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PubMed2005

Proteomics as a tool for clinically relevant biomarker discovery and validation.

The excitement associated with clinical applications of proteomics was initially focused on its potential to serve as a vehicle for both biomarker discovery and drug discovery and routine clinical sample analysis. Some approaches were thought to be able to "identify" mass spectral characteristics that distinguished between control and disease samples, and thereafter it was believed that the same tool could be employed to screen samples in a high-throughput clinical setting. However, this has been difficult to achieve, and the early promise is yet to be fully realized. While we see an important place for mass spectrometry in drug and biomarker discovery, we believe that alternative strategies will prove more fruitful for routine analysis. Here we discuss the power and versatility of 2D gels and mass spectrometry in the discovery phase of biomarker work but argue that it is better to rely on immunochemical methods for high-throughput validation and routine assay applications.

Animals↗
PubMed2004

Circulating nucleic acids and proteomics of plasma/serum: clinical utility.

Circulating tumor-specific nucleic acids have been identified in plasma, serum, and other body fluids from cancer patients with tumors originating in almost any organ site. Polymerase chain reaction provides a highly sensitive and specific technique for the detection of these genetic changes in a limited amount of tissue/fluid. The presence of elevated levels of free DNA/RNA in many medical conditions, malignancy, and infectious processes is being investigated for screening, diagnosis, prognosis, surveillance for occult disease progression, identifying potential therapeutic targets, and monitoring treatment response. Additionally, elevated fetal DNA/RNA in maternal blood is being used to determine gender identity, assess chromosomal abnormalities, and monitor pregnancy-associated complications. Questions remain on the etiology, characteristics, stability, and potential pathologic consequences of cell-free DNA/RNA in the circulation. Nevertheless, nucleic acid-based assays that monitor plasma, serum, and body fluids provide a noninvasive, facile, and practical method for assessing patients. Proteomic profiling may prove complementary to a total functionality approach in providing a comprehensive evaluation of the patient's disease.

Biomarkers, Tumor↗
PubMed2005

Online coupling of capillary electrophoresis with mass spectrometry for the identification of biomarkers for clinical diagnosis.

Proteomic screening of complex biologic samples is of increasing importance in clinical research and diagnosis. In the postgenomic area it is evident that changes of the composition of body fluids, as well as post-translational modifications of proteins and peptides, provide more information than genetic typing. The study of these changes allows the state of health or disease of particular organs, and consequently, the whole organism, to be described. This review describes the application of capillary electrophoresis coupled online to an electrospray ionization time-of-flight mass spectrometer to the analysis of body fluids obtained from patients for the identification of biomarkers for diagnostic purposes.

Biomarkers↗
PubMed2002

Targeting of tumor associated antigens in renal cell carcinoma using proteome-based analysis and their clinical significance.

The suitability of proteome-based strategies for the targeting of tumor-associated markers along with further analysis regarding their clinical significance were investigated in human renal cell carcinoma (RCC). The immunogenic protein expression profile of normal kidney and RCC cell lines was studied by proteome analysis combined with immunoblotting using sera from healthy donors and RCC patients, also termed PROTEOMEX. Employing this approach, a series of proteins reactive with either RCC patient sera and/or reactive with control sera were identified by microanalysis of tryptic peptides. Some of these candidate antigens represent members of the cytoskeletal family, such as cytokeratins, in particular cytokeratin 8, cytoskeletal tropomyosin, F-actin capping protein, gamma-actin, stathmin, tubulin-alpha, tubulin-beta and vimentin. The expression pattern and clinical significance of three of these antigens, namely cytokeratin 8, stathmin and vimentin, were further analyzed in a large series of surgically removed RCC lesions of distinct subtypes. A heterogeneous expression pattern of cytokeratin 8, stathmin and vimentin was demonstrated in the different RCC subtypes. All epithelial cells of the autologous normal kidney showed a strong cytokeratin 8 staining pattern, whereas they totally lack vimentin expression. Stathmin was expressed in 10% of tubule cells. In conclusion, PROTEOMEX could be employed for the identification of tumor-associated antigens of the cytoskeleton which are differentially expressed in RCC of distinct subtypes as well as in normal renal epithelium.

Antigens, Neoplasm↗
PubMed2003

Proteomic prediction of disease outcome in cancer : clinical framework and current status.

