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PubMed2006

Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry.

AIM: To detect the new serum biomarkers for colorectal cancer (CRC) by serum protein profiling with surface-enhanced laser desorption ionisation--time of flight mass spectrometry (SELDI-TOF MS). METHODS: Two independent serum sample sets were analysed separately with the ProteinChip technology (set A: 40 CRC+49 healthy controls; set B: 37 CRC+31 healthy controls), using chips with a weak cation exchange moiety and buffer pH 5. Discriminative power of differentially expressed proteins was assessed with a classification tree algorithm. Sensitivities and specificities of the generated classification trees were obtained by blindly applying data from set A to the generated trees from set B and vice versa. CRC serum protein profiles were also compared with those from breast, ovarian, prostate, and non-small cell lung cancer. RESULTS: Mass-to-charge ratios (m/z) 3.1x10(3), 3.3x10(3), 4.5x10(3), 6.6x10(3) and 28x10(3) were used as classifiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%. Most of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3x10(3), main classifier in most trees, was a doubly charged form of the 6.6x10(3)-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1x10(3) was identified as an N-terminal fragment of albumin, and m/z 28x10(3) as apolipoprotein A-I. CONCLUSION: SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring.

Algorithms↗

PubMed2005

Expression of bFGF/FGFR-1 and vascular proliferation related to clinicopathologic features and tumor progress in localized prostate cancer.

Microvessel density (MVD) has been associated with progression of prostate cancer. Although basic fibroblast growth factor (bFGF) is a known endothelial mitogen, the prognostic role of bFGF and its receptor FGFR-1 in prostate cancer has been controversial. The aim of our study was to examine the tissue distribution and prognostic significance of bFGF, FGFR-1, and microvascular proliferation. Sections from 104 radical prostatectomy specimens were examined by factor VIII/Ki-67 staining for proliferating capillary index (PCI) and MVD, and tissue microarray sections were immunostained for bFGF and FGFR-1. Increased PCI (median 0.49%) was related to strong stromal expression of bFGF (P=0.003) but was without prognostic impact. Strong bFGF staining was associated with well-differentiated tumors, no capsular penetration, low serum-prostate-specific antigen (s-PSA), low tumor cell proliferation, and increased time to biochemical failure (P=0.007), and was of independent prognostic importance in multivariate survival analysis. bFGF expression in vessels was associated with low MVD (P=0.0003). In contrast, strong tumor cell FGFR-1 expression was related to high preoperative s-PSA. Thus, increased stromal and vessel bFGF was associated with less aggressive tumors. Our findings indicate a complex relationship between bFGF/FGFR-1 expression and prognosis of prostate cancer. Vascular proliferation revealed no prognostic impact in this study.

Biomarkers, Tumor↗

PubMed2006

Proteomics: recent applications and new technologies.

Interest in proteomics as a tool for drug development and a myriad of other applications continues to expand at a rapid rate. Proteomic analyses have recently been conducted on tissues, biofluids, subcellular components and enzymatic pathways as well as various disease and toxicological states, in both animal models and man. In addition, several recent studies have attempted to integrate proteomics data with genomics and/or metabonomics data in a systems biology approach. The translation of proteomic technology and bioinformatics tools to clinical samples, such as in the areas of disease and toxicity biomarkers, represents one of the major opportunities and challenges facing this field. An ongoing challenge in proteomics continues to be the analysis of the serum proteome due to the vast number and complexity of proteins estimated to be present in this biofluid. Aside from the removal of the most abundant proteins, a number of interesting approaches have recently been suggested that may help reduce the overall complexity of serum analysis. In keeping with the increasing interest in applications of proteomics, the tools available for proteomic analyses continue to improve and expand. For example, enhanced tools (such as software and labeling procedures) continue to be developed for the analysis of 2D gels and protein quantification. In addition, activity-based probes are now being used to tag, enrich and isolate distinct sets of proteins based on enzymatic activity. One of the most active areas of development involves microarrays. Antibody-based microarrays have recently been released as commercial products while numerous additional capture agents (e.g. aptamers) and many additional types of microarrays are being explored.

Animals↗

PubMed2003

Proteomics: advanced technology for the analysis of cellular function.

Proteomics developed initially from the decade-long study of comprehensive protein visualization on two-dimensional electrophoresis gels has been expanded by mass spectrometry and the growth in searchable sequence databases. Currently, by use of more sophisticated technology such as a combination of multidimensional chromatography and mass spectrometry, thousands of proteins can automatically be identified in a day along with semiquantitative information on differential-protein expression. As with differential gene expression by cDNA-chips, the differential-protein analysis is useful for monitoring and identifying proteins involved in various physiological changes in cells or organisms, although the analysis alone does not necessarily provide information regarding the cause of the change or the function of the proteins. However, proteomics also provides the tools to expand into more sophisticated biochemical approaches, such as the study of protein interactions that can be determined directly by performing a pull-down assay with a bait protein followed by mass spectrometric identification of the bound proteins. Proteomics, thus, is useful for both large-scale surveys of proteins and detailed studies of the functional relationships among the proteins of interest. Certainly this approach can be applicable to the assessment of amino acid adequacy and safety.

Animals↗

PubMed2002

High-throughput cell analysis using multiplexed array technologies.

The desire for more biologically relevant data from primary screening has resulted in a dramatic increase of cell-based assays in HTS labs. Consequently, new cell-array technologies are being developed to increase the quality and quantity of data emerging from such screens. These technologies take the form of both positional and non-positional formats, each with their own advantages. Notably, screens using these technologies generate databases of high-quality data that can be analyzed in ways currently not possible. The power of cell-based assays combined with new array and analytical technologies will enable the condensation of serial drug discovery processes, thereby decreasing the time and cost of taking a hit compound into clinical trials. Here, we compare array strategies being developed towards the goal of integrating multiplexed cell-based assays into HTS.

Animals↗

PubMed2004

Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays.

We developed a new DNA microarray-based technology, called protein binding microarrays (PBMs), that allows rapid, high-throughput characterization of the in vitro DNA binding-site sequence specificities of transcription factors in a single day. Using PBMs, we identified the DNA binding-site sequence specificities of the yeast transcription factors Abf1, Rap1 and Mig1. Comparison of these proteins' in vitro binding sites with their in vivo binding sites indicates that PBM-derived sequence specificities can accurately reflect in vivo DNA sequence specificities. In addition to previously identified targets, Abf1, Rap1 and Mig1 bound to 107, 90 and 75 putative new target intergenic regions, respectively, many of which were upstream of previously uncharacterized open reading frames. Comparative sequence analysis indicated that many of these newly identified sites are highly conserved across five sequenced sensu stricto yeast species and, therefore, are probably functional in vivo binding sites that may be used in a condition-specific manner. Similar PBM experiments should be useful in identifying new cis regulatory elements and transcriptional regulatory networks in various genomes.

Base Sequence↗

PubMed2003

Detection of renal cell carcinoma-associated markers via proteome- and other 'ome'-based analyses.

Proteome analysis has rapidly developed in the post-genome era and is now widely accepted as the complementary technology for genetic profiling. It has been shown to be a powerful tool for studying human diseases and for identifying novel prognostic, diagnostic and therapeutic markers. This review focuses on the identification of new biomarkers and therapeutic targets for renal cell carcinoma using different 'ome'-based technologies.

Biomarkers, Tumor↗

PubMed2002

On-chip microextraction for proteomic sample preparation of in-gel digests.

Despite the high sensitivity and relatively high tolerance for contaminants of matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) there is often a need to purify and concentrate the sample solution, especially after in-gel digestion of proteins separated by two-dimensional gel electrophoresis (2-DE). A silicon microextraction chip (SMEC) for sample clean-up and trace enrichment of peptides was manufactured and investigated. The microchip structure was used to trap reversed-phase chromatography media (POROS R2 beads) that facilitates sample purification/enrichment of contaminated and dilute samples prior to the MALDI-TOF MS analysis. The validity of the SMEC sample preparation technique was successfully investigated by performing analysis on a 10 nM peptide mixture containing 2 m urea in 0.1 m phosphate-buffered saline with MALDI-TOF MS. It is demonstrated that the microchip sample clean-up and enrichment of peptides can facilitate identification of proteins from 2-DE separations. The microchip structure was also used to trap beads immobilized with trypsin, thereby effectively becoming a microreactor for enzymatic digestion of proteins. This microreactor was used to generate a peptide map from a 100 nM bovine serum albumin sample.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2005

Multianalyte profiling of serum cytokines for detection of pancreatic cancer.

Early detection of pancreatic cancer might improve clinical outcome. Significant alterations in the levels of individual serum cytokines have been reported in pancreatic cancer. We hypothesized that a multicytokine panel could serve as biomarkers for pancreatic cancer. To evaluate the diagnostic utility of such a panel, we have utilized a novel multianalyte LabMAP profiling technology that allows simultaneous measurement of multiple markers. In this study, a panel of 31 serological markers including cytokines, chemokines, growth and angiogenic factors in combination with CA 19-9 was analyzed in sera of pancreatic cancer patients, patients with chronic pancreatitis, and matched control healthy subjects. Statistical analysis identified a multicytokine panel that was able to distinguish pancreatic cancer from healthy controls with a sensitivity of 85.7% and specificity of 92.3%, which was superior to performance of CA 19-9 alone. Importantly, a multicytokine panel allowed the discrimination of pancreatic cancer from chronic pancreatitis with high sensitivity of 98% and specificity of 96.4%. In conclusion, we demonstrated that analysis of multiple serum cytokines using a novel LabMAP technology is a promising approach for development of a diagnostic assay for pancreatic cancer.

