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Alvin Y Liu

Publications and source records attributed to Alvin Y Liu.

12 recordsLinked to original sources
PubMed2006

Mass spectrometric detection of tissue proteins in plasma.

It has long been thought that blood plasma could serve as a window into the state of one's organs in health and disease because tissue-derived proteins represent a significant fraction of the plasma proteome. Although substantial technical progress has been made toward the goal of comprehensively analyzing the blood plasma proteome, the basic assumption that proteins derived from a variety of tissues could indeed be detectable in plasma using current proteomics technologies has not been rigorously tested. Here we provide evidence that such tissue-derived proteins are both present and detectable in plasma via direct mass spectrometric analysis of captured glycopeptides and thus provide a conceptual basis for plasma protein biomarker discovery and analysis.

Antigens, CD↗
PubMed2006

Transcriptomes of human prostate cells.

BACKGROUND: The gene expression profiles of most human tissues have been studied by determining the transcriptome of whole tissue homogenates. Due to the solid composition of tissues it is difficult to study the transcriptomes of individual cell types that compose a tissue. To overcome the problem of heterogeneity we have developed a method to isolate individual cell types from whole tissue that are a source of RNA suitable for transcriptome profiling. RESULTS: Using monoclonal antibodies specific for basal (integrin beta4), luminal secretory (dipeptidyl peptidase IV), stromal fibromuscular (integrin alpha 1), and endothelial (PECAM-1) cells, respectively, we separated the cell types of the prostate with magnetic cell sorting (MACS). Gene expression of MACS-sorted cell populations was assessed with Affymetrix GeneChips. Analysis of the data provided insight into gene expression patterns at the level of individual cell populations in the prostate. CONCLUSION: In this study, we have determined the transcriptome profile of a solid tissue at the level of individual cell types. Our data will be useful for studying prostate development and cancer progression in the context of single cell populations within the organ.

Bone Morphogenetic Proteins↗
PubMed2006

Development of the Minimum Information Specification for In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE).

We describe the creation process of the Minimum Information Specification for In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE). Modeled after the existing minimum information specification for microarray data, we created a new specification for gene expression localization experiments, initially to facilitate data sharing within a consortium. After successful use within the consortium, the specification was circulated to members of the wider biomedical research community for comment and refinement. After a period of acquiring many new suggested requirements, it was necessary to enter a final phase of excluding those requirements that were deemed inappropriate as a minimum requirement for all experiments. The full specification will soon be published as a version 1.0 proposal to the community, upon which a more full discussion must take place so that the final specification may be achieved with the involvement of the whole community.

Computational Biology↗
PubMed2005

Stromal mesenchyme cell genes of the human prostate and bladder.

BACKGROUND: Stromal mesenchyme cells play an important role in epithelial differentiation and likely in cancer as well. Induction of epithelial differentiation is organ-specific, and the genes responsible could be identified through a comparative genomic analysis of the stromal cells from two different organs. These genes might be aberrantly expressed in cancer since cancer could be viewed as due to a defect in stromal signaling. We propose to identify the prostate stromal genes by analysis of differentially expressed genes between prostate and bladder stromal cells, and to examine their expression in prostate cancer. METHODS: Immunohistochemistry using antibodies to cluster designation (CD) cell surface antigens was first used to characterize the stromas of the prostate and bladder. Stromal cells were prepared from either prostate or bladder tissue for cell culture. RNA was isolated from the cultured cells and analyzed by DNA microarrays. Expression of candidate genes in normal prostate and prostate cancer was examined by RT-PCR. RESULTS: The bladder stroma was phenotypically different from that of the prostate. Most notable was the presence of a layer of CD13+ cells adjacent to the urothelium. This structural feature was also seen in the mouse bladder. The prostate stroma was uniformly CD13-. A number of differentially expressed genes between prostate and bladder stromal cells were identified. One prostate gene, proenkephalin (PENK), was of interest because it encodes a hormone. Secreted proteins such as hormones and bioactive peptides are known to mediate cell-cell signaling. Prostate stromal expression of PENK was verified by an antibody raised against a PENK peptide, by RT-PCR analysis of laser-capture microdissected stromal cells, and by database analysis. Gene expression analysis showed that PENK expression was down-regulated in prostate cancer. CONCLUSION: Our findings show that the histologically similar stromas of the prostate and bladder are phenotypically different, and express organ-specific genes. The importance of these genes in epithelial development is suggested by their abnormal expression in cancer. Among the candidates is the hormone PENK and the down-regulation of PENK expression in cancer suggests a possible association with cancer development.

Cells, Cultured↗
PubMed2005

Application of Affymetrix array and Massively Parallel Signature Sequencing for identification of genes involved in prostate cancer progression.