Better than gene sequencing or quantitative amplification, proteomics tools allow the study of tumor phenotype. Indeed, most current prognostic tests in cancer (carcinoembryonary antigen [CEA], prostate-specific antigen [PSA], CA 19-1, CA 125, alpha-fetoprotein [AFP], etc.) are based on the detection and quantification of single proteins in body fluids. However, a common characteristic of these tests is their relatively low predictive value, so that they are usually complemented with other procedures such as biopsy and/or endoscopy. Recently, improved analytical and bioinformatics tools have driven the attention on pattern recognition approaches rather then single-marker tests for prognostic forecasting. It is expected that predicting metastasization on the basis of tumoral protein patterns will soon be a reality. However, currently available technologies either limit the number of proteins that can be analyzed simultaneously or they are expensive, difficult, and time-consuming. Moreover, the tools adapted for expression proteomics might not be the same as those for prognostic studies that require investigation of protein function over time. We believe that clinical proteomics research designed within a precise clinical and pathology framework should be strongly supported, since many prognostic factors are determined not by the tumor itself, but by the patient, the treatment and the environment.

Animals↗
PubMed2005

Proteome analysis in the clinical chemistry laboratory: myth or reality?

BACKGROUND: We review here modern aspects of proteomic analysis, as displayed via orthogonal mass/charge analysis (isoelectric focusing in the first dimension, followed by sodium dodecyl sulphate electrophoresis in polyacrylamide gels, SDS-PAGE, at right angles, in the second dimension). METHODS: This technique is capable of displaying a few thousand polypeptide chains, characterized by a single pI and M(r) value as coordinates, and recognized via elution, digestion and mass spectrometry analysis. Although, up to the present, this technique has been used mostly for advanced research, with no immediate applications in the clinical chemistry laboratory, there are hints that such applications will soon become a reality. RESULTS AND CONCLUSIONS: In the field of cancer research, it is here shown that stathmin (Op18) becomes heavily phosphorylated in cancerous mantle cell lymphomas and that the progression of the disease can be followed by the progression of phosphorylation of Op18 and by the appearance of additional phosphorylated spots. Also chemoresistance of different tumors has been evaluated via 2D-PAGE through quantitative, differential proteomics: among up- and down-regulated proteins in a human cervix squamous cell carcinoma cell line (A431), rendered resistant to cisplatin, one particular protein was found to appear in large quantities by de novo synthesis: 14-3-3, a protein known to impart resistance to apoptosis to cells. In the field of brain disorders, we could set up an easy test for detecting pathological prions in sporadic Creutzfeldt-Jakob disease (sCJD), by simply searching for those pathological forms in the olfactory mucosa (up to this finding, diagnosis could only be confirmed post-mortem). We are currently working on a test for differentiating sCJD from all the other degenerative dementias. Upon 2D mapping of cerebrospinal fluid (CSF) and immunoblot analysis, we could identify a major spot (pI 4.8, M(r) 30 kDa) followed by some two-three minor spots (pIs 5.0-6.0, same M(r) value) of the same 14-3-3 anti-apoptotic protein involved in chemoresistance. By this test, sCJD could be differentiated from all the other degenerative dementias, which are 14-3-3 negative (in sCJD, the rapid and massive brain cell damage releases large quantities of 14-3-3 in the cerebrospinal fluid). Another protein that appears very promising as a marker for sCJD is cystatin C, that is strongly up-regulated in this pathology. Human sera should also be mined for discovery of many more markers for disease. Up to the present, no one could be found, but this was due to the presence of several major proteins, obscuring all rare ones. Via several immuno-subtraction steps, followed by ion exchange and size exclusion chromatography, one can now detect proteins and peptides present in sera at levels below 10 ng/mL, highlighting the road to discovery of novel markers of disease. Another technique that could revolutionize biomarker discovery in biological fluids consists in the use of combinatorial beads to reduce the dynamic range. They consist in a library of combinatorial ligands coupled to small beads. Such a library comprises hexameric ligands composed of amino acids, resulting in millions different structures. When these beads are impregnated with complex proteomes (e.g., human sera, CSF, urines) of widely differing protein compositions, they are able to significantly reduce the concentration differences, thus greatly enhancing the possibility of evidencing low-abundance species.

Animals↗
PubMed2003

Protein microarrays: molecular profiling technologies for clinical specimens.

