Biomedical subjects

Sarah Hawley

Publications and source records attributed to Sarah Hawley.

9 recordsLinked to original sources

PubMed2006

A molecular correlate to the Gleason grading system for prostate adenocarcinoma.

Adenocarcinomas of the prostate can be categorized into tumor grades based on the extent to which the cancers histologically resemble normal prostate glands. Because grades are surrogates of intrinsic tumor behavior, characterizing the molecular phenotype of grade is of potential clinical importance. To identify molecular alterations underlying prostate cancer grades, we used microdissection to obtain specific cohorts of cancer cells corresponding to the most common Gleason patterns (patterns 3, 4, and 5) from 29 radical prostatectomy samples. We paired each cancer sample with matched benign lumenal prostate epithelial cells and profiled transcript abundance levels by microarray analysis. We identified an 86-gene model capable of distinguishing low-grade (pattern 3) from high-grade (patterns 4 and 5) cancers. This model performed with 76% accuracy when applied to an independent set of 30 primary prostate carcinomas. Using tissue microarrays comprising >800 prostate samples, we confirmed a significant association between high levels of monoamine oxidase A expression and poorly differentiated cancers by immunohistochemistry. We also confirmed grade-associated levels of defender against death (DAD1) protein and HSD17 beta4 transcripts by immunohistochemistry and quantitative RT-PCR, respectively. The altered expression of these genes provides functional insights into grade-associated features of therapy resistance and tissue invasion. Furthermore, in identifying a profile of 86 genes that distinguish high- from low-grade carcinomas, we have generated a set of potential targets for modulating the development and progression of the lethal prostate cancer phenotype.

Adenocarcinoma↗

PubMed2006

Influence of surgical manipulation on prostate gene expression: implications for molecular correlates of treatment effects and disease prognosis.

PURPOSE: Measurements of tissue gene expression are increasingly used for disease stratification, clinical trial eligibility, and assessment of neoadjuvant therapy response. However, the method of tissue acquisition alone could significantly influence the expression of specific transcripts or proteins. This study examines whether there are transcript alterations associated with surgical resection of the prostate gland by radical retropubic prostatectomy. MATERIALS AND METHODS: Twelve patients with clinically localized prostate cancer underwent immediate in situ prostate biopsy after induction of anesthesia for radical prostatectomy. Ex vivo prostate biopsies were performed immediately after surgical removal. Prostate epithelium was acquired by laser-capture microdissection, and transcript abundance levels were quantitated by cDNA microarray hybridization and confirmed by quantitative polymerase chain reaction. Data were analyzed by paired, two-sample t test using Statistical Analysis of Microarray algorithms, and linear models were fit as a function of clinical characteristics. RESULTS: Of 5,753 cDNAs with measurable expression in prostate epithelium, 88 (1.5%) were altered as a result of surgery (false-discovery rate < or = 10%), representing 62 unique genes. These included transcripts encoding acute phase response proteins, IER2 and JUNB, and regulators of cell proliferation, p21Cip1 and KLF6. Of the clinical characteristics examined, including patient age, prostate volume, serum prostate-specific antigen, blood loss, and operative time, only gland volume was significantly and negatively associated with the magnitude of gene expression difference between pre- and postsurgical specimens. CONCLUSION: Surgical manipulation results in significant gene expression changes. Molecular analyses of surgical samples should recognize that transcript alterations occur rapidly, and these results are important when designing and analyzing molecular correlates of clinical studies.

Aged↗

PubMed2006

Combining results of microarray experiments: a rank aggregation approach.

As technology for microarray analysis becomes widespread, it is becoming increasingly important to be able to compare and combine the results of experiments that explore the same scientific question. In this article, we present a rank-aggregation approach for combining results from several microarray studies. The motivation for this approach is twofold; first, the final results of microarray studies are typically expressed as lists of genes, rank-ordered by a measure of the strength of evidence that they are functionally involved in the disease process, and second, using the information on this rank-ordered metric means that we do not have to concern ourselves with data on the actual expression levels, which may not be comparable across experiments. Our approach draws on methods for combining top-k lists from the computer science literature on meta-search. The meta-search problem shares several important features with that of combining microarray experiments, including the fact that there are typically few lists with many elements and the elements may not be common to all lists. We implement two meta-search algorithms, which use a Markov chain framework to convert pairwise preferences between list elements into a stationary distribution that represents an aggregate ranking (Dwork et al, 2001). We explore the behavior of the algorithms in hypothetical examples and a simulated dataset and compare their performance with that of an algorithm based on the order-statistics model of Thurstone (Thurstone, 1927). We apply all three algorithms to aggregate the results of five microarray studies of prostate cancer.

Algorithms↗

PubMed2006

The contributions of normal variation and genetic background to mammalian gene expression.

