Optimization of laser capture microdissection and RNA amplification for gene expression profiling of prostate cancer

BACKGROUND: To discover prostate cancer biomarkers, we profiled gene expression in benign and malignant cells laser capture microdissected (LCM) from prostate tissues and metastatic prostatic adenocarcinomas. Here we present methods developed, optimized, and validated to obtain high quality gene expression data. RESULTS: RNase inhibitor was included in solutions used to stain frozen tissue sections for LCM, which improved RNA quality significantly. Quantitative PCR assays, requiring minimal amounts of LCM RNA, were developed to determine RNA quality and concentration. SuperScript II™ reverse transcriptase was replaced with SuperScript III™, and SpeedVac concentration was eliminated to optimize linear amplification. The GeneChip(® )IVT labeling kit was used rather than the Enzo BioArray™ HighYield™ RNA transcript labeling kit since side-by-side comparisons indicated high-end signal saturation with the latter. We obtained 72 μg of labeled complementary RNA on average after linear amplification of about 2 ng of total RNA. CONCLUSION: Unsupervised clustering placed 5/5 normal and 2/2 benign prostatic hyperplasia cases in one group, 5/7 Gleason pattern 3 cases in another group, and the remaining 2/7 pattern 3 cases in a third group with 8/8 Gleason pattern 5 cases and 3/3 metastatic prostatic adenocarcinomas. Differential expression of alpha-methylacyl coenzyme A racemase (AMACR) and hepsin was confirmed using quantitative PCR

Comparability of the tandem-R andIMx assays for the measurement of serum prostate-specific antigen

Objectives.To assess the comparability of the Tandem-R and IMx serumprostate-specific antigen (PSA) assays across levels of the ratio of free-to-total serum PSA found in a community-based population of healthy men.Methods.Banked serum samples from the baseline component of the Olmsted CountyStudy of Urinary Symptoms and Health Status Among Men were thawed and analyzed using the Tandem-R and IMx PSA assays. Serum levels also were determined for the free, noncomplexed form of PSA, PSA complexed to alpha-1 antichymotrypsin, and total PSA with a research-based immunofluorometric assay.Results.The results of the Tandem-R and IMx assays were strongly correlated at alllevels of the ratio of free-to-total serum PSA. The Spearman correlation coefficients ranged from 0.87 to 0.98 (all p Conclusions.For the majority of men, results of the Tandem-R and IMx PSA assays were virtually identical. The small differences found would not be of clinical significance for most men but should be considered when comparing results of different assays in sequential determinations for a specific man.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31299/1/0000205.pd

Sex and Ethnic Differences in 47 Candidate Proteomic Markers of Cardiovascular Disease: The Mayo Clinic Proteomic Markers of Arteriosclerosis Study

Cardiovascular disease (CVD) susceptibility differs between men and women and varies with ethnicity. This variability is not entirely explained by conventional CVD risk factors. We examined differences in circulating levels of 47 novel protein markers of CVD in 2561 men and women of African-American (AA) and non-Hispanic White (NHW) ethnicity, enrolled at geographically distinct sites.Participants (1,324 AAs, mean age 63.5 y, 71% women; 1,237 NHWs, mean age 58.9 y, 57% women) belonged to sibships ascertained on the basis of hypertension. Solid-phase immunoassays and immunoturbidometric, clot-based, chromogenic, and electrophoretic assays were used to measure the 47 protein markers in plasma or serum. Marker levels were log transformed and outliers were adjusted to within 4 SD. To identify markers independently associated with sex or ethnicity, we employed multivariable regression analyses that adjusted for conventional risk factors, prior history of CVD, medication use and lifestyle factors (physical activity, alcohol consumption and education). Generalized estimating equations were used to correct for intrafamilial correlations. After adjustment for the above covariates, female sex was associated with higher levels of 29 markers and lower levels of 6 markers. Female sex was independently associated with higher levels of several inflammatory markers as well as lipoproteins, adipokines, natriuretic peptides, vasoconstrictor peptides and markers of calcification and thrombosis. AA ethnicity was associated with higher levels of 19 markers and lower levels of 6 markers, including higher levels of several inflammatory makers, higher leptin and lower adiponectin levels, lower levels of vasodilator-natriuretic peptides, higher levels of vasoconstrictor-antidiuretic peptides and markers of calcification and thrombosis.Plasma levels of several novel protein markers of CVD differ significantly in the context of sex and ethnicity. These results have implications for individualized CVD risk assessment

