Differential gene alteration among hepatoma cell lines demonstrated by cDNA microarray-based comparative genomic hybridization

We assayed chromosomal abnormalities in hepatoma cell lines using the microarray-based comparative genomic hybridization (array-CGH) method and investigated the relationship between genomic copy number alterations and expression profiles in these hepatoma cell lines. We modified a cDNA array-CGH assay to compare genomic DNAs from seven hepatoma cell lines, as well as DNA from two non-hepatoma cell lines and from normal cells. The mRNA expression of each sample was assayed in parallel by cDNA microarray. We identified small amplified or deleted chromosomal regions, as well as alterations in DNA copy number not previously described. We predominantly found alterations of apoptosis-related genes in Hep3B and HepG2, cell adhesion and receptor molecules in HLE, and cytokine-related genes in PLC/PRF/5. About 40% of the genes showing amplification or loss showed altered levels of mRNA (p < 0.05). Hierarchical clustering analysis showed that the expression of these genes allows differentiation between alpha-fetoprotein (AFP)-producing and AFP-negative cell lines. cDNA array-CGH is a sensitive method that can be used to detect alterations in genomic copy number in tumor cells. Differences in DNA copy alterations between AFP-producing and AFP-negative cells may lead to differential gene expression and may be related to the phenotype of these cells.     

Determining Frequent Patterns of Copy Number Alterations in Cancer

Cancer progression is often driven by an accumulation of genetic changes but also accompanied by increasing genomic instability. These processes lead to a complicated landscape of copy number alterations (CNAs) within individual tumors and great diversity across tumor samples. High resolution array-based comparative genomic hybridization (aCGH) is being used to profile CNAs of ever larger tumor collections, and better computational methods for processing these data sets and identifying potential driver CNAs are needed. Typical studies of aCGH data sets take a pipeline approach, starting with segmentation of profiles, calls of gains and losses, and finally determination of frequent CNAs across samples. A drawback of pipelines is that choices at each step may produce different results, and biases are propagated forward. We present a mathematically robust new method that exploits probe-level correlations in aCGH data to discover subsets of samples that display common CNAs. Our algorithm is related to recent work on maximum-margin clustering. It does not require pre-segmentation of the data and also provides grouping of recurrent CNAs into clusters. We tested our approach on a large cohort of glioblastoma aCGH samples from The Cancer Genome Atlas and recovered almost all CNAs reported in the initial study. We also found additional significant CNAs missed by the original analysis but supported by earlier studies, and we identified significant correlations between CNAs.     

Oligonucleotide Arrays vs. Metaphase-Comparative Genomic Hybridisation and BAC Arrays for Single-Cell Analysis: First Applications to Preimplantation Genetic Diagnosis for Robertsonian Translocation Carriers

Comprehensive chromosome analysis techniques such as metaphase-Comparative Genomic Hybridisation (CGH) and array-CGH are available for single-cell analysis. However, while metaphase-CGH and BAC array-CGH have been widely used for Preimplantation Genetic Diagnosis, oligonucleotide array-CGH has not been used in an extensive way. A comparison between oligonucleotide array-CGH and metaphase-CGH has been performed analysing 15 single fibroblasts from aneuploid cell-lines and 18 single blastomeres from human cleavage-stage embryos. Afterwards, oligonucleotide array-CGH and BAC array-CGH were also compared analysing 16 single blastomeres from human cleavage-stage embryos. All three comprehensive analysis techniques provided broadly similar cytogenetic profiles; however, non-identical profiles appeared when extensive aneuploidies were present in a cell. Both array techniques provided an optimised analysis procedure and a higher resolution than metaphase-CGH. Moreover, oligonucleotide array-CGH was able to define extra segmental imbalances in 14.7% of the blastomeres and it better determined the specific unbalanced chromosome regions due to a higher resolution of the technique (≈20 kb). Applicability of oligonucleotide array-CGH for Preimplantation Genetic Diagnosis has been demonstrated in two cases of Robertsonian translocation carriers 45,XY,der(13;14)(q10;q10). Transfer of euploid embryos was performed in both cases and pregnancy was achieved by one of the couples. This is the first time that an oligonucleotide array-CGH approach has been successfully applied to Preimplantation Genetic Diagnosis for balanced chromosome rearrangement carriers.     