BACKGROUND: Qualitative and quantitative variability in gene expression represents the substrate for external conditions to exert selective pressures for natural selection. Current technologies allow for some forms of genetic variation, such as DNA mutations and polymorphisms, to be determined accurately on a comprehensive scale. Other components of variability, such as stochastic events in cellular transcriptional and translational processes, are less well characterized. Although potentially important, the relative contributions of genomic versus epigenetic and stochastic factors to variation in gene expression have not been quantified in mammalian species. RESULTS: In this study we compared microarray-based measures of hepatic transcript abundance levels within and between five different strains of Mus musculus. Within each strain 23% to 44% of all genes exhibited statistically significant differences in expression between genetically identical individuals (positive false discovery rate of 10%). Genes functionally associated with cell growth, cytokine activity, amine metabolism, and ubiquitination were enriched in this group. Genetic divergence between individuals of different strains also contributed to transcript abundance level differences, but to a lesser extent than intra-strain variation, with approximately 3% of all genes exhibiting inter-strain expression differences. CONCLUSION: These results indicate that although DNA sequence fixes boundaries for gene expression variability, there remain considerable latitudes of expression within these genome-defined limits that have the potential to influence phenotypes. The extent of normal or expected natural variability in gene expression may provide an additional level of phenotypic opportunity for natural selection.

Animals↗

PubMed2006

Telomerase activity in disseminated prostate cancer cells.

OBJECTIVE: To analyse telomerase activity in disseminated prostate cancer cells isolated from bone marrow aspirates taken from men with localized prostate cancer before radical prostatectomy (RP). PATIENTS AND METHODS: Disseminated epithelial prostate cancer cells were isolated from bone marrow aspirates from 69 men with localized prostate cancer before RP, by magnetic column-chromatography enrichment, followed by isolation of fluorescently labelled epithelial cells by micropipetting. We used pools of 10 non-epithelial bone marrow cells after tumour cell enrichment as control samples. These pure cell pools were tested for the presence of telomerase activity. RESULTS: In all, 49 of the patient samples contained disseminated prostate cancer cells. Homogeneous pools of 10 cells were obtained from 35 of these; 49% of the 35 specimens showed telomerase activity, whereas all five control samples did not. Telomerase activity in the 35 samples was not significantly associated with Gleason score, preoperative prostate-specific antigen level, tumour stage, or surgical margin status. Follow-up is continuing to assess an association with disease recurrence. CONCLUSION: This work shows the feasibility of isolating disseminated cancer cells for analysing individual or pooled cells. Compared to tissue staining, where telomerase is detected in 80-90% of samples, we found lower rates of telomerase activity in the disseminated tumour cells (49%). Telomerase-negative cells might provide information about cell dormancy, as telomerase is a marker of cell proliferation in immortal and cancer cells. Telomerase-positive cells might predict early disease recurrence, but a longer follow-up is needed to test this possibility.

Bone Marrow↗

PubMed2005

IGF-I and IGFBP-3 polymorphisms and risk of prostate cancer.

BACKGROUND: Insulin-like growth factor-I (IGF-I) is a potent mitogen for both normal and malignant prostate epithelial cells. The majority of circulating IGF-I is bound in a complex with IGF binding protein-3 (IGFBP-3), which in turn limits IGF-I bioavailability. Multiple studies suggest that higher IGF-I and/or lower IGFBP-3 serum levels are positively associated with prostate cancer risk. Several polymorphisms within the IGF-I and IGFBP-3 coding regions have been associated with increased serum protein levels. METHODS: To ascertain the potential relationship between serum levels and polymorphism, and prostate cancer risk, we investigated the role of two polymorphisms the IGF-I cytosine-adenosine (CA)-repeat and the IGFBP-3 Ala32Gly, and prostate cancer in a population-based, case-control, study of middle-aged men. RESULTS: We found no significant association between the IGFBP-3 Ala32Gly polymorphism and prostate cancer risk, even though the presence of at least one Gly allele did correlate with increased serum levels of IGFBP-3. For IGF-I, more controls (42%) than cases (38%) were homozygous for 19-CA-repeats (odds ratio, OR = 0.85; 95% confidence interval (CI) = 0.66-1.09). After stratifying by disease characteristics, 19-CA-repeat homozygous men displayed a decreased risk of low-grade disease (OR = 0.50; 95% CI = 0.27-0.93), but no associations were observed with more aggressive features of disease. Additionally, there was no correlation between mean serum IGF-I protein levels and IGF-I genotype in controls. CONCLUSIONS: Further evaluation of the IGF-I CA-repeat polymorphism and prostate cancer is necessary to determine if the modest risk reduction associated with the 19-CA-repeat homozygous state is observed in other study populations.

Adult↗

PubMed2005

Loss of stearoyl-CoA desaturase expression is a frequent event in prostate carcinoma.

