Biomedical subjects

Kuang-Hung Pan

Publications and source records attributed to Kuang-Hung Pan.

5 recordsLinked to original sources

PubMed2005

Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays.

Global analysis of gene expression by using DNA microarrays is employed increasingly to search for differences in biological properties between normal and diseased tissue. In such studies, expression that deviates from defined thresholds commonly is used for creating genetic signatures that characterize disease vs. normality. Although it is axiomatic that the threshold parameters applied to microarray analysis will alter the contents of such genetic signatures, the extent to which threshold choice can affect the fundamental conclusions made from microarray-based studies has not been elucidated. We used GABRIEL (Genetic Analysis By Rules Incorporating Expert Logic), a platform of knowledge-based algorithms for the global analysis of gene expression, together with conventional statistical approaches, to examine the sensitivity of conclusions to threshold choice in recently published microarray-based studies. An analysis of the effects of threshold decisions in one of these studies [Ramaswamy, S., Ross, K. N., Lander, E. S. & Golub, T. R. (2003) Nat. Genet. 33, 49-54], which arrived at the important conclusion that the metastatic potential of primary tumors is encoded by the bulk of cells in the tumor, is the focus of this article. We discovered that support for this conclusion highly depends on the threshold used to create gene expression signatures. We also found that threshold choice dramatically affected the gene function categories represented nonrandomly in signatures. Our results suggest that the robustness of biological conclusions made by using microarray analysis should be routinely assessed by examining the validity of the conclusions by using a range of threshold parameters.

Adenocarcinoma↗

PubMed2005

An integrated data analysis approach to characterize genes highly expressed in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the major causes of cancer deaths worldwide. New diagnostic and therapeutic options are needed for more effective and early detection and treatment of this malignancy. We identified 703 genes that are highly expressed in HCC using DNA microarrays, and further characterized them in order to uncover novel tumor markers, oncogenes, and therapeutic targets for HCC. Using Gene Ontology annotations, genes with functions related to cell proliferation and cell cycle, chromatin, repair, and transcription were found to be significantly enriched in this list of highly expressed genes. We also identified a set of genes that encode secreted (e.g. GPC3, LCN2, and DKK1) or membrane-bound proteins (e.g. GPC3, IGSF1, and PSK-1), which may be attractive candidates for the diagnosis of HCC. A significant enrichment of genes highly expressed in HCC was found on chromosomes 1q, 6p, 8q, and 20q, and we also identified chromosomal clusters of genes highly expressed in HCC. The microarray analyses were validated by RT-PCR and PCR. This approach of integrating other biological information with gene expression in the analysis helps select aberrantly expressed genes in HCC that may be further studied for their diagnostic or therapeutic utility.

Biomarkers, Tumor↗

PubMed2004

Disparate effects of telomere attrition on gene expression during replicative senescence of human mammary epithelial cells cultured under different conditions.

Telomere shortening in populations of human mammary epithelial cells (HMECs) that survive early replicative arrest (M0) by the inactivation of p16(INK4A) during cell culture on plastic dishes leads to a state of permanent replicative arrest termed senescence. While culture of HMECs on feeder layers abrogates M0 and p16(INK4A) inactivation, progressive telomere attrition in these cells also eventually results in permanent replicative arrest. Expression of telomerase prevents both senescence on plastic (S-P) and senescence on feeder layers (S-FL) in HMECs, as it does also in cultured primary human fibroblasts. We report here that the gene expression profiles of senescence in HMECs of the same lineage maintained under different culture conditions showed surprisingly little commonality. Moreover, neither of these senescence-associated profiles in HMECs resembles the profile for senescence in human fibroblasts. These results indicate that senescence-associated alterations in gene expression resulting from telomere attrition are affected by culture conditions as well as by cell origins, and argue that replicative senescence at the molecular level is a diverse rather than unique cellular process.

Adult↗

PubMed2003

Senescence-specific gene expression fingerprints reveal cell-type-dependent physical clustering of up-regulated chromosomal loci.

Replicative senescence is the state of irreversible proliferative arrest that occurs as a concomitant of progressive telomere shortening. By using cDNA microarrays and the gabriel system of computer programs to apply domain-specific and procedural knowledge for data analysis, we investigated global changes in gene transcription occurring during replicative senescence in human fibroblasts and mammary epithelial cells (HMECs). Here we report the identification of transcriptional "fingerprints" unique to senescence, the finding that gene expression perturbations during senescence differ greatly in fibroblasts and HMECs, and the discovery that despite the disparate nature of the chromosomal loci affected by senescence in fibroblasts and HMECs, the up-regulated loci in both types of cells show physical clustering. This clustering, which contrasts with the random distribution of genes down-regulated during senescence or up-regulated during reversible proliferative arrest (i.e., quiescence), supports the view that replicative senescence is associated with alteration of chromatin structure.

Breast↗

PubMed2002

Analysis of DNA microarrays using algorithms that employ rule-based expert knowledge.

The ability to investigate the transcription of thousands of genes concurrently by using DNA microarrays offers both major scientific opportunities and significant analytical challenges. Here we describe GABRIEL, a rule-based system of computer programs designed to apply domain-specific and procedural knowledge systematically and uniformly for the analysis and interpretation of data from DNA microarrays. GABRIEL'S problem-solving rules direct stereotypical tasks, whereas domain-specific knowledge pertains to gene functions and relationships or to experimental conditions. Additionally, GABRIEL can learn novel rules through genetic algorithms, which define patterns that best match the data being analyzed and can identify groupings in gene expression profiles preordered by chromosomal position or by a nonsupervised algorithm such as hierarchical clustering. GABRIEL subsystems explain the logic that underlies conclusions and provide a graphical interface and interactive platform for the acquisition of new knowledge. The present report compares GABRIEL'S output with published findings in which expert knowledge has been applied post hoc to microarray groupings generated by hierarchical clustering.

Algorithms↗