GSVD comparison of patient-matched normal and tumor aCGH profiles reveals global copy-number alterations predicting glioblastoma multiforme survival

Despite recent large-scale profiling efforts, the best prognostic predictor of glioblastoma multiforme (GBM) remains the patient's age at diagnosis. We describe a global pattern of tumor-exclusive co-occurring copy-number alterations (CNAs) that is correlated, possibly coordinated with GBM patients' survival and response to chemotherapy. The pattern is revealed by GSVD comparison of patient-matched but probe-independent GBM and normal aCGH datasets from The Cancer Genome Atlas (TCGA). We find that, first, the GSVD, formulated as a framework for comparatively modeling two composite datasets, removes from the pattern copy-number variations (CNVs) that occur in the normal human genome (e.g., female-specific X chromosome amplification) and experimental variations (e.g., in tissue batch, genomic center, hybridization date and scanner), without a-priori knowledge of these variations. Second, the pattern includes most known GBM-associated changes in chromosome numbers and focal CNAs, as well as several previously unreported CNAs in >3% of the patients. These include the biochemically putative drug target, cell cycle-regulated serine/threonine kinase-encoding TLK2, the cyclin E1-encoding CCNE1, and the Rb-binding histone demethylase-encoding KDM5A. Third, the pattern provides a better prognostic predictor than the chromosome numbers or any one focal CNA that it identifies, suggesting that the GBM survival phenotype is an outcome of its global genotype. The pattern is independent of age, and combined with age, makes a better predictor than age alone. GSVD comparison of matched profiles of a larger set of TCGA patients, inclusive of the initial set, confirms the global pattern. GSVD classification of the GBM profiles of an independent set of patients validates the prognostic contribution of the pattern.     

Genomic Profiling of Oral Squamous Cell Carcinoma by Array-Based Comparative Genomic Hybridization

We designed a study to investigate genetic relationships between primary tumors of oral squamous cell carcinoma (OSCC) and their lymph node metastases, and to identify genomic copy number aberrations (CNAs) related to lymph node metastasis. For this purpose, we collected a total of 42 tumor samples from 25 patients and analyzed their genomic profiles by array-based comparative genomic hybridization. We then compared the genetic profiles of metastatic primary tumors (MPTs) with their paired lymph node metastases (LNMs), and also those of LNMs with non-metastatic primary tumors (NMPTs). Firstly, we found that although there were some distinctive differences in the patterns of genomic profiles between MPTs and their paired LNMs, the paired samples shared similar genomic aberration patterns in each case. Unsupervised hierarchical clustering analysis grouped together 12 of the 15 MPT-LNM pairs. Furthermore, similarity scores between paired samples were significantly higher than those between non-paired samples. These results suggested that MPTs and their paired LNMs are composed predominantly of genetically clonal tumor cells, while minor populations with different CNAs may also exist in metastatic OSCCs. Secondly, to identify CNAs related to lymph node metastasis, we compared CNAs between grouped samples of MPTs and LNMs, but were unable to find any CNAs that were more common in LNMs. Finally, we hypothesized that subpopulations carrying metastasis-related CNAs might be present in both the MPT and LNM. Accordingly, we compared CNAs between NMPTs and LNMs, and found that gains of 7p, 8q and 17q were more common in the latter than in the former, suggesting that these CNAs may be involved in lymph node metastasis of OSCC. In conclusion, our data suggest that in OSCCs showing metastasis, the primary and metastatic tumors share similar genomic profiles, and that cells in the primary tumor may tend to metastasize after acquiring metastasis-associated CNAs.     