Prostate carcinogenesis is influenced by genetic alterations resulting in a biochemical condition that favors cell proliferation and survival. Studies of prostate carcinoma using comparative genomic hybridization and cDNA microarray analysis indicate that numerous biochemical processes may be affected during cellular transformation and progression to an invasive phenotype. Among the consistently observed tumor-associated changes are alterations in fatty acid metabolism that influence diverse cellular activities such as signaling, energy utilization, and membrane fluidity. Increases in fatty acid synthase (FAS) levels have been shown to be one of the earliest and most frequent molecular alterations in prostate carcinogenesis. We sought to identify tumor-associated changes in the expression of genes with functional roles associated with lipid metabolism. Defined populations of normal and neoplastic prostate epithelium were acquired by laser capture microdissection and transcript levels were measured by cDNA microarray hybridization. We determined that stearoyl-CoA desaturase (SCD) transcripts were downregulated in cancer relative to normal epithelium. These results were confirmed by quantitative PCR. Further analysis by immunohistochemical evaluation of radical prostatectomy samples employed a quantitative scoring system with a range of 0-300. The median SCD expression levels were 150, 45 and 10 for normal, PIN and carcinoma samples, respectively. Statistically significant differential SCD expression between normal and cancerous epithelium was determined at the p=0.001 level, and between PIN and prostate carcinoma at the p=0.03 level. Of these cases, 92% overexpressed fatty acid synthase (FAS) in cancerous cells and 84.7% exhibited the signature of FAS overexpression and SCD loss in prostate carcinoma as compared to normal prostate epithelium. These results indicate that loss of SCD expression is a frequent event in prostate adenocarcinoma, and further supports a role for altered lipid metabolism as a factor in the process of carcinogenesis.

Blotting, Northern↗

PubMed2005

Regulation of hepatocyte activator inhibitor-1 expression by androgen and oncogenic transformation in the prostate.

Hepatocyte activator inhibitor-1 (HAI-1) is a transmembrane serine protease inhibitor that regulates the conversion of latent to active hepatocyte growth factor (HGF). Studies supporting a role for the HGF pathway in prostate carcinogenesis prompted an analysis of HAI-1 expression in the prostate. Here we analyze the regulation of HAI-1 expression by androgen, oncogenic transformation, and cancer progression. Immunohistochemical analysis revealed that HAI-1 expression was restricted to prostate epithelium, where staining occurred primarily in basal and atrophic luminal epithelial cells. Compared to normal glands, HAI-1 expression was significantly increased in localized prostate cancer and was present in most prostate cancer metastases. HAI-1 protein expression levels were sensitive to androgen in normal epithelium but not in cancer. Although androgen did not increase HAI-1 protein expression levels in LNCaP cells, it decreased HAI-1 surface expression, consistent with previous data from our group (Martin DB, Gifford DR, Wright ME, Keller A, Yi E, Goodlett DR, Aebersold R, Nelson PS: Quantitative proteomic analysis of proteins released by neoplastic prostate epithelium. Cancer Res 2004, 64:347-355). HAI-1 overexpression in cancer was predictive of prostate-specific antigen recurrence (relative risk, 1.24). These results suggest that HAI-1 regulates the HGF Met axis on prostate epithelial cells and influences HGF mediated tumor invasion and metastasis.

Androgens↗

PubMed2005

Analyzing patterns of staining in immunohistochemical studies: application to a study of prostate cancer recurrence.

BACKGROUND: Immunohistochemical studies use antibodies to stain tissues with the goal of quantifying protein expression. However, protein expression is often heterogeneous resulting in variable degrees and patterns of staining. This problem is particularly acute in prostate cancer, where tumors are infiltrative and heterogeneous in nature. In this article, we introduce analytic approaches that explicitly consider both the frequency and intensity of tissue staining. METHODS: Compositional data analysis is a technique used to analyze vectors of unit-sum proportions, such as those obtained from soil sample studies or species abundance surveys. We summarized specimen staining patterns by the proportion of cells staining at mild, moderate, and intense levels and used compositional data analysis to summarize and compare the resulting staining profiles. RESULTS: In a study of Syndecan-1 staining patterns among 44 localized prostate cancer cases with Gleason score 7 disease, compositional data analysis did not detect a statistically significant difference between the staining patterns in recurrent (n = 22) versus nonrecurrent (n = 22) patients. Results indicated only modest increases in the proportion of cells staining at a moderate intensity in the recurrent group. In contrast, an analysis that compared quantitative scores across groups indicated a (borderline) significant increase in staining in the recurrent group (P = 0.05, t test). CONCLUSIONS: Compositional data analysis offers a novel analytic approach for immunohistochemical studies, providing greater insight into differences in staining patterns between groups, but possibly lower statistical power than existing, score-based methods. When appropriate, we recommend conducting a compositional data analysis in addition to a standard score-based analysis.

Biomarkers, Tumor↗