Genomic evidence of pre-invasive clonal expansion, dispersal and progression in bronchial dysplasia

The term ‘field cancerization’ is used to describe an epithelial surface that has a propensity to develop cancerous lesions, and in the case of the aerodigestive tract this is often as a result of chronic exposure to carcinogens in cigarette smoke 1, 2. The clinical endpoint is the development of multiple tumours, either simultaneously or sequentially in the same epithelial surface. The mechanisms underlying this process remain unclear; one possible explanation is that the epithelium is colonized by a clonal population of cells that are at increased risk of progression to cancer. We now address this possibility in a short case series, using individual genomic events as molecular biomarkers of clonality. In squamous lung cancer the most common genomic aberration is 3q amplification. We use a digital PCR technique to assess the clonal relationships between multiple biopsies in a longitudinal bronchoscopic study, using amplicon boundaries as markers of clonality. We demonstrate that clonality can readily be defined by these analyses and confirm that field cancerization occurs at a pre-invasive stage and that pre-invasive lesions and subsequent cancers are clonally related. We show that while the amplicon boundaries can be shared between different biopsies, the degree of 3q amplification and the internal structure of the 3q amplicon varies from lesion to lesion. Finally, in this small cohort, the degree of 3q amplification corresponds to clinical progression. Copyright © 2011 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd

IMSA: Integrated metagenomic sequence analysis for identification of exogenous reads in a host genomic background

Metagenomics, the study of microbial genomes within diverse environments, is a rapidly developing field. The identification of microbial sequences within a host organism enables the study of human intestinal, respiratory, and skin microbiota, and has allowed the identification of novel viruses in diseases such as Merkel cell carcinoma. There are few publicly available tools for metagenomic high throughput sequence analysis. We present Integrated Metagenomic Sequence Analysis (IMSA), a flexible, fast, and robust computational analysis pipeline that is available for public use. IMSA takes input sequence from high throughput datasets and uses a user-defined host database to filter out host sequence. IMSA then aligns the filtered reads to a user-defined universal database to characterize exogenous reads within the host background. IMSA assigns a score to each node of the taxonomy based on read frequency, and can output this as a taxonomy report suitable for cluster analysis or as a taxonomy map (TaxMap). IMSA also outputs the specific sequence reads assigned to a taxon of interest for downstream analysis. We demonstrate the use of IMSA to detect pathogens and normal flora within sequence data from a primary human cervical cancer carrying HPV16, a primary human cutaneous squamous cell carcinoma carrying HPV 16, the CaSki cell line carrying HPV16, and the HeLa cell line carrying HPV18

An integrated inspection of the somatic mutations in a lung squamous cell carcinoma using next-generation sequencing

Squamous cell carcinoma (SCC) of the lung kills over 350,000 people annually worldwide, and is the main lung cancer histotype with no targeted treatments. High-coverage whole-genome sequencing of the other main subtypes, small-cell and adenocarcinoma, gave insights into carcinogenic mechanisms and disease etiology. The genomic complexity within the lung SCC subtype, as revealed by The Cancer Genome Atlas, means this subtype is likely to benefit from a more integrated approach in which the transcriptional consequences of somatic mutations are simultaneously inspected. Here we present such an approach: the integrated analysis of deep sequencing data from both the whole genome and whole transcriptome (coding and non-coding) of LUDLU-1, a SCC lung cell line. Our results show that LUDLU-1 lacks the mutational signature that has been previously associated with tobacco exposure in other lung cancer subtypes, and suggests that DNA-repair efficiency is adversely affected; LUDLU-1 contains somatic mutations in TP53 and BRCA2, allelic imbalance in the expression of two cancer-associated BRCA1 germline polymorphisms and reduced transcription of a potentially endogenous PARP2 inhibitor. Functional assays were performed and compared with a control lung cancer cell line. LUDLU-1 did not exhibit radiosensitisation or an increase in sensitivity to PARP inhibitors. However, LUDLU-1 did exhibit small but significant differences with respect to cisplatin sensitivity. Our research shows how integrated analyses of high-throughput data can generate hypotheses to be tested in the lab

Progressive 3q Amplification Consistently Targets SOX2 in Preinvasive Squamous Lung Cancer

Rationale: Amplification of distal 3q is the most common genomic aberration in squamous lung cancer (SQC). SQC develops in a multistage progression from normal bronchial epithelium through dysplasia to invasive disease. Identifying the key driver events in the early pathogenesis of SQC will facilitate the search for predictive molecular biomarkers and the identification of novel molecular targets for chemoprevention and therapeutic strategies. For technical reasons, previous attempts to analyze 3q amplification in preinvasive lesions have focused on small numbers of predetermined candidate loci rather than an unbiased survey of copy-number variation

Comparison of filtering databases.

<p>NCBI’s RefSeq database includes viral sequence mis-annotated as human; using this as a host filter results in loss of HPV16 reads (black). Filtering against the human genome (hg19) alone allows detection of these reads (gray).</p

IMSA results on CaSki positive control dataset.

<p>A) Bar chart showing the number of reads in the dataset at each step of the IMSA pipeline. B) Breakdown of the division of reads left after host filtering, as determined by BLAST to NCBI’s nt database. C) The number of reads that align within each 100 base pair bin along the HPV16 genome in the unfiltered dataset compared to the IMSA filtered dataset.</p

TaxMap of viral reads in a combined HeLa and CaSki dataset.

<p>IMSA is able to accurately identify both alphapapillomaviridae species 7 (HPV18) and species 9 (HPV16) in the merged dataset.This TaxMap has been filtered to only show nodes with a score above 50.</p

TaxMap of bacterial reads in a primary cutaneous SCC.

<p>TaxMap of shows the breakdown of bacterial read scores at the kingdom, family, genus and species levels. This TaxMap has been filtered to only show nodes with a score above 50.</p