Biomedical subjects

David Lindgren

Publications and source records attributed to David Lindgren.

3 recordsLinked to original sources

PubMed2006

Independent component analysis reveals new and biologically significant structures in micro array data.

BACKGROUND: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem. BSS attempts to separate a mixture of signals into their different sources and refers to the problem of recovering signals from several observed linear mixtures. In the context of micro array data, "sources" may correspond to specific cellular responses or to co-regulated genes. RESULTS: We applied independent component analysis (ICA) to three different microarray data sets; two tumor data sets and one time series experiment. To obtain reliable components we used iterated ICA to estimate component centrotypes. We found that many of the low ranking components indeed may show a strong biological coherence and hence be of biological significance. Generally ICA achieved a higher resolution when compared with results based on correlated expression and a larger number of gene clusters with significantly enriched for gene ontology (GO) categories. In addition, components characteristic for molecular subtypes and for tumors with specific chromosomal translocations were identified. ICA also identified more than one gene clusters significant for the same GO categories and hence disclosed a higher level of biological heterogeneity, even within coherent groups of genes. CONCLUSION: Although the ICA approach primarily detects hidden variables, these surfaced as highly correlated genes in time series data and in one instance in the tumor data. This further strengthens the biological relevance of latent variables detected by ICA.

Algorithms↗

PubMed2005

Molecular signatures in childhood acute leukemia and their correlations to expression patterns in normal hematopoietic subpopulations.

Global expression profiles of a consecutive series of 121 childhood acute leukemias (87 B lineage acute lymphoblastic leukemias, 11 T cell acute lymphoblastic leukemias, and 23 acute myeloid leukemias), six normal bone marrows, and 10 normal hematopoietic subpopulations of different lineages and maturations were ascertained by using 27K cDNA microarrays. Unsupervised analyses revealed segregation according to lineages and primary genetic changes, i.e., TCF3(E2A)/PBX1, IGH@/MYC, ETV6(TEL)/RUNX1(AML1), 11q23/MLL, and hyperdiploidy (>50 chromosomes). Supervised discriminatory analyses were used to identify differentially expressed genes correlating with lineage and primary genetic change. The gene-expression profiles of normal hematopoietic cells were also studied. By using principal component analyses (PCA), a differentiation axis was exposed, reflecting lineages and maturation stages of normal hematopoietic cells. By applying the three principal components obtained from PCA of the normal cells on the leukemic samples, similarities between malignant and normal cell lineages and maturations were investigated. Apart from showing that leukemias segregate according to lineage and genetic subtype, we provide an extensive study of the genes correlating with primary genetic changes. We also investigated the expression pattern of these genes in normal hematopoietic cells of different lineages and maturations, identifying genes preferentially expressed by the leukemic cells, suggesting an ectopic activation of a large number of genes, likely to reflect regulatory networks of pathogenetic importance that also may provide attractive targets for future directed therapies.

Bone Marrow↗

PubMed2005

Microarray analyses reveal strong influence of DNA copy number alterations on the transcriptional patterns in pancreatic cancer: implications for the interpretation of genomic amplifications.

DNA copy number alterations are believed to play a major role in the development and progression of human neoplasms. Although most of these genomic imbalances have been associated with dysregulation of individual genes, their large-scale transcriptional consequences remain unclear. Pancreatic carcinomas frequently display gene copy number variation of entire chromosomes as well as of chromosomal subregions. These changes range from homozygous deletions to high-level amplifications and are believed to constitute key genetic alterations in the cellular transformation of this tumor type. To investigate the transcriptional consequences of the most drastic genomic changes, that is, genomic amplifications, and to analyse the genome-wide transcriptional effects of DNA copy number changes, we performed expression profiling of 29 pancreatic carcinoma cell lines and compared the results with matching genomic profiling data. We show that a strong association between DNA copy numbers and mRNA expression levels is present in pancreatic cancer, and demonstrate that as much as 60% of the genes within highly amplified genomic regions display associated overexpression. Consequently, we identified 67 recurrently overexpressed genes located in seven precisely mapped commonly amplified regions. The presented findings indicate that more than one putative target gene may be of importance in most pancreatic cancer amplicons.

Chromosome Mapping↗