Bao Ling Adam

SELDI-TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma†

Proteomic profiling of serum is an emerging technique to identify new biomarkers indicative of disease severity and progression. The objective of our study was to assess the use of surface‐enhanced laser desorption/ionization time‐of‐flight mass spectrometry (SELDI‐TOF MS) to identify multiple serum protein biomarkers for detection of liver disease progression to hepatocellular carcinoma (HCC). A cohort of 170 serum samples obtained from subjects in the United States with no liver disease (n = 39), liver diseases not associated with cirrhosis (n = 36), cirrhosis (n = 38), or HCC (n = 57) were applied to metal affinity protein chips for protein profiling by SELDI‐TOF MS. Across the four test groups, 38 differentially expressed proteins were used to generate multiple decision classification trees to distinguish the known disease states. Analysis of a subset of samples with only hepatitis C virus (HCV)‐related disease was emphasized. The serum protein profiles of control patients were readily distinguished from each HCV‐associated disease state. Two‐way comparisons of chronic hepatitis C, HCV cirrhosis, or HCV‐HCC versus healthy had a sensitivity/specificity range of 74% to 95%. For distinguishing chronic HCV from HCV‐HCC, a sensitivity of 61% and a specificity of 76% were obtained. However, when the values of known serum markers α fetoprotein, des‐gamma carboxyprothrombin, and GP73 were combined with the SELDI peak values, the sensitivity and specifity improved to 75% and 92%, respectively. In conclusion, SELDI‐TOF MS serum profiling is able to distinguish HCC from liver disease before cirrhosis as well as cirrhosis, especially in patients with HCV infection compared with other etiologies. (HEPATOLOGY 2005;41:634–642.)

An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers

Discovery of “signature” protein profiles that distinguish disease states (eg, malignant, benign, and normal) is a key step towards translating recent advancements in proteomic technologies into clinical utilities. Protein data generated from mass spectrometers are, however, large in size and have complex features due to complexities in both biological specimens and interfering biochemical/physical processes of the measurement procedure. Making sense out of such high-dimensional complex data is challenging and necessitates the use of a systematic data analytic strategy. We propose here a data processing strategy for two major issues in the analysis of such mass-spectrometry-generated proteomic data: (1) separation of protein “signals” from background “noise” in protein intensity measurements and (2) calibration of protein mass/charge measurements across samples. We illustrate the two issues and the utility of the proposed strategy using data from a prostate cancer biomarker discovery project as an example.

Data reduction using a discrete wavelet transform in discriminant analysis of very high dimensionality data.

We present a method of data reduction using a wavelet transform in discriminant analysis when the number of variables is much greater than the number of observations. The method is illustrated with a prostate cancer study, where the sample size is 248, and the number of variables is 48,538 (generated using the ProteinChip technology). Using a discrete wavelet transform, the 48,538 data points are represented by 1271 wavelet coefficients. Information criteria identified 11 of the 1271 wavelet coefficients with the highest discriminatory power. The linear classifier with the 11 wavelet coefficients detected prostate cancer in a separate test set with a sensitivity of 97% and specificity of 100%.

Serum Protein Expression Profiling for Cancer Detection: Validation of a SELDI-Based Approach for Prostate Cancer

Multiple studies have reported that analysis of serum and other bodily fluids using surface enhanced laser desorption/ionization time of flight mass spectroscopy (SELDI-TOF-MS) can identify a “fingerprint” or “signature” of spectral peaks that can separate patients with a specific disease from normal control patients. Ultimately, classification by SELDI-TOF-MS relies on spectral differences in position and amplitude of resolved peaks. Since the reproducibility of quantitation, resolution and mass accuracy of the SELDI-TOF-MS, or any high throughput mass spectrometric technique, has never been determined this method has come under some skepticism as to its clinical usefulness. This manuscript describes a detailed design of a three-phase study to validate the clinical usefulness of SELDI-TOF-MS in the identification of patients with prostatic adenocarcinoma (PCA). At the end of this validation study, the usefulness of the general SELDI-TOF-MS approach to identifying patients with PCA will be demonstrated and how it compares with PCA diagnosis by measuring prostate specific antigen.