Biomarkers, Tumor↗

PubMed2005

Analysis of Human Proteome Organization Plasma Proteome Project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: multi-institution correlation of spectra and identification of biomarkers.

We report on a multicenter analysis of HUPO reference specimens using SELDI-TOF MS. Eight sites submitted data obtained from serum and plasma reference specimen analysis. Spectra from five sites passed preliminary quality assurance tests and were subjected to further analysis. Intralaboratory CVs varied from 15 to 43%. A correlation coefficient matrix generated using data from these five sites demonstrated high level of correlation, with values >0.7 on 37 of 42 spectra. More than 50 peaks were differentially present among the various sample types, as observed on three chip surfaces. Additionally, peaks at approximately 9200 and approximately 15,950 m/z were present only in select reference specimens. Chromatographic fractionation using anion-exchange, membrane cutoff, and reverse phase chromatography, was employed for protein purification of the approximately 9200 m/z peak. It was identified as the haptoglobin alpha subunit after peptide mass fingerprinting and high-resolution MS/MS analysis. The differential expression of this protein was confirmed by Western blot analysis. These pilot studies demonstrate the potential of the SELDI platform for reproducible and consistent analysis of serum/plasma across multiple sites and also for targeted biomarker discovery and protein identification. This approach could be exploited for population-based studies in all phases of the HUPO PPP.

Biomarkers↗

PubMed2006

[Identification of biomarkers and therapeutic targets for renal cell cancer using ProteinChip technology].

In order to understand tumour biology in its complexity, it is necessary to investigate the proteomics in addition to the DNA and RNA level. SELDI-TOF-MS represents a new technology allowing a highly sensitive high-throughput analysis to detect specific protein profiles. In renal cancer, it was possible to define specific protein patterns in serum. Several proteins have been identified, i.e. serum amyloid alpha (SAA). Analysis of tumour tissues leads to a better understanding of tumour biology and provides the basis for differential classification and evaluation of prognosis. Investigation of the proteome concerning therapy results opens up the possibility of assessing downstream effects on the one hand and identifying biomarkers for selection of patients and therapy monitoring on the other hand. This review presents the first results for renal cancer.

Carcinoma, Renal Cell↗

PubMed2004

Microarray profiling of antiviral antibodies for the development of diagnostics, vaccines, and therapeutics.

Multiplex analysis of antiviral antibody (Ab) responses provides a potentially powerful strategy for viral diagnosis, prognostication, and development of vaccines and prophylactic Abs. In the coming years, advancements in proteomic technologies will provide even more robust methods to characterize antiviral Ab responses. Biomedical researchers will be faced with the exciting challenge of identifying antiviral Ab specificities that correlate with improved outcomes and efficacious interventions, and translating the findings into more effective diagnostics, prophylactics, and therapeutics.

Animals↗

PubMed2005

Serum protein fingerprinting coupled with artificial neural network distinguishes glioma from healthy population or brain benign tumor.

To screen and evaluate protein biomarkers for the detection of gliomas (Astrocytoma grade I-IV) from healthy individuals and gliomas from brain benign tumors by using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) coupled with an artificial neural network (ANN) algorithm. SELDI-TOF-MS protein fingerprinting of serum from 105 brain tumor patients and healthy individuals, included 28 patients with glioma (Astrocytoma I-IV), 37 patients with brain benign tumor, and 40 age-matched healthy individuals. Two thirds of the total samples of every compared pair as training set were used to set up discriminating patterns, and one third of total samples of every compared pair as test set were used to cross-validate; simultaneously, discriminate-cluster analysis derived SPSS 10.0 software was used to compare Astrocytoma grade I-II with grade III-IV ones. An accuracy of 95.7%, sensitivity of 88.9%, specificity of 100%, positive predictive value of 90% and negative predictive value of 100% were obtained in a blinded test set comparing gliomas patients with healthy individuals; an accuracy of 86.4%, sensitivity of 88.9%, specificity of 84.6%, positive predictive value of 90% and negative predictive value of 85.7% were obtained when patient's gliomas was compared with benign brain tumor. Total accuracy of 85.7%, accuracy of grade I-II Astrocytoma was 86.7%, accuracy of III-IV Astrocytoma was 84.6% were obtained when grade I-II Astrocytoma was compared with grade III-IV ones (discriminant analysis). SELDI-TOF-MS combined with bioinformatics tools, could greatly facilitate the discovery of better biomarkers. The high sensitivity and specificity achieved by the use of selected biomarkers showed great potential application for the discrimination of gliomas patients from healthy individuals and gliomas from brain benign tumors.

