High-resolution genomic profiles of human lung cancer.
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ABSTRACT:
SUBMITTER: Tonon G
PROVIDER: S-EPMC1160520 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A BAC-array platform for comparative genomic hybridization was constructed from a library of 32,433 clones providing complete genome coverage, and evaluated by screening for DNA copy number changes in 11 breast cell lines (BT474, MCF7, HCC1937, SK-BR-3, L56Br-C1, ZR-75-1, MCF10A, JIMT1, MDA-MB-231, MDA-MB-361 and HCC2218). These were also characterized by gene expression analysis and found to represent all five recently described breast cancer subtypes using the ‘intrinsic gene set’ and centroid correlation. Three cell lines, HCC1937 and L56BrC1 derived from BRCA1 mutation carriers and MDA-MB-231, were of basal-like subtype and characterized by a high frequency of low-level gains and losses of typical pattern, including limited deletions on 5q. Four estrogen receptor positive cell lines were of luminal A subtype and characterized by a different pattern of aberrations and high-level amplifications, including ERBB2 and other 17q amplicons in BT474 and MDA-MB-361. SK-BR-3 cells, characterized by a complex genome including ERBB2 amplification, massive high-level amplifications on 8q and a homozygous deletion of CDH1 at 16q22, had an expression signature closest to luminal B subtype. The effects of gene amplifications were verified by gene expression analysis to distinguish targeted genes from silent amplicon passengers. JIMT1, derived from an ERBB2 amplified trastuzumab resistant tumor, was of the ERBB2 subtype. Homozygous deletions included other known targets such as PTEN (HCC1937) and CDKN2A (MDA-MB-231, MCF10A), but also new candidate suppressor genes such as FUSSEL18 (HCC1937) and WDR11 (L56Br-C1) as well as regions without known genes. The tiling BAC arrays constitute a powerful tool for high-resolution genomic profiling suitable for cancer research and clinical diagnostics. Keywords: comparative genomic hybridization
2007-04-01 | GSE6746 | GEO
Project description:We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73?ex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.
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Project description:During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.
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Project description:BackgroundThe incidence of human papillomavirus-associated vulval neoplasia is increasing worldwide; yet the associated genetic changes remain poorly understood.MethodsWe have used single-nucleotide polymorphism microarray analysis to perform the first high-resolution investigation of genome-wide allelic imbalance in vulval neoplasia. Our sample series comprised 21 high-grade vulval intraepithelial neoplasia and 6 vulval squamous cell carcinomas, with paired non-lesional samples used to adjust for normal copy number variation.ResultsOverall the most common recurrent aberrations were gains at 1p and 20, with the most frequent deletions observed at 2q, 3p and 10. Copy-neutral loss of heterozygosity at 6p was a recurrent event in vulval intraepithelial neoplasia. The pattern of genetic alterations differed from the characteristic changes we previously identified in cutaneous squamous cell carcinomas. Vulval neoplasia samples did not exhibit gain at 5p, a frequent recurrent aberration in a series of cervical tumours analysed elsewhere using an identical protocol.ConclusionThis series of 27 vulval samples comprises the largest systematic genome-wide analysis of vulval neoplasia performed to date. Despite shared papillomavirus status and regional proximity, our data suggest that the frequency of certain genetic alterations may differ in vulval and cervical tumours.
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Project description:We present the Human Muscle Gene Map (HMGM), the first comprehensive and updated high-resolution expression map of human skeletal muscle. The 1078 entries of the map were obtained by merging data retrieved from UniGene with the RH mapping information on 46 novel muscle transcripts, which showed no similarity to any known sequence. In the map, distances are expressed in megabase pairs. About one-quarter of the map entries represents putative novel genes. Genes known to be specifically expressed in muscle account for <4% of the total. The genomic distribution of the map entries confirmed the previous finding that muscle genes are selectively concentrated in chromosomes 17, 19, and X. Five chromosomal regions are suspected to have a significant excess of muscle genes. Present data support the hypothesis that the biochemical and functional properties of differentiated muscle cells may result from the transcription of a very limited number of muscle-specific genes along with the activity of a large number of genes, shared with other tissues, but showing different levels of expression in muscle. [The sequence data described in this paper have been submitted to the EMBL data library under accession nos. F23198-F23242.]
