Sequential screening for lung cancer in a high-risk group: randomised controlled trial: LungSEARCH: a randomised controlled trial of Surveillance using sputum and imaging for the EARly detection of lung Cancer in a High-risk group.

BACKGROUND: Low-dose computed tomography (LDCT) screening detects early-stage lung cancer and reduces mortality. We proposed a sequential approach targeted to a high-risk group as a potentially efficient screening strategy. METHODS: LungSEARCH was a national multicentre randomised trial. Current/ex-smokers with mild/moderate chronic obstructive pulmonary disease (COPD) were allocated (1:1) to have 5 years surveillance or not. Screened participants provided annual sputum samples for cytology and cytometry, and if abnormal were offered annual LDCT and autofluorescence bronchoscopy (AFB). Those with normal sputum provided annual samples. The primary end-point was the percentage of lung cancers diagnosed at stage I/II (nonsmall cell) or limited disease (small cell). RESULTS: 1568 participants were randomised during 2007-2011 from 10 UK centres. 85.2% of those screened provided an adequate baseline sputum sample. There were 42 lung cancers among 785 screened individuals and 36 lung cancers among 783 controls. 54.8% (23 out of 42) of screened individuals versus 45.2% (14 out of 31) of controls with known staging were diagnosed with early-stage disease (one-sided p=0.24). Relative risk was 1.21 (95% CI 0.75-1.95) or 0.82 (95% CI 0.52-1.31) for early-stage or advanced cancers, respectively. Overall sensitivity for sputum (in those randomised to surveillance) was low (40.5%) with a cumulative false-positive rate (FPR) of 32.8%. 55% of cancers had normal sputum results throughout. Among sputum-positive individuals who had AFB, sensitivity was 45.5% and cumulative FPR was 39.5%; the corresponding measures for those who had LDCT were 100% and 16.1%, respectively. CONCLUSIONS: Our sequential strategy, using sputum cytology/cytometry to select high-risk individuals for AFB and LDCT, did not lead to a clear stage shift and did not improve the efficiency of lung cancer screening.

The genomic road to invasion-examining the similarities and differences in the genomes of associated oral pre-cancer and cancer samples.

BACKGROUND: It is frequently assumed that pre-invasive lesions are simpler precursors of cancer and will contain a limited subset of the genomic changes seen in their associated invasive disease. Driver mutations are thought to occur early, but it is not known how many of these are present in pre-invasive lesions. These assumptions need to be tested with the increasing focus on both personalised cancer treatments and early detection methodologies. METHODS: We examined genomic copy number changes in 256 pre-invasive and invasive samples from 69 oral cancer patients. Forty-eight samples from 16 patients were further examined using exome sequencing. RESULTS: Evidence of a shared ancestor of both dysplasia and carcinoma was seen in all but one patient. One-third of dysplasias showed independent copy number events. The remainder had a copy number pattern that was similar to or simpler than that of the carcinoma. All dysplasias examined contained somatic mutations absent in the related carcinoma. Previously observed copy number changes and TP53 mutations were very frequently observed, and almost always shared between dysplasia and carcinoma. Other gene changes were more sporadic. Pathway analysis confirmed that each patient's disease developed in a different way. Examining the numbers of shared mutations and the rate of accumulation of mutations showed evidence that all samples contain a population of sub-clones, with little evidence of selective advantage of a subset of these. CONCLUSIONS: These findings suggest that most of the genomic changes driving oral cancer occur in the pre-cancerous state by way of gradual random accumulation rather than a dramatic single event.

Past and future impact of next-generation sequencing in head and neck cancer.

Progress in sequencing technology is intrinsically linked to progress in understanding cancer genomics. The purpose of this review was to discuss the development from Sanger sequencing to next-generation sequencing (NGS) technology. We highlight the technical considerations for understanding reports using NGS. We discuss the findings of studies in head and neck cancer using NGS as well as The Cancer Genome Atlas. Finally we discuss future routes for research utilizing this methodology and the potential impact of this. © 2015 Wiley Periodicals, Inc. Head Neck 38: E2395-E2402, 2016.

Elucidating drivers of oral epithelial dysplasia formation and malignant transformation to cancer using RNAseq.

Oral squamous cell carcinoma (OSCC) is a prevalent cancer with poor prognosis. Most OSCC progresses via a non-malignant stage called dysplasia. Effective treatment of dysplasia prior to potential malignant transformation is an unmet clinical need. To identify markers of early disease, we performed RNA sequencing of 19 matched HPV negative patient trios: normal oral mucosa, dysplasia and associated OSCC. We performed differential gene expression, principal component and correlated gene network analysis using these data. We found differences in the immune cell signatures present at different disease stages and were able to distinguish early events in pathogenesis, such as upregulation of many HOX genes, from later events, such as down-regulation of adherens junctions. We herein highlight novel coding and non-coding candidates for involvement in oral dysplasia development and malignant transformation, and speculate on how our findings may guide further translational research into the treatment of oral dysplasia.

Clinical and genomic analysis of a randomised phase II study evaluating anastrozole and fulvestrant in postmenopausal patients treated for large operable or locally advanced hormone-receptor-positive breast cancer.

BACKGROUND: The aim of this study was to assess the efficacy of neoadjuvant anastrozole and fulvestrant treatment of large operable or locally advanced hormone-receptor-positive breast cancer not eligible for initial breast-conserving surgery, and to identify genomic changes occurring after treatment. METHODS: One hundred and twenty post-menopausal patients were randomised to receive 1 mg anastrozole (61 patients) or 500 mg fulvestrant (59 patients) for 6 months. Genomic DNA copy number profiles were generated for a subgroup of 20 patients before and after treatment. RESULTS: A total of 108 patients were evaluable for efficacy and 118 for toxicity. The objective response rate determined by clinical palpation was 58.9% (95% CI=45.0-71.9) in the anastrozole arm and 53.8% (95% CI=39.5-67.8) in the fulvestrant arm. The breast-conserving surgery rate was 58.9% (95% CI=45.0-71.9) in the anastrozole arm and 50.0% (95% CI=35.8-64.2) in the fulvestrant arm. Pathological responses >50% occurred in 24 patients (42.9%) in the anastrozole arm and 13 (25.0%) in the fulvestrant arm. The Ki-67 score fell after treatment but there was no significant difference between the reduction in the two arms (anastrozole 16.7% (95% CI=13.3-21.0) before, 3.2% (95% CI=1.9-5.5) after, n=43; fulvestrant 17.1% (95%CI=13.1-22.5) before, 3.2% (95% CI=1.8-5.7) after, n=38) or between the reduction in Ki-67 in clinical responders and non-responders. Genomic analysis appeared to show a reduction of clonal diversity following treatment with selection of some clones with simpler copy number profiles. CONCLUSIONS: Both anastrozole and fulvestrant were effective and well-tolerated, enabling breast-conserving surgery in over 50% of patients. Clonal changes consistent with clonal selection by the treatment were seen in a subgroup of patients.

The clonal relationships between pre-cancer and cancer revealed by ultra-deep sequencing.

The study of the relationships between pre-cancer and cancer and identification of early driver mutations is becoming increasingly important as the value of molecular markers of early disease and personalised drug targets is recognized, especially now the extent of clonal heterogeneity in fully invasive disease is being realized. It has been assumed that pre-cancerous lesions exhibit a fairly passive progression to invasive disease; the degree to which they, too, are heterogeneous is unknown. We performed ultra-deep sequencing of thousands of selected mutations, together with copy number analysis, from multiple, matched pre-invasive lesions, primary tumours and metastases from five patients with oral cancer, some with multiple primary tumours presenting either synchronously or metachronously, totalling 75 samples. This allowed the clonal relationships between the samples to be observed for each patient. We expose for the first time the unexpected variety and complexity of the relationships between this group of oral dysplasias and their associated carcinomas and, ultimately, the diversity of processes by which tumours are initiated, spread and metastasize. Instead of a series of genomic precursors of their adjacent invasive disease, we have shown dysplasia to be a distinct dynamic entity, refuting the belief that pre-cancer and invasive tumours with a close spatial relationship always have linearly related genomes. We show that oral pre-cancer exhibits considerable subclonal heterogeneity in its own right, that mutational changes in pre-cancer do not predict the onset of invasion, and that the genomic pathway to invasion is neither unified nor predictable. Sequence data from this study have been deposited in the European Nucleotide Archive, Accession No. PRJEB6588.

