Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 12407684

Block principal component analysis with application to gene microarray data classification.

Aiyi Liu·Ying Zhang·Edmund Gehan·Robert Clarke
View original source ↗Export metadata ↓

Abstract

We propose a block principal component analysis method for extracting information from a database with a large number of variables and a relatively small number of subjects, such as a microarray gene expression database. This new procedure has the advantage of computational simplicity, and theory and numerical results demonstrate it to be as efficient as the ordinary principal component analysis when used for dimension reduction, variable selection and data visualization and classification. The method is illustrated with the well-known National Cancer Institute database of 60 human cancer cell lines data (NCI60) of gene microarray expressions, in the context of classification of cancer cell lines.

Explore related subjects

DNA, NeoplasmGene Expression ProfilingHumansOligonucleotide Array Sequence AnalysisPrincipal Component AnalysisTumor Cells, CulturedJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Aiyi Liu, Ying Zhang, Edmund Gehan, Robert Clarke. 2002-11-30. Block principal component analysis with application to gene microarray data classification.. https://doi.org/10.1002/sim.1263

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2003

The presence of p53 mutations in human osteosarcomas correlates with high levels of genomic instability.

The p53 gene is a critical tumor suppressor that is inactivated in a majority of cancers. The central role of p53 in response to stresses such as DNA damage, hypoxia, and oncogene activation underlies this high frequency of negative selection during tumorigenic transformation. Mutations in p53 disrupt checkpoint responses to DNA damage and result in the potential for destabilization of the genome. Consistent with this, p53 mutant cells have been shown to accumulate genomic alterations in cell culture, mouse models, and some human tumors. The relationship between p53 mutation and genomic instability in human osteosarcoma is addressed in this report. Similar to some other primary human tumors, the mutation of p53 correlates significantly with the presence of high levels of genomic instability in osteosarcomas. Surprisingly, osteosarcomas harboring an amplification of the HDM2 oncogene, which inhibits the tumor-suppressive properties of p53, do not display high levels of genomic instability. These results demonstrate that the inactivation of p53 in osteosarcomas directly by mutation versus indirectly by HDM2 amplification may have different cellular consequences with respect to the stability of the genome.

DNA, Neoplasm↗
PubMed2003

Prognostic value of circulating prostate cells in patients with a rising PSA after radical prostatectomy.

BACKGROUND: To predict poor outcome in patients with a biochemical recurrence (rising PSA) after radical prostatectomy (RP), urologists rely primarily on Gleason score, PSA doubling time, and time from surgery to biochemical (i.e., PSA) recurrence. In the present study, we assess the value of RT-PCR detection circulating prostate cells in blood of patients with a rising PSA. METHODS: RNA from blood samples was obtained from 55 patients with a rising PSA and from 45 patients without evidence of biochemical failure (PSA < 0.1 ng/ml). Both groups were matched for age, Gleason score, pT stage, and interval between radical prostatectomy and PCR testing. RESULTS: PSA positive cells were detected in 1/45 (2%) patients without a PSA recurrence and 19/55 (34%) patients with a PSA recurrence. In the rising PSA group, mean PSA doubling time was significantly shorter in patients with positive RT-PCR (5 months) than in patients with negative RT-PCR (16 months; P = 0.001). An earlier onset of recurrence was also detected in patients with a positive RT-PCR (31 months for positive RT-PCR vs. 50 months for negative RT-PCR) but this result did not achieve statistical significance (P = 0.102). Salvage radiation therapy was administered in 15 patients. Three of the five patients with a positive RT-PCR progressed during radiotherapy whereas 7 of the 10 patients with a negative RT-PCR obtained a complete response and none have progressed. CONCLUSIONS: These preliminary results suggest that RT-PCR detection of prostate cells in blood of patients after RP correlates with rapidly progressing biochemical failure after RP.

DNA, Neoplasm↗
PubMed2003

Application of laser capture microdissection in genetic analysis of neuroblastoma and neuroblastoma precursor cells.

Recently developed quantitative and high-throughput technologies that allow automated and rapid screening of the whole genome, transcriptome and proteome have revolutionized the field of cancer genetics. At the same time, new challenges are met, e.g. the need for improved data analysis and standardization of tumor sample handling. Even if these issues are resolved, an 'old' problem in genetic tumor analysis remains, i.e. contamination of tumor samples by stromal and surrounding normal cells. To overcome this obstacle, laser capture microdissection (LCM) has been developed in order to procure the cells of interest from stained tissue sections with retention of morphology. In this review we describe the possible down-stream applications of LCM in the genetic analysis of neuroblastoma (NB). Special focus is given to MYCN copy number determination using real-time quantitative polymerase chain reaction (Q-PCR), analysis of 1p-, 3p- and 11q-deletions using loss of heterozygosity analysis and Q-PCR expression analysis of microdissected normal neuroblast cells and NB cells.

DNA, Neoplasm↗