Proteomics, the study of protein function within biologic systems, will further our understanding of cancer pathogenesis. Coupled with transcript profiling, proteomics can herald the advent of molecular therapy tailored to the individual patient's neoplasm. Protein microarrays, one emerging class of proteomic technologies, have broad applications for discovery and quantitative analysis. This technology is uniquely suited to gather information about the post-translational modifications of proteins reflecting the activity state of signal pathways and networks. Protein microarrays now make it feasible to conduct signal network profiling within cellular samples. Nevertheless, to be successful, design and use of protein microarrays must take into consideration enormous analytical challenges. A subclass of protein microarrays, Reverse Phase Arrays, created to meet these challenges, has been optimized for use with tissue specimens, and is now in use for the analysis of biopsy samples for clinical trial research.

Antibodies↗
PubMed2006

Genomics and proteomics: emerging technologies in clinical cancer research.

Fueled by the complete genomic data acquired from the human genome project and the desperate clinical need of comprehensive analytical tools to study a heterogeneous disease like cancer, genomic and proteomic technologies have evolved rapidly, accelerating the rate and number of discoveries in clinical cancer research. These discoveries include mechanistic understanding of cancer biology as well as the identification of biomarkers supporting early detection, molecular classification of tumors, molecular predictors of metastasis, treatment response, and prognosis. While the technical advances have been significant, clinical researchers and practicing physicians are now confronted with the challenges of understanding technically and statistically complex data sets, translating this complex information to fit clinical contexts and incorporating it into clinical studies. In this review, we will summarize the available technologies and associated bioinformatics, discuss studies that are clinically relevant, and discuss the limitations we are still facing. We will present a framework for future directions of these technologies and how we believe they should be applied in clinical studies.

Biomedical Research↗
PubMedDate not supplied

Mass spectrometry-based proteomics and analyses of serum: a primer for the clinical investigator.

The vocabulary of proteomics and the swiftly-developing, technological nature of the field constitute substantial barriers to clinical investigators. In recent years, mass spectrometry has emerged as the most promising technique in this field. The purpose of this review is to introduce the field of mass spectrometry-based proteomics to clinical investigators, to explain many of the relevant terms, to introduce the equipment employed in this field, and to outline approaches to asking clinical questions using a proteomic approach. Examples of clinical applications of proteomic techniques are provided from the fields of cancer and vasculitis research, with an emphasis on a pattern recognition approach.

Blood Proteins↗
PubMed2004

Clinical infrastructures to support proteomic studies of tissue and fluids in breast cancer.

The Danish Breast Cancer Cooperative Group (DBCG) was established in 1977 with the aim to ensure optimal breast cancer diagnostics and therapeutic modalities on a nationwide basis. DBCG was organized in such a way so it represents a broad interdisciplinary collaboration with established clinical databases and biobanks. This review summarizes the infrastructures, such as those of the DBCG, that are required to facilitate translational research studies aiming at further diagnostic and therapeutic improvements through interactions directed at prevention, early diagnosis, and treatment of primary breast cancer.

Body Fluids↗
PubMed2006

Protein and peptide arrays: recent trends and new directions.

Microarrays of proteins and peptides make it possible the screening of thousands of binding events in a parallel and high throughput fashion; therefore they are emerging as a powerful tool for proteomics and clinical assays. The complex nature of Proteome, the wide dynamic range of protein concentration in real samples and the critical role of immobilized protein orientation must be taken into account to maximize the utility of protein microarrays. Immobilization strategy and designing of an ideal local chemical environment on the solid surface are both essential for the success of a protein microarray experiment. This review article will focus on protein and peptide arrays highlighting their technical challenges and presenting new directions by means of a set of selected recent applications.

Combinatorial Chemistry Techniques↗
PubMed2006

[Detection and clinical significance of serum proteomic patterns of breast cancers by surface enhanced laser desorption/ionization time of flight mass spectrometry].