Proteomic identification of serum biomarkers for head and neck cancer surveillance.

Serum protein profiling by SELDI‐TOF‐MS distinguishes pretreatment and post‐treatment samples from patients with head and neck squamous cell cancer (HNSCC) by disease status (disease‐free or recurrence) with a high degree of sensitivity and specificity. We sought to identify biomarkers for recurrence with potential utility for surveillance and incorporated 2‐D DIGE and MALDI‐TOF‐MS techniques to overcome the limitations of SELDI‐TOF‐MS in determining biomarker identity.

Effects of Chlorpyrifos and Chlorpyrifos-Oxon on the Dynamics and Movement of Mitochondria in Rat Cortical Neurons

Organophosphate (OP)-based pesticides have been used extensively for decades, and as a result, they have become almost ubiquitous in our environment. There is clinical and animal evidence to suggest that chronic exposures to OPs can lead to cognitive dysfunction and other neurological abnormalities, although the mechanism for these effects is unknown. We previously reported that repeated, subthreshold exposures (defined as doses not associated with signs of acute toxicity) to the commonly used OP chlorpyrifos (CPF) resulted in protracted impairments in the performance of attention and memory-related tasks in rodents as well as deficits in axonal transport ex vivo (in the sciatic nerve). Here, we investigated the effects of CPF and its active metabolite CPF oxon (CPO) on the dynamics and movement of mitochondria in rat primary cortical neurons using time-lapse imaging techniques. Exposure to CPF (1.0–20.0 μM) or CPO (5.0 nM–20.0 μM) for 1 or 24 h resulted in a concentration-dependent increase in mitochondrial length, a decrease in mitochondrial number (indicative of increased fusion events), and a decrease in their movement in axons. The changes occurred at concentrations of CPF and CPO that did not inhibit acetylcholinesterase activity (the commonly cited mechanism of acute OP toxicity), and they were not blocked by cholinergic receptor antagonists. Furthermore, the changes did not seem to be associated with direct (OP-related) effects on mitochondrial viability or function (i.e., mitochondrial membrane potential or ATP production). The results suggest that an underlying mechanism of organophosphate-based deficits in cognitive function might involve alterations in mitochondrial dynamics and/or their transport in axons.

Repeated exposure to chlorpyrifos leads to prolonged impairments of axonal transport in the living rodent brain

The toxicity of the class of chemicals known as the organophosphates (OP) is most commonly attributed to the inhibition of the enzyme acetylcholinesterase. However, there is significant evidence that this mechanism may not account for all of the deleterious neurologic and neurobehavioral symptoms of OP exposure, especially those associated with levels that produce no overt signs of acute toxicity. In the study described here we evaluated the effects of the commonly used OP-pesticide, chlorpyrifos (CPF) on axonal transport in the brains of living rats using manganese (Mn(2+))-enhanced magnetic resonance imaging (MEMRI) of the optic nerve (ON) projections from the retina to the superior colliculus (SC). T1-weighted MEMRI scans were evaluated at 6 and 24h after intravitreal injection of Mn(2+). As a positive control for axonal transport deficits, initial studies were conducted with the tropolone alkaloid colchicine administered by intravitreal injection. In subsequent studies both single and repeated exposures to CPF were evaluated for effects on axonal transport using MEMRI. As expected, intravitreal injection of colchicine (2.5μg) produced a robust decrease in transport of Mn(2+) along the optic nerve (ON) and to the superior colliculus (SC) (as indicated by the reduced MEMRI contrast). A single subcutaneous (s.c.) injection of CPF (18.0mg/kg) was not associated with significant alterations in the transport of Mn(2+). Conversely, 14-days of repeated s.c. exposure to CPF (18.0mg/kg/day) was associated with decreased transport of Mn(2+) along the ONs and to the SC, an effect that was also present after a 30-day (CPF-free) washout period. These results indicate that repeated exposures to a commonly used pesticide, CPF can result in persistent alterations in axonal transport in the living mammalian brain. Given the fundamental importance of axonal transport to neuronal function, these observations may (at least in part) explain some of the long term neurological deficits that have been observed in humans who have been repeatedly exposed to doses of OPs not associated with acute toxicity.