Genomic profiling of submucosal-invasive gastric cancer by array-based comparative genomic hybridization

Genomic copy number aberrations (CNAs) in gastric cancer have already been extensively characterized by array comparative genomic hybridization (array CGH) analysis. However, involvement of genomic CNAs in the process of submucosal invasion and lymph node metastasis in early gastric cancer is still poorly understood. In this study, to address this issue, we collected a total of 59 tumor samples from 27 patients with submucosal-invasive gastric cancers (SMGC), analyzed their genomic profiles by array CGH, and compared them between paired samples of mucosal (MU) and submucosal (SM) invasion (23 pairs), and SM invasion and lymph node (LN) metastasis (9 pairs). Initially, we hypothesized that acquisition of specific CNA(s) is important for these processes. However, we observed no significant difference in the number of genomic CNAs between paired MU and SM, and between paired SM and LN. Furthermore, we were unable to find any CNAs specifically associated with SM invasion or LN metastasis. Among the 23 cases analyzed, 15 had some similar pattern of genomic profiling between SM and MU. Interestingly, 13 of the 15 cases also showed some differences in genomic profiles. These results suggest that the majority of SMGCs are composed of heterogeneous subpopulations derived from the same clonal origin. Comparison of genomic CNAs between SMGCs with and without LN metastasis revealed that gain of 11q13, 11q14, 11q22, 14q32 and amplification of 17q21 were more frequent in metastatic SMGCs, suggesting that these CNAs are related to LN metastasis of early gastric cancer. In conclusion, our data suggest that generation of genetically distinct subclones, rather than acquisition of specific CNA at MU, is integral to the process of submucosal invasion, and that subclones that acquire gain of 11q13, 11q14, 11q22, 14q32 or amplification of 17q21 are likely to become metastatic.     

Delineating the Cytogenomic and Epigenomic Landscapes of Glioma Stem Cell Lines

Glioblastoma multiforme (GBM), the most common and malignant type of glioma, is characterized by a poor prognosis and the lack of an effective treatment, which are due to a small sub-population of cells with stem-like properties, termed glioma stem cells (GSCs). The term “multiforme” describes the histological features of this tumor, that is, the cellular and morphological heterogeneity. At the molecular level multiple layers of alterations may reflect this heterogeneity providing together the driving force for tumor initiation and development. In order to decipher the common “signature” of the ancestral GSC population, we examined six already characterized GSC lines evaluating their cytogenomic and epigenomic profiles through a multilevel approach (conventional cytogenetic, FISH, aCGH, MeDIP-Chip and functional bioinformatic analysis). We found several canonical cytogenetic alterations associated with GBM and a common minimal deleted region (MDR) at 1p36.31, including CAMTA1 gene, a putative tumor suppressor gene, specific for the GSC population. Therefore, on one hand our data confirm a role of driver mutations for copy number alterations (CNAs) included in the GBM genomic-signature (gain of chromosome 7- EGFR gene, loss of chromosome 13- RB1 gene, loss of chromosome 10-PTEN gene); on the other, it is not obvious that the new identified CNAs are passenger mutations, as they may be necessary for tumor progression specific for the individual patient. Through our approach, we were able to demonstrate that not only individual genes into a pathway can be perturbed through multiple mechanisms and at different levels, but also that different combinations of perturbed genes can incapacitate functional modules within a cellular networks. Therefore, beyond the differences that can create apparent heterogeneity of alterations among GSC lines, there’s a sort of selective force acting on them in order to converge towards the impairment of cell development and differentiation processes. This new overview could have a huge importance in therapy.     

A meta-analysis of array-CGH studies implicates antiviral immunity pathways in the development of hepatocellular carcinoma

Background

The development and progression of hepatocellular carcinoma (HCC) is significantly correlated to the accumulation of genomic alterations. Array-based comparative genomic hybridization (array CGH) has been applied to a wide range of tumors including HCCs for the genome-wide high resolution screening of DNA copy number changes. However, the relevant chromosomal variations that play a central role in the development of HCC still are not fully elucidated.

