Jaakko Hollmén

Identification of differentially expressed genes in pulmonary adenocarcinoma by using cDNA array

No clear patterns in molecular changes underlying the malignant processes in lung cancer of different histological types have been found so far. To identify critical genes in lung cancer progression we compared the expression profile of cancer related genes in 14 pulmonary adenocarcinoma patients with normal lung tissue by using the cDNA array technique. Principal component analyses (PCA) and permutation test were used to detect the differentially expressed genes. The expression profiles of 10 genes were confirmed by semi-quantitative real-time RT–PCR. In tumour samples, as compared to normal lung tissue, the up-regulated genes included such known tumour markers as CCNB1, PLK, tenascin, KRT8, KRT19 and TOP2A. The down-regulated genes included caveolin 1 and 2, and TIMP3. We also describe, for the first time, down-regulation of the interesting SOCS2 and 3, DOC2 and gravin. We show that silencing of SOCS2 is not caused by methylation of exon 1 of the gene. In conclusion, by using the cDNA array technique we were able to reveal marked differences in the gene expression level between normal lung and tumour tissue and find possible new tumour markers for pulmonary adenocarcinoma.

Differentially expressed genes in nonsmall cell lung cancer: expression profiling of cancer-related genes in squamous cell lung cancer

The expression patterns of cancer-related genes in 13 cases of squamous cell lung cancer (SCC) were characterized and compared with those in normal lung tissue and 13 adenocarcinomas (AC), the other major type of nonsmall cell lung cancer (NSCLC). cDNA array was used to screen the gene expression levels and the array results were verified using a real-time reverse-transcriptase-polymerase chain reaction (RT-PCR). Thirty-nine percent of the 25 most upregulated and the 25 most downregulated genes were common to SCC and AC. Of these genes, DSP, HMGA1 (alias HMGIY), TIMP1, MIF, CCNB1, TN, MMP11, and MMP12 were upregulated and COPEB (alias CPBP), TYROBP, BENE, BMPR2, SOCS3, TIMP3, CAV1, and CAV2 were downregulated. The expression levels of several genes from distinct protein families (cytokeratins and hemidesmosomal proteins) were markedly increased in SCC compared with AC and normal lung. In addition, several genes, overexpressed in SCC, such as HMGA1, CDK4, IGFBP3, MMP9, MMP11, MMP12, and MMP14, fell into distinct chromosomal loci, which we have detected as gained regions on the basis of comparative genomic hybridization data. Our study revealed new candidate genes involved in NSCLC.

DNA copy number amplification profiling of human neoplasms

DNA copy number amplifications activate oncogenes and are hallmarks of nearly all advanced tumors. Amplified genes represent attractive targets for therapy, diagnostics and prognostics. To investigate DNA amplifications in different neoplasms, we performed a bibliomics survey using 838 published chromosomal comparative genomic hybridization studies and collected amplification data at chromosome band resolution from more than 4500 cases. Amplification profiles were determined for 73 distinct neoplasms. Neoplasms were clustered according to the amplification profiles, and frequently amplified chromosomal loci (amplification hot spots) were identified using computational modeling. To investigate the site specificity and mechanisms of gene amplifications, colocalization of amplification hot spots, cancer genes, fragile sites, virus integration sites and gene size cohorts were tested in a statistical framework. Amplification-based clustering demonstrated that cancers with similar etiology, cell-of-origin or topographical location have a tendency to obtain convergent amplification profiles. The identified amplification hot spots were colocalized with the known fragile sites, cancer genes and virus integration sites, but global statistical significance could not be ascertained. Large genes were significantly overrepresented on the fragile sites and the reported amplification hot spots. These findings indicate that amplifications are selected in the cancer tissue environment according to the qualitative traits and localization of cancer genes.

