[Gene expression analyses and their possible clinical benefit in head and neck cancer]. / Genexpressionsanalysen und ihrmöglicher klinischer Nutzen inder Betrachtung der Kopf-Hals-Karzinome

Systems biology approaches for mutational (exome analysis and targeted sequencing) and gene expression analysis (transcriptome-wide gene expression profiling) represent a new and growing scientific field in head and neck oncology. In addition to medical biological expertise, bioinformatic assistance is increasingly required. For squamous cell head and neck cancer (HNSCC), the recent molecular genetic single-gene and signal pathway observations represent basic research. Important aspects of this have now been significantly enhanced by systems biology approaches, which have grown into relevant areas of translational clinical research. It is now known that HPV16 is associated with genetic alterations at various locations, but also that it functionally affects genes not altered in their base sequence at the level of methylation. In transcriptome analyses, various consortia found matching clusters of gene expression and HPV16 association with the spectrum of somatic mutations. The differential methylation of gene promoters discovered in HPV16-driven HNSCC proved predictive for survival­even in HNSCC patients without HPV detection. The authors present an overview of some translationally relevant findings and venture an outlook on possible future clinical developments.

Genomic and epigenomic co-evolution in follicular lymphomas.

Follicular lymphoma (FL) with a t(14;18) is a B-cell neoplasm clinically characterized by multiple recurrencies. In order to investigate the clonal evolution of this lymphoma, we studied paired primary and relapse tumor samples from 33 patients with recurrent non-transformed t(14;18)-positive FL. We reconstructed phylogenetic trees of the evolution by taking advantage of the activation-induced cytidine deaminase (AID)-mediated somatic hypermutation (SHM) active in the germinal center reaction using sequences of the clonal VHDHJH rearrangements of the immunoglobulin heavy chain (IGH) locus. Mutational analysis of the IGH locus showed evidence for ongoing somatic mutation and for counter-selection of mutations affecting the BCR conformation during tumor evolution. We further followed evolutionary divergence by targeted sequencing of gene loci affected by aberrant SHM as well as of known driver genes of lymphomagenesis, and by array-based genome-wide chromosomal imbalance and DNA methylation analysis. We observed a wide spectrum of evolutionary patterns ranging from almost no evolution to divergent evolution within recurrent non-transformed t(14;18) FL. Remarkably, we observed a correlation of the magnitude of evolutionary divergence across all genetic and epigenetic levels suggesting co-evolution. The distribution of coding mutations in driver genes and the correlation with SHM suggest CREBBP and AID to be potential modifiers of genetic and epigenetic co-evolution in FL.

MicroRNA-21 targets tumor suppressor genes ANP32A and SMARCA4.

MicroRNA-21 (miR-21) is a key regulator of oncogenic processes. It is significantly elevated in the majority of human tumors and functionally linked to cellular proliferation, survival and migration. In this study, we used two experimental-based strategies to search for novel miR-21 targets. On the one hand, we performed a proteomic approach using two-dimensional differential gel electrophoresis (2D-DIGE) to identify proteins suppressed upon enhanced miR-21 expression in LNCaP human prostate carcinoma cells. The tumor suppressor acidic nuclear phosphoprotein 32 family, member A (ANP32A) (alias pp32 or LANP) emerged as the most strongly downregulated protein. On the other hand, we applied a mathematical approach to select correlated gene sets that are negatively correlated with primary-miR-21 (pri-miR-21) expression in published transcriptome data from 114 B-cell lymphoma cases. Among these candidates, we found tumor suppressor SMARCA4 (alias BRG1) together with the already validated miR-21 target, PDCD4. ANP32A and SMARCA4, which are both involved in chromatin remodeling processes, were confirmed as direct miR-21 targets by immunoblot analysis and reporter gene assays. Furthermore, knock down of ANP32A mimicked the effect of enforced miR-21 expression by enhancing LNCaP cell viability, whereas overexpression of ANP32A in the presence of high miR-21 levels abrogated the miR-21-mediated effect. In A172 glioblastoma cells, enhanced ANP32A expression compensated for the effects of anti-miR-21 treatment on cell viability and apoptosis. In addition, miR-21 expression clearly increased the invasiveness of LNCaP cells, an effect also seen in part upon downregulation of ANP32A. In conclusion, these results suggest that downregulation of ANP32A contributes to the oncogenic function of miR-21.

Pathway activation patterns in diffuse large B-cell lymphomas.

Deregulation of cell signaling pathways controlling cell growth and cell survival is a common feature of all cancers. Although a core repertoire of oncogenic mechanisms is widely conserved between various malignancies, the constellation of pathway activities can vary even in patients with the same malignant disease. Modern molecularly targeted cancer drugs intervene in cell signaling compensating for pathway deregulation. Hence characterizing tumors with respect to pathway activation will become crucial for treatment decisions. Here we have used semi-supervised machine learning methodology to generate signatures of eight oncogene-inducible pathways, which are conserved across epithelial and lymphoid tissues. We combined them to patterns of pathway activity called PAPs for pathway activation patterns and searched for them in 220 morphologically, immunohistochemically and genetically well-characterized mature aggressive B-cell lymphomas including 134 cases with clinical data available. Besides Burkitt lymphoma, which was characterized by a unique pattern, the PAPs identified four distinct groups of mature aggressive B-cell lymphomas across independent gene expression studies with distinct biological characteristics, genetic aberrations and prognosis. We confirmed our findings through cross-platform analysis in an independent data set of 303 mature aggressive B-cell lymphomas.

Development and implementation of an analysis tool for array-based comparative genomic hybridization.

OBJECTIVES: Array-comparative genomic hybridization (aCGH) is a high-throughput method to detect and map copy number aberrations in the genome. Multi-step analysis of high-dimensional data requires an integrated suite of bioinformatic tools. In this paper we detail an analysis pipeline for array CGH data. METHODS: We developed an analysis tool for array CGH data which supports single and multi-chip analyses as well as combined analyses with paired mRNA gene expression data. The functions supporting relevant steps of analysis were implemented using the open source software R and combined as package aCGHPipeline. Analysis methods were illustrated using 189 CGH arrays of aggressive B-cell lymphomas. RESULTS: The package covers data input, quality control, normalization, segmentation and classification. For multi-chip analysis aCGHPipeline offers an algorithm for automatic delineation of recurrent regions. This task was performed manually up to now. The package also supports combined analysis with mRNA gene expression data. Outputs consist of HTML documents to facilitate communication with clinical partners. CONCLUSIONS: The R package aCGHPipeline supports basic tasks of single and multi-chip analysis of array CGH data.