Publications by authors named "Chee How Lee"

Dendritic cells (DCs) exhibit distinct functional properties at immature and mature states. To identify genes preferentially regulated in monocyte-derived immature DCs (imDCs), 13 000-element microarrays were hybridized with RNA isolated from imDCs, mature DCs (mDCs), monocytes, and macrophages and a TGF-beta-induced protein (betaig-h3) was identified as being most prominently up-regulated in imDCs. By polymerase chain reaction (PCR), little betaig-h3 mRNA was detected in monocytes and macrophages, but it was abundant in imDCs.

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Ki67 is a nuclear protein that is tightly linked to the cell cycle. It is a marker of cell proliferation and has been used to stratify good and poor prognostic categories in invasive breast cancer. Its correlation with gene expression patterns has not been fully elucidated.

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Purpose: Breast cancers can display distinct clinical characteristics in different ethnic populations. Previous studies involving European and United States patients have shown that breast tumors can be divided by their gene expression profiles into distinct "molecular subtypes." In this report, we surveyed a series of invasive and preinvasive breast tumors from Asian-Chinese patients to investigate whether similar subtypes could also be observed in this ethnic group.

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The Nottingham prognostic index (NPI) is a widely used clinicopathological staging system for breast cancer prognostication. Using a step-wise classification approach where breast tumor expression profiles were first divided into general "molecular subtypes" [estrogen receptor (ER)+, ER-, ERBB2+], followed by an independent analysis of each subtype, we identified a 62-gene expression signature (NPI-ES) highly correlated to the NPI in ER+ tumors. The NPI-ES classified the majority of ER+ tumors into two distinct groups with high confidence and was significantly correlated to NPI status in two independent sets of ER+ tumors derived from different centers.

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Comparative genomic hybridization (CGH), microsatellite instability (MSI) assays, and expression microarrays were used to molecularly subclassify a common set of gastric tumor samples. We identified a number of novel genomic aberrations associated with gastric cancer and discovered that gastric tumors could be grouped by their expression profiles into three broad classes: "tumorigenic," "reactive," and "gastric-like." Patients with gastric-like tumors exhibited a significantly better overall survival than patients belonging to the other two classes (P < 0.

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