Adrenomedullin is up-regulated in patients with pancreatic cancer and causes insulin resistance in β cells and mice

New-onset diabetes in patients with pancreatic cancer is likely to be a paraneoplastic phenomenon caused by tumor-secreted products. We aimed to identify the diabetogenic secretory product(s) of pancreatic cancer. Methods: Using microarray analysis, we identified adrenomedullin as a potential mediator of diabetes in patients with pancreatic cancer. Adrenomedullin was up-regulated in pancreatic cancer cell lines, in which supernatants reduced insulin signaling in beta cell lines. We performed quantitative reverse-transcriptase polymerase chain reaction and immunohistochemistry on human pancreatic cancer and healthy pancreatic tissues (controls) to determine expression of adrenomedullin messenger RNA and protein, respectively. We studied the effects of adrenomedullin on insulin secretion by beta cell lines and whole islets from mice and on glucose tolerance in pancreatic xenografts in mice. We measured plasma levels of adrenomedullin in patients with pancreatic cancer, patients with type 2 diabetes mellitus, and individuals with normal fasting glucose levels (controls). Results: Levels of adrenomedullin messenger RNA and protein were increased in human pancreatic cancer samples compared with controls. Adrenomedullin and conditioned media from pancreatic cell lines inhibited glucose-stimulated insulin secretion from beta cell lines and islets isolated from mice; the effects of conditioned media from pancreatic cancer cells were reduced by small hairpin RNA-mediated knockdown of adrenomedullin. Conversely, overexpression of adrenomedullin in mice with pancreatic cancer led to glucose intolerance. Mean plasma levels of adrenomedullin (femtomoles per liter) were higher in patients with pancreatic cancer compared with patients with diabetes or controls. Levels of adrenomedullin were higher in patients with pancreatic cancer who developed diabetes compared those who did not. Conclusions: Adrenomedullin is up-regulated in patients with pancreatic cancer and causes insulin resistance in β cells and mice.Fil: Aggarwal, Gaurav. Mayo Clinic College of Medicine; Estados UnidosFil: Ramachandran, Vijaya. University of Texas Health Science Center at Houston. University of Texas Md Anderson Cancer Center; Estados UnidosFil: Javeed, Naureen. Mayo Clinic College of Medicine; Estados UnidosFil: Arumugam, Thiruvengadam. University of Texas Health Science Center at Houston. University of Texas Md Anderson Cancer Center; Estados UnidosFil: Dutta, Shamit. Mayo Clinic College of Medicine; Estados UnidosFil: Klee, George G.. Mayo Clinic College of Medicine; Estados UnidosFil: Klee, Eric W.. Mayo Clinic College of Medicine; Estados UnidosFil: Smyrk, Thomas C.. Mayo Clinic College of Medicine; Estados UnidosFil: Bamlet, William. Mayo Clinic College of Medicine; Estados UnidosFil: Han, Jing Jing. Mayo Clinic College of Medicine; Estados UnidosFil: Rumie Vittar, Natalia Belen. Mayo Clinic College of Medicine; Estados Unidos. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Biología Molecular. Sección Química Biológica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: De Andrade, Mariza. Mayo Clinic College of Medicine; Estados UnidosFil: Mukhopadhyay, Debabrata. Mayo Clinic College of Medicine; Estados UnidosFil: Petersen, Gloria M.. Mayo Clinic College of Medicine; Estados UnidosFil: Fernandez Zapico, Martin Ernesto. Mayo Clinic College of Medicine; Estados UnidosFil: Logsdon, Craig D.. University of Texas Health Science Center at Houston. University of Texas Md Anderson Cancer Center; Estados UnidosFil: Chari, Suresh T.. Mayo Clinic College of Medicine; Estados Unido

Reference intervals comparison of calculation methods and evaluation of procedures for merging reference measurements fromTwo US medical centers

Objectives: To analyze consistency of reference limits and widths of reference intervals (RIs) calculated by six procedures and evaluate a protocol for merging intrainstitutional reference data. Methods: The differences between reference limits were compared with "optimal" bias goals. Also, widths of the RIs were compared. RIs were calculated using Mayo-SAS quantile, EP Evaluator, and four International Federation of Clinical Chemistry and Laboratory Medicine methods: parametric and nonparametric (NP) with and without latent abnormal values exclusion (LAVE). Regression parameters from cotested samples were evaluated for harmonizing intrainstitutional reference data. Results: Mayo-SAS quintile, LAVE(-) NP, and EP Evaluator generated similar RIs, but these RIs often were wider than RIs from parametric procedures. LAVE procedures generated narrower RIs for nutritional and inflammatory markers. Transformation with regression parameters did not ensure homogeneity of merged data. Conclusions: Parametric methods are recommended when inappropriate values cannot be excluded. The nonparametric procedures may generate wider RIs. Data sets larger than 200 are recommended for robust estimates. Caution should be exercised when merging intrainstitutional data