Methods

In present study, in order to further characterize the copy number alterations (CNAs) important to HCC development, we conducted a meta-analysis of four published independent array-CGH datasets including total 159 samples.

Results

Eighty five significant gains (frequency ≥25%) were mostly mapped to five broad chromosomal regions including 1q, 6p, 8q, 17q and 20p, as well as two narrow regions 5p15.33 and 9q34.2-34.3. Eighty eight significant losses (frequency ≥25%) were most frequently present in 4q, 6q, 8p, 9p, 13q, 14q, 16q, and 17p. Significant correlations existed between chromosomal aberrations either located on the same chromosome or the different chromosomes. HCCs with different etiologies largely exhibited surprisingly similar profiles of chromosomal aberrations with only a few exceptions. Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the genes affected by these chromosomal aberrations were significantly enriched in 31 canonical pathways with the highest enrichment observed for antiviral immunity pathways.

Conclusions

Taken together, our findings provide novel and important clues for the implications of antiviral immunity-related gene pathways in the pathogenesis and progression of HCC.     

Stochastic segmentation models for array-based comparative genomic hybridization data analysis

Array-based comparative genomic hybridization (array-CGH) is a high throughput, high resolution technique for studying the genetics of cancer. Analysis of array-CGH data typically involves estimation of the underlying chromosome copy numbers from the log fluorescence ratios and segmenting the chromosome into regions with the same copy number at each location. We propose for the analysis of array-CGH data, a new stochastic segmentation model and an associated estimation procedure that has attractive statistical and computational properties. An important benefit of this Bayesian segmentation model is that it yields explicit formulas for posterior means, which can be used to estimate the signal directly without performing segmentation. Other quantities relating to the posterior distribution that are useful for providing confidence assessments of any given segmentation can also be estimated by using our method. We propose an approximation method whose computation time is linear in sequence length which makes our method practically applicable to the new higher density arrays. Simulation studies and applications to real array-CGH data illustrate the advantages of the proposed approach.     

Loss of 9p21 is embedded in a complex but consistent pattern of genomic imbalances in oral squamous cell carcinomas

35 oral squamous cell carcinomas examined previously by comparative genomic hybridization (CGH) exhibited 5 up to 47 copy number alterations (CNAs). 13 of those cases showed a loss of parts of the short arm of chromosome 9, band p21 being affected in all of these cases. A highly complex but strikingly consistent pattern of genomic imbalances with an average 31.5 CNAs per tumor was associated with this deletion, and gains clearly dominated over losses of genomic material. Comparable patterns, however, could also be found in tumors with a high number of CNAs (24 CNAs) but without the deletion. Low numbers of imbalances were accompanied by low consistency of the CNA patterns. None of these latter cases showed the deletion 9p21. 66.7% of the dim(9p21)-positive tumors were of class pT4 (vs. 22% in dim(9p21)-negative cases), 77% of stage III or IV (vs. 47% in the group without the deletion), but only 8% of the dim(9p21)-positive tumors were classified as grade 3 (vs. 41% in the negative group). Other clinicopathologic features like prevalence of relapse, or survival time could not be as clearly associated with the deletion. For instance, short relapse-free survival was clearly associated with a high number of CNAs, rather independent of presence or absence of dim(9p21) in the affected tumor. From these findings it is concluded that previously found associations of 9p21 deletion with clinical parameters can reasonably be estimated only in the context of the pattern and complexity of the genomic imbalances accompanying this chromosomal loss in the examined tumors.     

