Dataset Information

EGAS00001000837-sc-20171218 - samples

ABSTRACT: Background: Lung carcinoma-in-situ (CIS) lesions are the pre-invasive precursor to lung squamous cell carcinoma. However, only half progress to invasive cancer in three years, while a third spontaneously regress. Whether modern molecular profiling techniques can identify those pre-invasive lesions that will subsequently progress and distinguish them from those that will regress is unknown. Methods: Progressive and regressive CIS lesions were laser-captured and their genome, epigenome and transcriptome interrogated. We analysed 83 progressive lesions, 41 regressive and 33 normal epithelial control samples. DNA methylation and gene expression profiles were further validated using publicly available lung cancer data. Results: Somatic mutation burden was higher in progressive lesions than regressive CIS lesions, across base substitutions, rearrangements, and copy number changes. Driver mutations were present in both progressive and regressive CIS lesions, but were more numerous in progressive cases. Progressive and regressive CIS lesions had distinct epigenomic and transcriptional profiles, with a strong chromosomal instability signature. Gene expression, methylation and copy number profiles can all predict accurately which CIS lesions will progress to lung cancer. Conclusion: Pre-invasive CIS lesions that will subsequently progress to invasive lung cancer can be distinguished from those that will regress using molecular profiling. Progression is associated with a strong chromosomal instability signature. These findings inform the development of novel therapeutic targets.

PROVIDER: EGAD00001003883 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Similar Datasets

Project description:Cervical cancer develops from pre-cancerous high-grade cervical intraepithelial neoplasia (CIN) lesions harbouring a transforming infection with high-risk human papillomavirus (hrHPV), which is characterised by p16INK4a overexpression. Since it takes one or more decades for these pre-cancerous lesions to progress to invasive squamous cell carcinomas (SCCs), it is obvious that they are heterogeneous in terms of duration of existence and progression risk. We performed array-based comparative genomic hybridisation (array CGH) of 46 p16INK4a immuno-positive CIN2/3 lesions to determine whether this heterogeneity is reflected in their chromosomal profiles. Chromosomal profiles of CIN2/3 lesions were related to those of invasive cervical squamous cell carcinomas (SCCs) and promoter methylation of the CADM1 gene, a tumour suppressor gene known to be functionally involved in the tumorigenic phenotype of cervical cancer cells. Frequent alterations found in CIN2/3 lesions included gains located at chromosome 1, 3, 7 and 20 and losses located at 4, 11, 16, 17 and 19. Unsupervised hierarchical clustering identified two subsets of CIN2/3 lesions, chromosomal profiles of one of which closely resembled invasive SCCs. Gains of 1, 3q and 20 were characteristic for CIN2/3 lesions with chromosomal signatures resembling carcinomas. In addition, dense promoter methylation of the CADM1 gene was significantly more frequent in these CIN2/3 lesions (p=0.004). No chromosomal alterations were detected in one p16INK4a positive and five p16INK4a negative CIN1 lesions. These findings suggest that biomarkers associated with gains at chromosomes 1, 3q and 20 are potential hallmarks of advanced p16INK4a positive CIN2/3 lesions with a high short-term risk of progression. Genomic DNA of 46 high-grade cervical lesions was hybridised to 5K CGH BAC microarrays (5K) produced at the Microarray facility of the VU Medical Center. In total 4632 BAC clones with known chromosomal location were spotted in triplicate, which included the 1Mb resolution Sanger BAC clone set and a subset of clones from the Children’s Hospital Oakland Research Institute (CHORI). All samples were labelled with Cy3 and hybridised together with a pool of normal male reference DNA labelled with Cy5. Hybridisations were essentially performed as described by Snijders et al (Nature Genetics 2001). Both pre-hybridisation and hybridisation were performed in a hybridisation station (HybStation12 – Perkin Elmer Life Sciences). Hybridised arrays were scanned using a G2505B scanner (Agilent, Wilmington, DE, USA). Spots were quantified using ImaGene 5.6.1 software (BioDiscovery Ltd, Marina del Rey, CA, USA) with default settings for the flagging of bad quality spots. Genomic DNA of 6 CIN1 lesions was hybridised on CGH oligo microarrays (44K) produced by Agilent following the manufacturer’s protocol against the same normal reference pool. Hybridised arrays were scanned using the same scanner (G2505B, Agilent). Quantification of these arrays was done using Feature Extraction software version 9.5.1 (Agilent).

Dataset Information

EGAS00001000837-sc-20171218 - samples

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets