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Biomedical subjects

Michelle Nessling

Publications and source records attributed to Michelle Nessling.

7 recordsLinked to original sources

Molecular classification of human gliomas using matrix-based comparative genomic hybridization.

Gliomas are the most frequent primary brain tumors and comprise a group of morphologically, biologically and clinically heterogeneous neoplasms. The different glioma types are associated with distinct genetic aberrations, which may provide useful information for tumor classification as well as prediction of prognosis and response to therapy. To facilitate the molecular classification of gliomas, we established a genomic microarray that consists of bacterial artificial chromosome (BAC) and P1-derived artificial chromosome (PAC) clones representing tumor suppressor genes, proto-oncogenes and chromosomal regions frequently gained or lost in gliomas. In addition, reference clones distributed evenly throughout the genome in approximately 15 Mbp intervals were spotted on the microarray. These customized microarrays were used for matrix-based comparative genomic hybridization (matrix CGH) analysis of 70 gliomas. Matrix CGH findings were validated by molecular genetic analyses of candidate genes, loss of heterozygosity studies and chromosomal CGH. Our results indicate that matrix CGH allows for the sensitive and specific detection of gene amplifications as well as low-level copy number gains and losses in clinical glioma samples. Furthermore, molecular classification based on matrix CGH data closely paralleled histological classification and was able to distinguish with few exceptions between diffuse astrocytomas and oligodendrogliomas, anaplastic astrocytomas and anaplastic oligodendrogliomas, anaplastic oligodendrogliomas and glioblastomas, as well as primary and secondary glioblastomas. Thus, matrix CGH is a powerful technique that allows for an automated genomic profiling of gliomas and represents a promising new tool for their molecular classification.

Adult↗

Candidate genes in breast cancer revealed by microarray-based comparative genomic hybridization of archived tissue.

Genomic imbalances in 31 formalin-fixed and paraffin-embedded primary tumors of advanced breast cancer were analyzed by microarray-based comparative genomic hybridization (matrix-CGH). A DNA chip was designed comprising 422 mapped genomic sequences including 47 proto-oncogenes, 15 tumor suppressor genes, as well as frequently imbalanced chromosomal regions. Analysis of the data was challenging due to the impaired quality of DNA prepared from paraffin-embedded samples. Nevertheless, using a method for the statistical evaluation of the balanced state for each individual experiment, we were able to reveal imbalances with high significance, which were in good concordance with previous data collected by chromosomal CGH from the same patients. Owing to the improved resolution of matrix-CGH, genomic imbalances could be narrowed down to the level of individual bacterial artificial chromosome and P1-derived artificial chromosome clones. On average 37 gains and 13 losses per tumor cell genome were scored. Gains in more than 30% of the cases were found on 1p, 1q, 6p, 7p, 8q, 9q, 11q, 12q, 17p, 17q, 20q, and 22q, and losses on 6q, 9p, 11q, and 17p. Of the 51 chromosomal regions found amplified by matrix-CGH, only 12 had been identified by chromosomal CGH. Within these 51 amplicons, genome database information defined 112 candidate genes, 44 of which were validated by either PCR amplification of sequence tag sites or DNA sequence analysis.

Breast Neoplasms↗

Automated array-based genomic profiling in chronic lymphocytic leukemia: development of a clinical tool and discovery of recurrent genomic alterations.

B cell chronic lymphocytic leukemia (B-CLL) is characterized by a highly variable clinical course. Recurrent chromosomal imbalances provide significant prognostic markers. Risk-adapted therapy based on genomic alterations has become an option that is currently being tested in clinical trials. To supply a robust tool for such large scale studies, we developed a comprehensive DNA microarray dedicated to the automated analysis of recurrent genomic imbalances in B-CLL by array-based comparative genomic hybridization (matrix-CGH). Validation of this chip in a series of 106 B-CLL cases revealed a high specificity and sensitivity that fulfils the criteria for application in clinical oncology. This chip is immediately applicable within clinical B-CLL treatment trials that evaluate whether B-CLL cases with distinct chromosomal abnormalities should be treated with chemotherapy of different intensities and/or stem cell transplantation. Through the control set of DNA fragments equally distributed over the genome, recurrent genomic imbalances were discovered: trisomy of chromosome 19 and gain of the MYCN oncogene correlating with an elevation of MYCN mRNA expression.

Automation↗

Hidden gene amplifications in aggressive B-cell non-Hodgkin lymphomas detected by microarray-based comparative genomic hybridization.

DNA amplifications are important mechanisms for proto-oncogene activation. Comparative genomic hybridization (CGH) to metaphase chromosome preparations has revealed amplifications in 10-20% of B-cell lymphomas (B-NHL). We analysed a series of 16 aggressive non-Hodgkin lymphomas by the new approach termed Matrix-CGH (M-CGH) using genomic DNA microarrays as hybridization target. For M-CGH, a dedicated B-cell lymphoma chip was constructed containing 496 genomic targets covering oncogenes, tumor suppressor genes as well as chromosome regions frequently altered in B-NHL. In 10 of 16 samples a total of 15 DNA amplifications were identified. The amplicons included BCL2, REL, CCND1, CCND2, JAK2, FGF4 and MDM2. Four of the 15 amplifications remained undetected by chromosomal CGH. The respective amplicons mapped to bands 2p13, 9p13-p21 and 12q24 and, were confirmed by fluorescence in situ hybridization. Furthermore, for four genomically amplified genes real-time quantitative reverse transcription polymerase chain reaction revealed elevated mRNA expression levels. These data show the superior diagnostic sensitivity of the newly developed diagnostic tool. As only a small portion of the genome (approximately 1.5%) has been analysed by the present DNA array, it is likely that gene amplifications are much more common in aggressive lymphomas than previously assumed.

Burkitt Lymphoma↗

Candidate genes for cross-resistance against DNA-damaging drugs.

Drug resistance of tumor cells leads to major drawbacks in the treatment of cancer. To identify candidate genes for drug resistance, we compared the expression patterns of the drug-sensitive human malignant melanoma cell line MeWo and three derived sublines with acquired resistance to the DNA-damaging agents cisplatin, etoposide, and fotemustine. Subarray analyses confirmed 57 candidate genes recovered from a genome-wide scan for differential expression. By specifically addressing cancer genes we retrieved another set of 209 candidates. Exemplary Northern blot studies indicated qualitative concordance for 110 of 135 (81.4%) data points. Whereas the etoposide-resistant line showed constant expression patterns over a period of approximately 2.5 years, the fotemustine- and cisplatin-resistant sublines exhibited considerable variability. Initially representing distinct entities, these two sublines finally converged in their expression patterns. A total of 110 genes was transiently or permanently deregulated in at least two resistant sublines. Fourteen genes displayed differential expression in all three of the sublines. We hypothesize that the variations in fotemustine and cisplatin resistance are based on progressive optimization and/or polyclonality. This, in addition to genomic alterations investigated by comparative genomic hybridization and evaluation of short-term response genes, can be used as a criterion for the selection of promising candidates. Among these are CYR61, AHCYL1, and MPP1, as well as several apoptosis-related genes, in particular STK17A and CRYAB. As MPP1 and CRYAB are also among the 14 genes differentially expressed in all three of the drug-resistant sublines, they represent the strongest candidates for resistance against DNA-damaging drugs.

Antineoplastic Agents↗

Microarray-based copy number and expression profiling in dedifferentiated and pleomorphic liposarcoma.

Sixteen dedifferentiated and pleomorphic liposarcomas were analyzed by comparative genomic hybridization (CGH) to genomic microarrays (matrix-CGH), cDNA-derived microarrays for expression profiling, and by quantitative PCR. Matrix-CGH revealed copy number gains of numerous oncogenes, i.e., CCND1, MDM2, GLI, CDK4, MYB, ESR1, and AIB1, several of which correlate with a high level of transcripts from the respective gene. In addition, a number of genes were found differentially expressed in dedifferentiated and pleomorphic liposarcomas. Application of dedicated clustering algorithms revealed that both tumor subtypes are clearly separated by the genomic profiles but only with a lesser power by the expression profiles. Using a support vector machine, a subset of five clones was identified as "class discriminators." Thus, for the distinction of these types of liposarcomas, genomic profiling appears to be more advantageous than RNA expression analysis.

Algorithms↗

Automated screening for genomic imbalances using matrix-based comparative genomic hybridization.

Genome-wide screening for chromosomal imbalances using comparative genomic hybridization (CGH) revealed a wealth of data on previously unrecognized tumor-specific genomic alterations. CGH to microarrays of DNA, an approach termed matrix-CGH, allows detection of genomic imbalances at a much higher resolution. We show that matrix CGH is also feasible from small tissue samples requiring universal amplification of genomic DNA. Because widespread application of matrix-CGH experiments using large numbers of DNA targets demands a high degree of automation, we have developed a protocol for a fully automated procedure. The use of specialized instrumentation for the generation of DNA chips, their hybridization, scanning, and evaluation required numerous alterations and modifications of the initial protocol. We here present the elaboration and testing of automated matrix-CGH. A chip consisting of 188 different genomic DNA fragments, cloned in bacterial artificial chromosome (BAC) or P1-derived artificial chromosome (PAC) vectors and immobilized in replicas of 10, was used to assess the performance of the automated protocol in determining the gene dosage variations in tumor cell lines COLO320-HSR, HL60, and NGP. Although ratios of matrix-CGH were highly concordant with results of chromosomal CGH (85%), the dynamic range of the matrix-CGH ratios was highly superior. Investigation of the two amplicons on 8q24 in COLO320-HSR and HL60, containing the MYC gene, revealed a homogeneous amplicon in COLO320-HSR but a heterogeneous amplification pattern in HL60 cells. Although control clones for normalization of the signal ratios can be predicted in cases with defined chromosomal aberrations, in primary tumors such data are often not available, requiring alternative normalization algorithms. Testing such algorithms in a primary high-grade B-cell lymphoma, we show the feasibility of this approach. With the matrix-CGH protocol presented here, robust and reliable detection of genomic gains and losses is accomplished in an automated fashion, which provides the basis for widespread application in tumor and clinical genetics.

Chromosome Aberrations↗