Genomic Profiles Associated with Early Micrometastasis in Lung Cancer: Relevance of 4q Deletion

Purpose: Bone marrow is a common homing organ for early disseminated tumor cells (DTC) and their presence can predict the subsequent occurrence of overt metastasis and survival in lung cancer. It is still unclear whether the shedding of DTC from the primary tumor is a random process or a selective release driven by a specific genomic pattern. Experimental Design: DTCs were identified in bone marrow from lung cancer patients by an immunocytochemical cytokeratin assay. Genomic aberrations and expression profiles of the respective primary tumors were assessed by microarrays and fluorescence in situ hybridization analyses. The most significant results were validated on an independent set of primary lung tumors and brain metastases. Results: Combination of DNA copy number profiles (array comparative genomic hybridization) with gene expression profiles identified five chromosomal regions differentiating bone marrow-negative from bone marrow-positive patients (4q12-q32, 10p12-p11, 10q21-q22, 17q21, and 20q11-q13). Copy number changes of 4q12-q32 were the most prominent finding, containing the highest number of differentially expressed genes irrespective of chromosomal size (P = 0.018). Fluorescence in situ hybridization analyses on further primary lung tumor samples confirmed the association between loss of 4q and bone marrow-positive status. In bone marrow-positive patients, 4q was frequently lost (37% versus 7%), whereas gains could be commonly found among bone marrow-negative patients (7% versus 17%). The same loss was also found to be common in brain metastases from both small and non-small cell lung cancer patients (39%). Conclusions: Thus, our data indicate, for the first time, that early hematogenous dissemination of tumor cells might be driven by a specific pattern of genomic changes.

Integrated gene copy number and expression microarray analysis of gastric cancer highlights potential target genes

We performed an integrated array comparative genomic hybridization (aCGH) and expression microarray analysis of 8 normal gastric tissues and 38 primary tumors, including 25 intestinal and 13 diffuse gastric adenocarcinomas to identify genes whose expression is deregulated in association with copy number alteration. Our aim was also to identify molecular genetic alterations that are specific to particular clinicopathological characteristics of gastric cancer. Distinct molecular genetic profiles were identified for intestinal and diffuse gastric cancers and for tumors obtained from 2 different locations of the stomach. Interestingly, the ERBB2 amplification and gains at 20q13.12‐q13.33 almost exclusively discriminated intestinal cancers from the diffuse type. In addition, the 17q12‐q25 gain was characteristic to cancers located in corpus and the 20q13.12‐q13.13 gain was more common in the antrum. Statistical analysis was performed using integrated copy number and expression data to identify genes showing differential expression associated with a copy number alteration. Genes with the highest statistical significance included ERBB2, MUC1, GRB7, PPP1R1B and PPARBP with concomitant changes in copy number and expression. Immunohistochemical analysis of ERBB2 and MUC1 on a tissue microarray containing 78 independent gastric tissues showed statistically significant differences (p < 0.05 and <0.001) in immunopositivity in the intestinal (31 and 70%) and diffuse subtypes (14 and 41%), respectively. In conclusion, our results demonstrate that intestinal and diffuse type gastric cancers as well as cancers located in different sites of the stomach have distinct molecular profiles which may have clinical value.

Identification of specific gene copy number changes in asbestos-related lung cancer

Asbestos is a well-known lung cancer-causing mineral fiber. In vitro and in vivo experiments have shown that asbestos can cause chromosomal damage and aberrations. Lung tumors, in general, have several recurrently amplified and deleted chromosomal regions. To investigate whether a distinct chromosomal aberration profile could be detected in the lung tumors of heavily asbestos-exposed patients, we analyzed the copy number profiles of 14 lung tumors from highly asbestos-exposed patients and 14 matched tumors from nonexposed patients using classic comparative genomic hybridization (CGH). A specific profile could lead to identification of the underlying genes that may act as mediators of tumor formation and progression. In addition, array CGH analyses on cDNA microarrays (13,000 clones) were carried out on 20 of the same patients. Classic CGH showed, on average, more aberrations in asbestos-exposed than in nonexposed patients, and an altered region in chromosome 2 seemed to occur more frequently in the asbestos-exposed patients. Array CGH revealed aberrations in 18 regions that were significantly associated with either of the two groups. The most significant regions were 2p21-p16.3, 5q35.3, 9q33.3-q34.11, 9q34.13-q34.3, 11p15.5, 14q11.2, and 19p13.1-p13.3 (P < 0.005). Furthermore, 11 fragile sites coincided with the 18 asbestos-associated regions (P = 0.08), which may imply preferentially caused DNA damage at these sites. Our findings are the first evidence, indicating that asbestos exposure may produce a specific DNA damage profile.

