Project description:Neuroblastoma (NB) is an aggressive tumor that affects both infants and children. The disease outcome is greatly influenced by age of patient, stage, chromosome copy number aberrations (CNAs) and gene expression abnormalities. We analyzed, by microarray technology, genome and transcriptome of 3 groups of tumors of patients with metastatic disease: G1, stage 4S and MYCN single copy; G2, stage 4 younger than 18 months of age, MYCN single copy with no disease progression and G3, stage 4, older than 19 months, with unfavorable outcome. We found an accumulation of structural copy number aberrations (CNAs) in G3 whereas G1 tumors had mostly numerical (N) CNAs and G2 showed an intermediate behavior. Pair wise comparisons demonstrated that the average of N CNAs significantly decreased from G1 to G2 to G3 (9.6 G1 < 7.2 G2 < 3.6 G3); in contrast S CNAs significantly increased in G3 (0.7 G1 < 3.7 G2 < 7.0 G3). Interestingly, we observed several intra-chromosomal rearrangements in G3 tumors on chromosomes not usually involved in NB. Excluding MYCN amplified tumors by G3 we found a high frequency of S CNAs in this group. Gene expression analysis showed a deregulation of downstream genes of Ras and Rho signaling pathway among the 3 groups. It has been also observed a progressive switch off of development and adhesion genes and a switch on of cell cycle genes from G1 to G2 to G3. Moreover, the telemorase genes were significantly expressed in G3 with respect to remaining groups. Present data show an accumulation of S CNAs from stage 4S to 4. The deregulation of genes Rho/Ras pathway may explain the increase of tumor aggressiveness from G1 to G2 to G3. The increase of cell cycle and telomerase genes expression associated with G3 would provide unlimited replicative potential for these tumors and may be responsible for accumulation of S CNAs. Finally, we can argue that accumulation of structural aberrations and gene deregulation is age-dependent and it is associated with a more aggressive tumor phenotype. We analyzed 133 samples of metastatic neuroblastoma from patients divided into three groups: G1 49 patients stage 4S and MYCN single copy; G2 37 patients stage 4 younger than 18 months of age at diagnosis, MYCN single copy with no disease progression; G3 47 patients stage 4 older than 19 months of age at diagnosis, with unfavorable outcome.

Project description:Tumorigenic processes are understood to be driven by epi-/genetic and genomic alterations from single point mutations to chromosomal alterations such as insertions and deletions of nucleotides up to gains and losses of large chromosomal fragments including products of chromosomal rearrangements e.g. fusion genes and proteins. Overall comparisons of copy number alterations (CNAs) present in 48 clear cell renal cell carcinoma (ccRCC) genomes result in ratios of gene losses versus gene gains between 26 ccRCC Fuhrman malignancy grades G1 (ratio 1.25) and 20 G3 (ratio 0.58). Gene losses and gains of 15762 CNA genes are mapped to 795 chromosomal cytoband loci including 280 KEGG pathways. CNAs are classified according to their contribution to Fuhrman tumour gradings G1 and G3. Gene gains and losses turn out to be highly structured processes in ccRCC genomes enabling the subclassification and stratification of ccRCC tumours in a genome-wide manner. CNAs of ccRCC seem to start with common tumour related gene losses flanked by CNAs specifying Fuhrman grade G1 losses and CNA gains favouring grade G3 tumours. The appearance of recurrent CNA signatures implies the presence of causal mechanisms most likely implicated in the pathogenesis and disease-outcome of ccRCC tumours distinguishing lower from higher malignant tumours. Finally, the diagnostic quality of initial 201 genes (108 genes supporting G1 and 93 genes G3 phenotypes) are successfully validated on published Swiss data (GSE19949) leading to a restricted CNA gene set of 171 CNA genes of which 85 genes favour Fuhrman grade G1 and 86 genes Fuhrman grade G3. Regarding these gene sets overall survival decreases with the number of G3 related gene losses plus the total number of gene gains. CNA gene sets presented define an entry to a gene-directed and pathway-related functional understanding of ongoing copy number alterations within and between individual ccRCC tumours leading to CNA genes of prognostic and predictive value.

Project description:Histological grading of breast cancer defines morphological subtypes informative of metastatic potential, although not without considerable inter-observer disagreement and clinical heterogeneity particularly among the moderately differentiated grade II (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade I (G1) and grade III (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with moderately differentiated disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable to that of lymph node status and tumor size. When incorporated into the Nottingham Prognostic Index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low and high grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed here. The Stockholm cohort data can be accessed at GEO Series GSE1456. Experiment Overall Design: All tumor specimens were assessed on U133 A and B arrays.

Project description:Histological grading of breast cancer defines morphological subtypes informative of metastatic potential, although not without considerable inter-observer disagreement and clinical heterogeneity particularly among the moderately differentiated grade II (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade I (G1) and grade III (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with moderately differentiated disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable to that of lymph node status and tumor size. When incorporated into the Nottingham Prognostic Index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low and high grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed here. The Stockholm cohort data can be accessed at GEO Series GSE1456. Keywords: Tumor sample comparisons

Dataset Information

High-resolution, genome-wide analysis of human metastatic neuroblastoma samples by array-Comparative Genomic Hybridization (aCGH)

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