genome Sequence of Francisella endociliophora Strain FSC1006, Isolated from a Laboratory Culture of the Marine Ciliate Euplotes raikovi.

A strain of Francisella endociliophora was isolated from a laboratory culture of the marine ciliate Euplotes raikovi. Here, we report the complete genome sequence of the bacterial strain FSC1006 (Francisella Strain Collection, Swedish Defence Research Agency, Umeå, Sweden).

An outbreak of respiratory tularemia caused by diverse clones of Francisella tularensis.

BACKGROUND: The bacterium Francisella tularensis is recognized for its virulence, infectivity, genetic homogeneity, and potential as a bioterrorism agent. Outbreaks of respiratory tularemia, caused by inhalation of this bacterium, are poorly understood. Such outbreaks are exceedingly rare, and F. tularensis is seldom recovered from clinical specimens. METHODS: A localized outbreak of tularemia in Sweden was investigated. Sixty-seven humans contracted laboratory-verified respiratory tularemia. F. tularensis subspecies holarctica was isolated from the blood or pleural fluid of 10 individuals from July to September 2010. Using whole-genome sequencing and analysis of single-nucleotide polymorphisms (SNPs), outbreak isolates were compared with 110 archived global isolates. RESULTS: There were 757 SNPs among the genomes of the 10 outbreak isolates and the 25 most closely related archival isolates (all from Sweden/Finland). Whole genomes of outbreak isolates were >99.9% similar at the nucleotide level and clustered into 3 distinct genetic clades. Unexpectedly, high-sequence similarity grouped some outbreak and archival isolates that originated from patients from different geographic regions and up to 10 years apart. Outbreak and archival genomes frequently differed by only 1-3 of 1 585 229 examined nucleotides. CONCLUSIONS: The outbreak was caused by diverse clones of F. tularensis that occurred concomitantly, were widespread, and apparently persisted in the environment. Multiple independent acquisitions of F. tularensis from the environment over a short time period suggest that natural outbreaks of respiratory tularemia are triggered by environmental cues. The findings additionally caution against interpreting genome sequence identity for this pathogen as proof of a direct epidemiological link.

CanSNPer: a hierarchical genotype classifier of clonal pathogens.

SUMMARY: Advances in typing methodologies have recently reformed the field of molecular epidemiology of pathogens. The falling cost of sequencing technologies is creating a deluge of whole genome sequencing data that burdens bioinformatics resources and tool development. In particular, single nucleotide polymorphisms in core genomes of pathogens are recognized as the most important markers for inferring genetic relationships because they are evolutionarily stable and amenable to high-throughput detection methods. Sequence data will provide an excellent opportunity to extend our understanding of infectious disease when the challenge of extracting knowledge from available sequence resources is met. Here, we present an efficient and user-friendly genotype classification pipeline, CanSNPer, based on an easily expandable database of predefined canonical single nucleotide polymorphisms. AVAILABILITY AND IMPLEMENTATION: All documentation and Python-based source code for the CanSNPer are freely available at http://github.com/adrlar/CanSNPer.