Detection of DNA copy number abnormality by microarray expression analysis

Gene copy-number abnormalities (CNAs) are characteristic of solid tumors and are found in association with developmental abnormalities and/or mental retardation. The ultimate impact of CNAs is exerted by the altered expression of encoded genes. We have utilized high-density oligonucleotide arrays from Affymetrix to identify DNA CNAs via their impact on mRNA expression levels. In these studies, we have used three different trisomic cell lines (trisomy 9, trisomy 18, trisomy 21) as models of CNAs and have compared mRNA expression in those trisomic cells with that observed in diploid cell lines of matched tissue origin. Our data clearly show that genes from CNA chromosome regions are substantially over-represented (P<0.000001 by chi-square analysis) in the differentially expressed subset from comparisons of all three trisomic cell lines with normal matching cells. In addition, we have been able to detect the origin of the duplication by a statistical scan for over-expressed genes. These data show that microarray detection of differential mRNA expression can be used to identify significant DNA CNAs.     

Flexible and accurate detection of genomic copy-number changes from aCGH

Genomic DNA copy-number alterations (CNAs) are associated with complex diseases, including cancer: CNAs are indeed related to tumoral grade, metastasis, and patient survival. CNAs discovered from array-based comparative genomic hybridization (aCGH) data have been instrumental in identifying disease-related genes and potential therapeutic targets. To be immediately useful in both clinical and basic research scenarios, aCGH data analysis requires accurate methods that do not impose unrealistic biological assumptions and that provide direct answers to the key question, "What is the probability that this gene/region has CNAs?" Current approaches fail, however, to meet these requirements. Here, we introduce reversible jump aCGH (RJaCGH), a new method for identifying CNAs from aCGH; we use a nonhomogeneous hidden Markov model fitted via reversible jump Markov chain Monte Carlo; and we incorporate model uncertainty through Bayesian model averaging. RJaCGH provides an estimate of the probability that a gene/region has CNAs while incorporating interprobe distance and the capability to analyze data on a chromosome or genome-wide basis. RJaCGH outperforms alternative methods, and the performance difference is even larger with noisy data and highly variable interprobe distance, both commonly found features in aCGH data. Furthermore, our probabilistic method allows us to identify minimal common regions of CNAs among samples and can be extended to incorporate expression data. In summary, we provide a rigorous statistical framework for locating genes and chromosomal regions with CNAs with potential applications to cancer and other complex human diseases.     

Simultaneous Detection of Both Single Nucleotide Variations and Copy Number Alterations by Next-Generation Sequencing in Gorlin Syndrome

Gorlin syndrome (GS) is an autosomal dominant disorder that predisposes affected individuals to developmental defects and tumorigenesis, and caused mainly by heterozygous germline PTCH1 mutations. Despite exhaustive analysis, PTCH1 mutations are often unidentifiable in some patients; the failure to detect mutations is presumably because of mutations occurred in other causative genes or outside of analyzed regions of PTCH1, or copy number alterations (CNAs). In this study, we subjected a cohort of GS-affected individuals from six unrelated families to next-generation sequencing (NGS) analysis for the combined screening of causative alterations in Hedgehog signaling pathway-related genes. Specific single nucleotide variations (SNVs) of PTCH1 causing inferred amino acid changes were identified in four families (seven affected individuals), whereas CNAs within or around PTCH1 were found in two families in whom possible causative SNVs were not detected. Through a targeted resequencing of all coding exons, as well as simultaneous evaluation of copy number status using the alignment map files obtained via NGS, we found that GS phenotypes could be explained by PTCH1 mutations or deletions in all affected patients. Because it is advisable to evaluate CNAs of candidate causative genes in point mutation-negative cases, NGS methodology appears to be useful for improving molecular diagnosis through the simultaneous detection of both SNVs and CNAs in the targeted genes/regions.     