BACKGROUND: Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. METHODS: Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. RESULTS: Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. CONCLUSION: Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases.

Cell Line, Tumor↗
PubMed2005

Analysis of prostate cancer by proteomics using tissue specimens.

PURPOSE: Prostate cancer cells differ from their normal counterpart in gene expression. Therefore, cancer and normal tissue/cells would show differences in their proteomes. From a diagnostic standpoint differences in the composition of secreted protein species are especially relevant. We used ProteinChip Array (Ciphergen Biosystems, Fremont, California) surface enhanced laser desorption/ionization (SELDI) time of flight mass spectrometry to profile prostate tissue samples to generate phenomic fingerprints. We used quantitative proteomics based on glycopeptide capture followed by tandem mass spectrometry to identify differentially expressed proteins. MATERIALS AND METHODS: Patient matched cancer and noncancer specimens were digested by collagenase to single cells. After digestion the cells were pelleted and the cell-free supernatant was used for analysis. A reversed phase hydrophobic ProteinChip Array was used to generate SELDI patterns from 43 primary prostate tumors, including 26 with matched noncancer specimens. Quantitative proteomics was applied to 1 specimen and the expression pattern was verified by Western blotting and immunohistochemistry. RESULTS: SELDI profiles showed that cancers of similar TNM stages were more likely to have similar profiles. On quantitative proteomics tissue metalloproteinase inhibitor-1 was identified to be down-regulated in cancer. Tissue metalloproteinase inhibitor-1 expression was localized to secretory cells. CONCLUSIONS: Protein profiling by SELDI is relatively easy to perform and it has great potential in prostate cancer diagnosis through pattern recognition. Quantitative proteomics can potentially determine the identity of many biomarkers specific for prostate cancer.

Biomarkers, Tumor↗
PubMed2004

Lineage relationship between LNCaP and LNCaP-derived prostate cancer cell lines.

BACKGROUND: LNCaP and its derivative cell lines, which include C4-2 (and the related C4-2B) and CL1, are used as models of prostate cancer. Unlike LNCaP, the other cell lines show features of progressed disease such as metastatic capability and hormone independence. Analyses were done to determine if C4-2 or CL1 cells were selected from pre-existent subpopulations in LNCaP. METHODS: Prostate cancer cells were characterized by cluster designation (CD) phenotyping. Specific cell populations were sorted by flow cytometry. DNA array analysis was used to probe differential gene expression. RESULTS: CD phenotyping showed that CL1 and C4-2 (and C4-2B) were very dissimilar, and C4-2 was more similar to LNCaP. One common difference between LNCaP and its derivatives was CD26, in which virtually all C4-2 or CL1 cells were CD26(+) but only approximately 10% of LNCaP cells were CD26(+). The CD26(+) subpopulation of LNCaP was isolated and cultured in vitro. After culture, a high percentage of the cells (descended from the sorted cells) were CD26(+), in contrast to those sorted by CD13 or CD44. The cultured CD13 and CD44 populations did not show a high percentage of CD13(+) and CD44(+) cells, respectively. CD13 and CD44 are markers, in addition to CD26, for CL1 but not for C4-2. CONCLUSIONS: C4-2 arose probably from CD26(+) LNCaP cells, while CL1 arose de novo.

Antigens, CD↗
PubMed2004

Heterogeneity in primary and metastatic prostate cancer as defined by cell surface CD profile.

Cluster designation (CD) antigens are cell surface markers that can be used to identify constituent cell populations of an organ. We have previously determined the CD phenotype of normal prostate parenchymal cells and are now extending this analysis to prostate cancer. Since expression of CD antigens is associated with cellular differentiation, cancer cells may differ from their normal counterpart in their CD profile. Compared with luminal secretory cells, prostate adenocarcinoma cells are frequently negative for CD10 and CD13, express increased levels of the cell activation molecule CD24, and decreased levels of the apoptosis-associated multifunctional enzyme CD38. Expression of CD57, CD63, CD75s, CD107a, CD107b, CD164, and CD166 by cancer cells is similar to that of secretory cells. Prostate basal epithelial cells do not express the CD antigens characteristic of prostate secretory cells; and the basal cell CD markers, CD29, CD44, CD49b, CD49f, CD104, and nerve growth factor receptor (NGFR) are not expressed by cancer cells. The preferential expression of secretory cell-associated CD markers by prostate cancer cells suggests a closer lineage relationship between cancer cells and secretory cells than basal cells. Although the above cancer CD phenotype was the most frequently seen, some prostate cancers contained populations of CD10- and/or CD13-positive cells, and CD57-negative cells. Furthermore, the cancer phenotype of tumor metastasis is different. Despite its low frequency in primary tumors, CD10 is expressed by virtually all of the nodal metastases of prostate cancer. In addition, stromal fibromuscular cells associated with primary prostate cancer differ from stromal cells in benign prostate tissue by an increased level of expression of the cell activation molecule, CD90. In summary, our data show that the CD marker expression profile of prostate cancer cells most closely resembles that of secretory prostate epithelial cells and that some prostate cancers consist of heterogeneous cell populations as distinguished by CD-marker expression profiles.