Adult↗

PubMed2006

Translating microarray data for diagnostic testing in childhood leukaemia.

BACKGROUND: Recent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF). METHODS: We examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort. RESULTS: We achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups. CONCLUSION: Our finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort and with microarray experiments being performed by a different research team.

Cell Line, Tumor↗

PubMed2006

High frequency of vancomycin-resistant Enterococcus faecium isolates with VanB phenotype and vanA genotype in Korean hospitals.

A total of 59 vancomycin-resistant Enterococcus faecium (VREF) clinical isolates were collected from 8 Korean hospitals for 2 months in 2004. They were investigated by genotyping for glycopeptide resistance, multilocus sequence typing (MLST), esp repeat profiling, and structural analysis of Tn1546-like element. Nine of 59 VREF isolates (15.3%) from 5 hospitals in Korea showed VanB phenotype, but they contained vanA gene. MLST and esp repeat profiling indicated that E. faecium isolates with VanB phenotype and vanA genotype occurred from independent genetic background except 3 isolates from 1 hospital. Structural analysis of Tn1546 also showed that these isolates were not clonally related. Data showed a relatively high frequency of VREF isolates with incongruence between phenotype and genotype for glycopeptide resistance in Korean hospitals.

Bacterial Proteins↗

PubMedDate not supplied

ProteinChip technology: a new and facile method for the identification and measurement of high-density lipoproteins apoA-I and apoA-II and their glycosylated products in patients with diabetes and cardiovascular disease.

This paper describes a ProteinChip technology for the identification and quantification of apolipoprotein profiles in crude biological samples. Expression levels of apoA-I and apoA-II and their glycosylated products were accomplished using single 1 microL plasma samples. In the present studies, strong anionic and weak cationic exchanger ProteinChips (SAX2 and WCX2 chip surfaces) were tested, and the WCX2 chip was found to be selective for specific apolipoproteins. Using the WCX2 chip and analysis via surface-enhanced laser desorption ionization mass spectrometry (SELDI-MS), apoA-I and apoA-II were separated as sharp peaks at 28 and 17 kD and did not overlap with other serum protein peaks. Since these assays can be completed on a large number of clinical samples in approximately 1 h, further development of this technique will facilitate both epidemiological studies and therapeutic trials in assessing the role of the apolipoproteins and their glycosylated products in atherosclerosis.

Apolipoprotein A-I↗

PubMed2005

[Genetic analysis of hematopoietic neoplasms].

Now dozens of genetic abnormalities have been identified in leukemias and lymphomas mainly through breakpoint analyses of the chromosome translocations recurrently observed in these tumors. After analyses on most of the major chromosome translocations have been completed, the current interests of genetic researches on hematopoietic tumors are unbalanced chromosome abnormalities that accompany gene deletions and amplifications among a variety of genetic mutations. In this regard, array based comparative genomic hybridization (CGH) and related techniques provide robust measures that enable high throughput genome-wide estimations of copy number changes for a large number of tumor samples. With these and other innovative techniques, identification of relevant genes for leukemogenesis and lymphomagenesis is being accelerated to provide more comprehensive understandings on development of these hematopoietic neoplasms.

Humans↗

PubMed2006

Proteomic analysis in human breast cancer: identification of a characteristic protein expression profile of malignant breast epithelium.

Gene expression analysis has become a promising tool in predicting the clinical course of malignant disease and the response to antineoplastic therapy. Surprisingly, only little is known about the protein expression pattern of human tumors. Recent advances in proteomic analysis allow proteins of interest to be identified by their expression and/or modification pattern in 2-DE rather than using the traditional approach of translating gene expression data. To identify a proteomic pattern that is characteristic for malignant breast epithelium, we performed differential 2-DE analysis in sets of microdissected malignant breast epithelia and corresponding adjacent normal breast epithelia from five patients with invasive breast carcinoma. Thirty-two protein spots were found to be selectively regulated in malignant epithelium, and were subjected to MALDI-TOF and/or immunoblotting for protein identification. Thirteen of the identified proteins had previously not been associated with breast cancer. The validity of these findings was confirmed by literature review and immunohistochemistry for identified proteins in an independent cohort of 50 breast cancer specimens. We here describe, for the first time, a proteomic analysis of matched normal and malignant epithelia from invasive breast carcinomas. This strategy leads to a better understanding of oncogenesis at an operational level and helps to characterize the malignant phenotype of individual tumors, and thereby to identify novel targets for antineoplastic therapy.

Adult↗