Copy Number Analysis Identifies Novel Interactions Between Genomic Loci in Ovarian Cancer

Ovarian cancer is a heterogeneous disease displaying complex genomic alterations, and consequently, it has been difficult to determine the most relevant copy number alterations with the scale of studies to date. We obtained genome-wide copy number alteration (CNA) data from four different SNP array platforms, with a final data set of 398 ovarian tumours, mostly of the serous histological subtype. Frequent CNA aberrations targeted many thousands of genes. However, high-level amplicons and homozygous deletions enabled filtering of this list to the most relevant. The large data set enabled refinement of minimal regions and identification of rare amplicons such as at 1p34 and 20q11. We performed a novel co-occurrence analysis to assess cooperation and exclusivity of CNAs and analysed their relationship to patient outcome. Positive associations were identified between gains on 19 and 20q, gain of 20q and loss of X, and between several regions of loss, particularly 17q. We found weak correlations of CNA at genomic loci such as 19q12 with clinical outcome. We also assessed genomic instability measures and found a correlation of the number of higher amplitude gains with poorer overall survival. By assembling the largest collection of ovarian copy number data to date, we have been able to identify the most frequent aberrations and their interactions.     

Comparative Oncogenomics Implicates the Neurofibromin 1 Gene (NF1) as a Breast Cancer Driver

Identifying genomic alterations driving breast cancer is complicated by tumor diversity and genetic heterogeneity. Relevant mouse models are powerful for untangling this problem because such heterogeneity can be controlled. Inbred Chaos3 mice exhibit high levels of genomic instability leading to mammary tumors that have tumor gene expression profiles closely resembling mature human mammary luminal cell signatures. We genomically characterized mammary adenocarcinomas from these mice to identify cancer-causing genomic events that overlap common alterations in human breast cancer. Chaos3 tumors underwent recurrent copy number alterations (CNAs), particularly deletion of the RAS inhibitor Neurofibromin 1 (Nf1) in nearly all cases. These overlap with human CNAs including NF1, which is deleted or mutated in 27.7% of all breast carcinomas. Chaos3 mammary tumor cells exhibit RAS hyperactivation and increased sensitivity to RAS pathway inhibitors. These results indicate that spontaneous NF1 loss can drive breast cancer. This should be informative for treatment of the significant fraction of patients whose tumors bear NF1 mutations.     

Computation of recurrent minimal genomic alterations from array-CGH data

MOTIVATION: The identification of recurrent genomic alterations can provide insight into the initiation and progression of genetic diseases, such as cancer. Array-CGH can identify chromosomal regions that have been gained or lost, with a resolution of approximately 1 mb, for the cutting-edge techniques. The extraction of discrete profiles from raw array-CGH data has been studied extensively, but subsequent steps in the analysis require flexible, efficient algorithms, particularly if the number of available profiles exceeds a few tens or the number of array probes exceeds a few thousands. RESULTS: We propose two algorithms for computing minimal and minimal constrained regions of gain and loss from discretized CGH profiles. The second of these algorithms can handle additional constraints describing relevant regions of copy number change. We have validated these algorithms on two public array-CGH datasets. AVAILABILITY: From the authors, upon request. CONTACT: celine@lri.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

De novo balanced complex chromosome rearrangement (CCR) involving chromosome 8, 11 and 16 in a boy with mild developmental delay and psychotic disorder

Congenital Complex Chromosome rearrangements (CCRs) compatible with life are rare in humans. We report a de novo CCR involving chromosomes 8, 11 and 16 with 4 breakpoints in a patient with mild dysmorphic features, acquisition delay and psychotic disorder. Conventional cytogenetic analysis revealed an apparently balanced 8;16 translocation. Further FISH analysis with WCP 8 and WCP 16 probes revealed the presence of a third chromosome involved in the translocation. The multicolour karyotype confirmed the complexity of the rearrangement and showed that the derivative chromosome 8 was composed of 3 distinct segments derived from chromosomes 8, 16 and 11. The breakpoints of this complex rearrangement were located at 8q21, 11q14, 11q23 and 16q12. Comparative genomic hybridization (CGH) and array-CGH were performed to investigate the possibility of any genomic imbalance as a result of the complex rearrangement. No imbalance was detected by these two techniques. Our study showed: i) the necessity to confirm reciprocal translocations with FISH using painting probes, particularly when the karyotype resolution is weak; ii) the usefulness of multicolour karyotype for the characterization of structural chromosomal rearrangements, particularly when they are complex; iii) the usefulness of CGH and array-CGH in cases of abnormal phenotype and apparently balanced rearrangement in order to explore the breakpoints and to detect additional imbalances.     