Impact of sample acquisition and linear amplification on gene expression profiling of lung adenocarcinoma: laser capture micro-dissection cell-sampling versus bulk tissue-sampling

<p>Abstract</p> <p>Background</p> <p>The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.</p> <p>Methods</p> <p>Expression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.</p> <p>Results</p> <p>The direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.</p> <p>Conclusion</p> <p>LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.</p

A Tissue Biomarker Panel Predicting Systemic Progression after PSA Recurrence Post-Definitive Prostate Cancer Therapy

Many men develop a rising PSA after initial therapy for prostate cancer. While some of these men will develop a local or metastatic recurrence that warrants further therapy, others will have no evidence of disease progression. We hypothesized that an expression biomarker panel can predict which men with a rising PSA would benefit from further therapy.A case-control design was used to test the association of gene expression with outcome. Systemic (SYS) progression cases were men post-prostatectomy who developed systemic progression within 5 years after PSA recurrence. PSA progression controls were matched men post-prostatectomy with PSA recurrence but no evidence of clinical progression within 5 years. Using expression arrays optimized for paraffin-embedded tissue RNA, 1021 cancer-related genes were evaluated-including 570 genes implicated in prostate cancer progression. Genes from 8 previously reported marker panels were included. A systemic progression model containing 17 genes was developed. This model generated an AUC of 0.88 (95% CI: 0.84-0.92). Similar AUCs were generated using 3 previously reported panels. In secondary analyses, the model predicted the endpoints of prostate cancer death (in SYS cases) and systemic progression beyond 5 years (in PSA controls) with hazard ratios 2.5 and 4.7, respectively (log-rank p-values of 0.0007 and 0.0005). Genes mapped to 8q24 were significantly enriched in the model.Specific gene expression patterns are significantly associated with systemic progression after PSA recurrence. The measurement of gene expression pattern may be useful for determining which men may benefit from additional therapy after PSA recurrence

Loss-of-function mutations in UDP-Glucose 6-Dehydrogenase cause recessive developmental epileptic encephalopathy

AbstractDevelopmental epileptic encephalopathies are devastating disorders characterized by intractable epileptic seizures and developmental delay. Here, we report an allelic series of germline recessive mutations in UGDH in 36 cases from 25 families presenting with epileptic encephalopathy with developmental delay and hypotonia. UGDH encodes an oxidoreductase that converts UDP-glucose to UDP-glucuronic acid, a key component of specific proteoglycans and glycolipids. Consistent with being loss-of-function alleles, we show using patients’ primary fibroblasts and biochemical assays, that these mutations either impair UGDH stability, oligomerization, or enzymatic activity. In vitro, patient-derived cerebral organoids are smaller with a reduced number of proliferating neuronal progenitors while mutant ugdh zebrafish do not phenocopy the human disease. Our study defines UGDH as a key player for the production of extracellular matrix components that are essential for human brain development. Based on the incidence of variants observed, UGDH mutations are likely to be a frequent cause of recessive epileptic encephalopathy.</jats:p

Loss-of-function mutations in UDP-Glucose 6-Dehydrogenase cause recessive developmental epileptic encephalopathy

Developmental epileptic encephalopathies are devastating disorders characterized by intractable epileptic seizures and developmental delay. Here, we report an allelic series of germline recessive mutations in UGDH in 36 cases from 25 families presenting with epileptic encephalopathy with developmental delay and hypotonia. UGDH encodes an oxidoreductase that converts UDP-glucose to UDP-glucuronic acid, a key component of specific proteoglycans and glycolipids. Consistent with being loss-of-function alleles, we show using patients’ primary fibroblasts and biochemical assays, that these mutations either impair UGDH stability, oligomerization, or enzymatic activity. In vitro, patient-derived cerebral organoids are smaller with a reduced number of proliferating neuronal progenitors while mutant ugdh zebrafish do not phenocopy the human disease. Our study defines UGDH as a key player for the production of extracellular matrix components that are essential for human brain development. Based on the incidence of variants observed, UGDH mutations are likely to be a frequent cause of recessive epileptic encephalopathy