A novel genomic signature reclassifies an oral cancer subtype.

Verrucous carcinoma of the oral cavity (OVC) is considered a subtype of classical oral squamous cell carcinoma (OSCC). Diagnosis is problematic, and additional biomarkers are needed to better stratify patients. To investigate their molecular signature, we performed low-coverage copy number (CN) sequencing on 57 OVC and exome and RNA sequencing on a subset of these and compared the data to the same OSCC parameters. CN results showed that OVC lacked any of the classical OSCC patterns such as gain of 3q and loss of 3p and demonstrated considerably fewer genomic rearrangements compared to the OSCC cohort. OVC and OSCC samples could be clearly differentiated. Exome sequencing showed that OVC samples lacked mutations in genes commonly associated with OSCC (TP53, NOTCH1, NOTCH2, CDKN2A and FAT1). RNA sequencing identified genes that were differentially expressed between the groups. In silico functional analysis showed that the mutated and differentially expressed genes in OVC samples were involved in cell adhesion and keratinocyte proliferation, while those in the OSCC cohort were enriched for cell death and apoptosis pathways. This is the largest and most detailed genomic and transcriptomic analysis yet performed on this tumour type, which, as an example of non-metastatic cancer, may shed light on the nature of metastases. These three independent investigations consistently show substantial differences between the cohorts. Taken together, they lead to the conclusion that OVC is not a subtype of OSCC, but should be classified as a distinct entity.

Stratifying tumour subtypes based on copy number alteration profiles using next-generation sequence data.

MOTIVATION: The role of personalized medicine and target treatment in the clinical management of cancer patients has become increasingly important in recent years. This has made the task of precise histological substratification of cancers crucial. Increasingly, genomic data are being seen as a valuable classifier. Specifically, copy number alteration (CNA) profiles generated by next-generation sequencing (NGS) can become a determinant for tumours subtyping. The principle purpose of this study is to devise a model with good prediction capability for the tumours histological subtypes as a function of both the patients covariates and their genome-wide CNA profiles from NGS data. RESULTS: We investigate a logistic regression for modelling tumour histological subtypes as a function of the patients' covariates and their CNA profiles, in a mixed model framework. The covariates, such as age and gender, are considered as fixed predictors and the genome-wide CNA profiles are considered as random predictors. We illustrate the application of this model in lung and oral cancer datasets, and the results indicate that the tumour histological subtypes can be modelled with a good fit. Our cross-validation indicates that the logistic regression exhibits the best prediction relative to other classification methods we considered in this study. The model also exhibits the best agreement in the prediction between smooth-segmented and circular binary-segmented CNA profiles. AVAILABILITY AND IMPLEMENTATION: An R package to run a logistic regression is available in http://www1.maths.leeds.ac.uk/~arief/R/CNALR/. CONTACT: a.gusnanto@leeds.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Using common variants to indicate cancer genes.

The catalogue of tumour-specific somatic mutations (SMs) is growing rapidly owing to the advent of next-generation sequencing. Identifying those mutations responsible for the development and progression of the disease, so-called driver mutations, will increase our understanding of carcinogenesis and provide candidates for targeted therapeutics. The phenotypic consequence(s) of driver mutations cause them to be selected for within the tumour environment, such that many approaches aimed at distinguishing drivers are based on finding significantly somatically mutated genes. Currently, these methods are designed to analyse, or be specifically applied to, nonsynonymous mutations: those that alter an encoded protein. However, growing evidence suggests the involvement of noncoding transcripts in carcinogenesis, mutations in which may also be disease-driving. We wished to test the hypothesis that common DNA variation rates within humans can be used as a baseline from which to score the rate of SMs, irrespective of coding capacity. We preliminarily tested this by applying it to a dataset of 159,498 SMs and using the results to rank genes. This resulted in significant enrichment of known cancer genes, indicating that the approach has merit. As additional data from cancer sequencing studies are made publicly available, this approach can be refined and applied to specific cancer subtypes. We named this preliminary version of our approach PRISMAD (polymorphism rates indicate somatic mutations as drivers) and have made it publicly accessible, with scripts, via a link at www.precancer.leeds.ac.uk/software-and-datasets.