Genetics of early miscarriage

A miscarriage is the most frequent complication of a pregnancy. Poor chromosome preparations, culture failure, or maternal cell contamination may hamper conventional karyotyping. Techniques such as chromosomal comparative genomic hybridization (chromosomal‐CGH), array-comparative genomic hybridization (array-CGH), fluorescence in situ hybridization (FISH), multiplex ligation-dependent probe amplification (MLPA) and quantitative fluorescent polymerase chain reaction (QF-PCR) enable us to trace submicroscopic abnormalities. We found the prevalence of chromosome abnormalities in women facing a single sporadic miscarriage to be 45% (95% CI: 38–52; 13 studies, 7012 samples). The prevalence of chromosome abnormalities in women experiencing a subsequent miscarriage after preceding recurrent miscarriage proved to be comparable: 39% (95% CI: 29–50; 6 studies 1359 samples). More chromosome abnormalities are detected by conventional karyotyping compared to FISH or MLPA only (chromosome region specific techniques), and the same amount of abnormalities compared to QF-PCR (chromosome region specific techniques) and chromosomal‐CGH and array-CGH (whole genome techniques) only. Molecular techniques could play a role as an additional technique when culture failure or maternal contamination occurs: recent studies show that by using array-CGH, an additional 5% of submicroscopic chromosome variants can be detected. Because of the small sample size as well as the unknown clinical relevance of these molecular aberrations, more and larger studies should be performed of submicroscopic chromosome abnormalities among sporadic miscarriage samples. For recurrent miscarriage samples molecular technique studies are relatively new. It has often been suggested that miscarriages are due to chromosomal abnormalities in more than 50%, but the present review has determined that chromosomal and submicroscopic genetic abnormalities on average are prevalent in maximally half of the miscarriage samples. This article is part of a Special Issue entitled: Molecular Genetics of Human Reproductive Failure.     

Impact on disease development, genomic location and biological function of copy number alterations in non-small cell lung cancer

Lung cancer, of which more than 80% is non-small cell, is the leading cause of cancer-related death in the United States. Copy number alterations (CNAs) in lung cancer have been shown to be positionally clustered in certain genomic regions. However, it remains unclear whether genes with copy number changes are functionally clustered. Using a dense single nucleotide polymorphism array, we performed genome-wide copy number analyses of a large collection of non-small cell lung tumors (n = 301). We proposed a formal statistical test for CNAs between different groups (e.g., non-involved lung vs. tumors, early vs. late stage tumors). We also customized the gene set enrichment analysis (GSEA) algorithm to investigate the overrepresentation of genes with CNAs in predefined biological pathways and gene sets (i.e., functional clustering). We found that CNAs events increase substantially from germline, early stage to late stage tumor. In addition to genomic position, CNAs tend to occur away from the gene locations, especially in germline, non-involved tissue and early stage tumors. Such tendency decreases from germline to early stage and then to late stage tumors, suggesting a relaxation of selection during tumor progression. Furthermore, genes with CNAs in non-small cell lung tumors were enriched in certain gene sets and biological pathways that play crucial roles in oncogenesis and cancer progression, demonstrating the functional aspect of CNAs in the context of biological pathways that were overlooked previously. We conclude that CNAs increase with disease progression and CNAs are both positionally and functionally clustered. The potential functional capabilities acquired via CNAs may be sufficient for normal cells to transform into malignant cells.