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Project description:IntroductionGenomic aberrations in the form of subchromosomal DNA copy number changes are a hallmark of epithelial cancers, including breast cancer. The goal of the present study was to analyze such aberrations in breast cancer at high resolution.MethodsWe employed high-resolution array comparative genomic hybridization with 4,134 bacterial artificial chromosomes that cover the genome at 0.9 megabase resolution to analyze 47 primary breast tumors and 18 breast cancer cell lines.ResultsCommon amplicons included 8q24.3 (amplified in 79% of tumors, with 5/47 exhibiting high level amplification), 1q32.1 and 16p13.3 (amplified in 66% and 57% of tumors, respectively). Moreover, we found several positive correlations between specific amplicons from different chromosomes, suggesting the existence of cooperating genetic loci. Queried by gene, the most frequently amplified kinase was PTK2 (79% of tumors), whereas the most frequently lost kinase was PTK2B (hemizygous loss in 34% of tumors). Amplification of ERBB2 as measured by comparative genomic hybridization (CGH) correlated closely with ERBB2 DNA and RNA levels measured by quantitative PCR as well as with ERBB2 protein levels. The overall frequency of recurrent losses was lower, with no region lost in more than 50% of tumors; the most frequently lost tumor suppressor gene was RB1 (hemizygous loss in 26% of tumors). Finally, we find that specific copy number changes in cell lines closely mimicked those in primary tumors, with an overall Pearson correlation coefficient of 0.843 for gains and 0.734 for losses.ConclusionHigh resolution CGH analysis of breast cancer reveals several regions where DNA copy number is commonly gained or lost, that non-random correlations between specific amplicons exist, and that specific genetic alterations are maintained in breast cancer cell lines despite repeat passage in tissue culture. These observations suggest that genes within these regions are critical to the malignant phenotype and may thus serve as future therapeutic targets.
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Project description:Circulating tumor cells and disseminated tumor cells (DTCs) are of great interest because they provide a minimally invasive window for assessing aspects of cancer biology, including tumor heterogeneity, a means to discover biomarkers of disease behavior, and a way to identify and prioritize therapeutic targets in the emerging era of precision oncology. However, the rarity of circulating tumor cells and DTCs poses a substantial challenge to the consistent success in analyzing their molecular features, including genomic aberrations. Herein, we describe optimized and robust methods to reproducibly detect genomic copy number alterations in samples of 2 to 40 cells after whole-genome amplification with the use of a high-resolution single-nuclear polymorphism-array platform and refined computational algorithms. We have determined the limit of detection for heterogeneity within a sample as 50% and also demonstrated success in analyzing single cells. We validated the genes in genomic regions that are frequently amplified or deleted by real-time quantitative PCR and nCounter copy number quantification. We further applied these methods to DTCs isolated from individuals with advanced prostate cancer to confirm their highly aberrant nature. We compared copy number alterations of DTCs with matched metastatic tumors isolated from the same individual to gain biological insight. These developments provide high-resolution genomic profiling of single and rare cell populations and should be applicable to a wide-range of sample sources.
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Project description:Lung cancer is the leading cause of human cancer mortality due to the lack of early diagnosis technology. The low-dose computed tomography scan (LDCT) is one of the main techniques to screen cancers. However, LDCT still has a risk of radiation exposure and it is not suitable for the general public. In this study, plasma metabolic profiles of lung cancer were performed using a comprehensive metabolomic method with different liquid chromatography methods coupled with a Q-Exactive high-resolution mass spectrometer. Metabolites with different polarities (amino acids, fatty acids, and acylcarnitines) can be detected and identified as differential metabolites of lung cancer in small volumes of plasma. Logistic regression models were further developed to identify cancer stages and types using those significant biomarkers. Using the Variable Importance in Projection (VIP) and the area under the curve (AUC) scores, we have successfully identified the top 5, 10, and 20 metabolites that can be used to differentiate lung cancer stages and types. The discrimination accuracy and AUC score can be as high as 0.829 and 0.869 using the five most significant metabolites. This study demonstrated that using 5 + metabolites (Palmitic acid, Heptadecanoic acid, 4-Oxoproline, Tridecanoic acid, Ornithine, and etc.) has the potential for early lung cancer screening. This finding is useful for transferring the diagnostic technology onto a point-of-care device for lung cancer diagnosis and prognosis.
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