Antigens, CD↗
PubMed2003

Loss of CD10 (neutral endopeptidase) is a frequent and early event in human prostate cancer.

BACKGROUND: We hypothesized that the aggressive LNCaP-derived androgen-independent cell line, CL1, might differ from LNCaP in their repertoire of cell surface markers and that these differences might typify changes that occur during clinical prostate cancer progression. METHODS: The cell surface marker expression profiles of CL1 and LNCaP were examined using flow cytometry. Markedly differential gene expression was confirmed using RT-PCR and further examined using immunohistochemistry among the prostate cancer cell lines LAPC-4, LNCaP, CL1, CL2, DU145, and PC-3. The expression of the most markedly differentially expressed surface marker, CD10, was further explored in a tissue microarray containing radical prostatectomy samples from 219 hormone naïve prostate cancer patients. RESULTS: There were marked differences in the expression of CD10, CD13, CD26, CD33, CD44, CD54, CD55, and CD104 between CL1 and LNCaP. Results from both the RT-PCR and immunohistochemistry confirmed the differential expression and found that CD10 demonstrated a pattern of expression in hormone sensitive but not hormone refractory cell lines. When CD10 expression was examined in a tissue microarray, CD10 expression was below the 25th percentile of matched normal prostate tissue in 68% of prostate cancers, below the median expression of matched normal prostate tissue in 86% of cancers, and completely absent in 34% of cancers. Samples of prostatic intraepithelial neoplasia demonstrated CD10 expression that was intermediate between normal prostatic tissue and prostate cancer. Among prostate cancer patients, CD10 expression did not correlate with Gleason score, pathological stage, or biochemical recurrence following radical prostatectomy. CONCLUSIONS: These findings demonstrate that loss or decreased expression of CD10 is an early and frequent event in human prostate cancer and implicates CD10 as a potential therapeutic target for early stage hormone sensitive prostate cancer.

Aged↗
PubMed2002

Human prostate epithelial cell-type cDNA libraries and prostate expression patterns.

BACKGROUND: Transcriptome analysis is a powerful approach to uncovering genes responsible for diseases such as prostate cancer. Ideally, one would like to compare the transcriptomes of a cancer cell and its normal counterpart for differences. METHODS: Prostate luminal and basal epithelial cell types were isolated and cell-type-specific cDNA libraries were constructed. Sequence analysis of cDNA clones generated 505 luminal cell genes and 560 basal cell genes. These sequences were deposited in a public database for expression analysis. RESULTS: From these sequences, 119 unique luminal expressed sequence tags (ESTs) were extracted and assembled into a luminal-cell transcriptome set, while 154 basal ESTs were extracted and assembled into a basal-cell set. Interlibrary comparison was performed to determine representation of these sequences in cDNA libraries constructed from prostate tumors, PIN, cell lines. CONCLUSIONS: Our analysis showed that a significant number of epithelial cell genes were not represented in the various transcriptomes of prostate tissues, suggesting that they might be underrepresented in libraries generated from tissue containing multiple cell types. Although both luminal and basal cell types are epithelial, their transcriptomes are more divergent from each other than expected, underscoring their functional difference (secretory vs. nonsecretory). Tumor tissues show different expression of luminal and basal genes, with perhaps a trend towards expression of basal genes in advanced diseases.

DNA, Complementary↗
PubMed2002

Characterization of prostate cell types by CD cell surface molecules.

A set of monoclonal antibodies raised against lymphocyte cell surface molecules, the cluster designation (CD) antigens, was used to distinguish the constituent cell types of the prostate. The luminal secretory epithelial, basal epithelial, fibromuscular stromal, nerve sheath, and endothelial cells express distinctive complements of cell surface molecules that were identified by immunohistochemistry using 152 commercially available antibodies. Many of the CD antibodies stained lymphocyte populations in the prostate. These lymphocyte populations were grouped into abundance classes of rare, moderate, and high. Some of these molecules are expressed by multiple cell types, both parenchymal and lymphoid; others are expressed by only one cell type. Distinctive patterns of CD expression, which are most similar to the expression pattern of prostate luminal cells, also characterize a small series of Gleason score 6 prostate cancers. The cell-type specificity of CD molecules increases the prospect of isolating specific cell populations, using such techniques as laser capture microdissection and flow cytometry, for cell-specific molecular studies.

Adenocarcinoma↗