Evaluation of nicotine and cotinine analogs as potential neuroprotective agents for Alzheimer’s disease

The currently available therapies for Alzheimers disease (AD) and related forms of dementia are limited by modest efficacy, adverse side effects, and the fact that they do not prevent the relentless progression of the illness. The purpose of the studies described here was to investigate the neuroprotective effects of the nicotine metabolite cotinine as well as a small series of cotinine and nicotine analogs (including stereoisomers) and to compare their effects to the four clinically prescribed AD therapies.

A mixture model approach to the tests of concordance and discordance between two large-scale experiments with two-sample groups

MOTIVATION Due to advances in experimental technologies, such as microarray, mass spectrometry and nuclear magnetic resonance, it is feasible to obtain large-scale data sets, in which measurements for a large number of features can be simultaneously collected. However, the sample sizes of these data sets are usually small due to their relatively high costs, which leads to the issue of concordance among different data sets collected for the same study: features should have consistent behavior in different data sets. There is a lack of rigorous statistical methods for evaluating this concordance or discordance. METHODS Based on a three-component normal-mixture model, we propose two likelihood ratio tests for evaluating the concordance and discordance between two large-scale data sets with two sample groups. The parameter estimation is achieved through the expectation-maximization (E-M) algorithm. A normal-distribution-quantile-based method is used for data transformation. RESULTS To evaluate the proposed tests, we conducted some simulation studies, which suggested their satisfactory performances. As applications, the proposed tests were applied to three SELDI-MS data sets with replicates. One data set has replicates from different platforms and the other two have replicates from the same platform. We found that data generated by SELDI-MS showed satisfactory concordance between replicates from the same platform but unsatisfactory concordance between replicates from different platforms. AVAILABILITY The R codes are freely available at http://home.gwu.edu/~ylai/research/Concordance.

Use of Combination Proteomic Analysis to Demonstrate Molecular Similarity of Head and Neck Squamous Cell Carcinoma Arising From Different Subsites

OBJECTIVE To evaluate head and neck squamous cell carcinomas (HNSCCs) for differences in protein expression between oral cavity, oropharynx, larynx, and hypopharynx subsites. DESIGN Retrospective proteomic analysis using tissue microarray (TMA) and 2-dimensional difference gel electrophoresis (2D-DIGE). For the TMA, automated quantitative protein expression analysis was used to interrogate levels of 4 cell-cycle regulatory proteins chosen for their known roles in cancer (cyclin D1, p53, Rb, and p14). For the 2D-DIGE, lesional and normal adjacent tissues were enriched by laser capture microdissection. Total protein was extracted, analyzed by 2D-DIGE with saturation dye labeling, and evaluated for relative abundance levels of individual protein spots. SETTING Two tertiary-care academic medical centers. PATIENTS Seventy-one patients with HNSCC for TMA, and 14 patients with HNSCC with frozen tumor and normal tissue for 2D-DIGE. RESULTS The automated quantitative analysis of protein expression analysis revealed no difference between subsite for cyclin D1, p53, Rb, or p14 expression. The 2D-DIGE study was based on 28 gels (14 cancer gels and 14 adjacent normal gels), and 732 spots were identified as matching across more than 90% of gels. Significance was evaluated based on false discovery rate (FDR) estimated from permuted data sets. There were no significant differences in protein expression between subsites (FDR greater than or equal to 30% in all instances). CONCLUSIONS Observed differences in outcomes between HNSCCs from different subsites may not reflect differences in tumor biologic characteristics between subsites. Rather, it is possible that observed clinical heterogeneity among HNSCCs may be based on other factors, such as viral vs chemical carcinogenesis.