Caveolins as tumour markers in lung cancer detected by combined use of cDNA and tissue microarrays

To identify new potential diagnostic markers for lung cancer, the expression profiles of 37 lung tumours were analysed using cDNA arrays. Seven samples were from small‐cell lung cancer (SCLC), two from large‐cell neuroendocrine tumours (LCNEC), and 28 from other non‐small‐cell lung cancers (mainly squamous cell cancer and adenocarcinoma). Principal component analysis and the permutation test were used to detect differences in the gene expression profiles and a set of genes was found that distinguished high‐grade neuroendocrine carcinomas (SCLC and LCNEC) from other lung cancers. In addition, several genes, such as caveolin‐1 (CAV1) and caveolin‐2 (CAV2), were constantly deregulated in all types of tumour sample, compared with normal tissue. The expression of these two genes was investigated further at the protein level on a tissue microarray containing tumours from 161 patients and normal tissues. Immunostaining for CAV1 was negative in 48% of tumours, whereas 28% of the tumours did not express CAV2. Lack of CAV1 protein expression was not caused by methylation or mutation. In stage I adenocarcinomas, CAV2 protein expression correlated with shorter survival. In conclusion, the present study was able to identify genes that have not previously been implicated in lung cancer by the combined use of two different array techniques. Some of these genes may provide novel diagnostic markers for lung cancer. Copyright

Gene expression and copy number profiling suggests the importance of allelic imbalance in 19p in asbestos-associated lung cancer

Asbestos is a pulmonary carcinogen known to give rise to DNA and chromosomal damage, but the exact carcinogenic mechanisms are still largely unknown. In this study, gene expression arrays were performed on lung tumor samples from 14 heavily asbestos-exposed and 14 non-exposed patients matched for other characteristics. Using a two-step statistical analysis, 47 genes were revealed that could differentiate the tumors of asbestos-exposed from those of non-exposed patients. To identify asbestos-associated regions with DNA copy number and expressional changes, the gene expression data were combined with comparative genomic hybridization microarray data. As a result, a combinatory profile of DNA copy number aberrations and expressional changes significantly associated with asbestos exposure was obtained. Asbestos-related areas were detected in 2p21–p16.3, 3p21.31, 5q35.2–q35.3, 16p13.3, 19p13.3–p13.1 and 22q12.3–q13.1. The most prominent of these, 19p13, was further characterized by microsatellite analysis in 62 patients for the differences in allelic imbalance (AI) between the two groups of lung tumors. 79% of the exposed and 45% of the non-exposed patients (P=0.008) were found to be carriers of AI in their lung tumors. In the exposed group, AI in 19p was prevalent regardless of the histological tumor type. In adenocarcinomas, AI in 19p appeared to occur independently of the asbestos exposure.

Classification of human cancers based on DNA copy number amplification modeling

BackgroundDNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms.MethodsWe applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets.ResultsProbabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns – finite or bounded descriptions of the ranges of the amplifications in the chromosome – were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands.ConclusionsOur results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features co-localize with amplification breakpoints and link them in the amplification process.

Data integration and visualization system for enabling conceptual biology

MOTIVATION Integration of heterogeneous data in life sciences is a growing and recognized challenge. The problem is not only to enable the study of such data within the context of a biological question but also more fundamentally, how to represent the available knowledge and make it accessible for mining. RESULTS Our integration approach is based on the premise that relationships between biological entities can be represented as a complex network. The context dependency is achieved by a judicious use of distance measures on these networks. The biological entities and the distances between them are mapped for the purpose of visualization into the lower dimensional space using the Sammons mapping. The system implementation is based on a multi-tier architecture using a native XML database and a software tool for querying and visualizing complex biological networks. The functionality of our system is demonstrated with two examples: (1) A multiple pathway retrieval, in which, given a pathway name, the system finds all the relationships related to the query by checking available metabolic pathway, transcriptional, signaling, protein-protein interaction and ontology annotation resources and (2) A protein neighborhood search, in which given a protein name, the system finds all its connected entities within a specified depth. These two examples show that our system is able to conceptually traverse different databases to produce testable hypotheses and lead towards answers to complex biological questions.