OBJECTIVE: To detect the serum proteomic patterns in breast cancer patients by surface enhanced laser desorption/ionization time of flight (SELDI-TOF-MS) protein chip array techniques, to screen biomarker candidates and build diagnostic models in order to evaluate their clinical significance. METHODS: SELDI-TOF-MS technique and weak cation exchanger (WCX2) protein chip were used to detect the serum proteomic patterns of 38 patients with breast cancer, 33 patients with benign breast diseases and 43 normal control subjects. Biomarker Wizard 3.01 and Biomarker Pattern Software 5.01 were used in combination to analyze the data and to develop diagnostic models. RESULTS: Four protein peaks pattern (M2077_07, M1827_38, M2650_51 and M2060_62 mass/charge ratio [m/z]) was observed in the model I, and it could be used to distinguish breast cancer from non cancerous diseases. Its sensitivity and specificity were 73.7% (28/38) and 73.7% (56/76), respectively. The model II was formed by 5 protein peaks (M2251_62, M3405_56, M3428_16, M4666_98, M16239_8 m/z). When it was used in differential diagnosis between stage I breast cancer and benign breast diseases, the sensitivity and specificity were 84.8% (28/33) and 55.6% (5/9), respectively. Another 5 peaks (M1701_48, M3116_17, M1676_88, M5890_33, M2921_02 m/z) could build the model III to distinguish stage I and stage II approximately IV breast cancers. Its sensitivity and specificity were 88.9% (8/9) and 86.2% (25/29), respectively. CONCLUSION: Our findings suggested that application of SELDI-TOF-MS can be of great potential for early breast cancer screening, diagnosis and preoperative staging, and deserves further studies.

Adult↗
PubMed2006

Proteomic-based prediction of clinical behavior in adult acute lymphoblastic leukemia.

BACKGROUND: Response in adult acute lymphoblastic leukemia (ALL) can be achieved in a majority of patients. However, unlike pediatric ALL, recurrence is common in adult ALL, and the ability to predict at an early stage which patients are most likely to experience recurrence may help in devising new therapeutic approaches to prevent recurrence. METHODS: Peripheral blood plasma from 57 patients with confirmed ALL was obtained before induction therapy for proteomic analysis. Follow-up continued for a median period of 71 weeks. For each plasma sample, 4 fractions eluted from a strong anion column were applied to 3 different ProteinChip array surfaces, and 12 surface-enhanced laser desorption/ionization (SELDI) spectra were generated. Peaks that correlated with recurrence were identified and decision trees were constructed and evaluated, using only 2 peaks per predictive tree. RESULTS: The best decision trees provided strong positive prediction of recurrence, with correct predictions 84% to 92% of the time, whereas negative prediction of patients who did not experience recurrence was less robust, with 62% to 74% accuracy. Prediction of recurrence was independent of cytogenetics, bone marrow blast count, lactate dehydrogenase, beta-2-microglobulin, or surface markers. Positive prediction of L3 morphological classification was achieved in 80% of test cases. CONCLUSIONS: Peripheral blood plasma is adequate to predict clinical behavior in ALL patients irrespective of the percentage of bone marrow blasts. Proteomic analysis of plasma offers a useful approach for profiling patients with ALL.

Adolescent↗
PubMed2025

Proteomic Analysis of 442 Clinical Plasma Samples From Individuals With Symptom Records Revealed Subtypes of Convalescent Patients Who Had COVID-19.

After the coronavirus disease 2019 (COVID-19) pandemic, the postacute effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have gradually attracted attention. To precisely evaluate the health status of convalescent patients with COVID-19, we analyzed symptom and proteome data of 442 plasma samples from healthy controls, hospitalized patients, and convalescent patients 6 or 12 months after SARS-CoV-2 infection. Symptoms analysis revealed distinct relationships in convalescent patients. Results of plasma protein expression levels showed that C1QA, C1QB, C2, CFH, CFHR1, and F10, which regulate the complement system and coagulation, remained highly expressed even at the 12-month follow-up compared with their levels in healthy individuals. By combining symptom and proteome data, 442 plasma samples were categorized into three subtypes: S1 (metabolism-healthy), S2 (COVID-19 retention), and S3 (long COVID). We speculated that convalescent patients reporting hair loss could have a better health status than those experiencing headaches and dyspnea. Compared to other convalescent patients, those reporting sleep disorders, appetite decrease, and muscle weakness may need more attention because they were classified into the S2 subtype, which had the most samples from hospitalized patients with COVID-19. Subtyping convalescent patients with COVID-19 may enable personalized treatments tailored to individual needs. This study provides valuable plasma proteomic datasets for further studies associated with long COVID.

Humans↗
PubMed2005

Serum proteomic fingerprinting discriminates between clinical stages and predicts disease progression in melanoma patients.

PURPOSE: Currently known serum biomarkers do not predict clinical outcome in melanoma. S100-beta is widely established as a reliable prognostic indicator in patients with advanced metastatic disease but is of limited predictive value in tumor-free patients. This study was aimed to determine whether molecular profiling of the serum proteome could discriminate between early- and late-stage melanoma and predict disease progression. PATIENTS AND METHODS: Two hundred five serum samples from 101 early-stage (American Joint Committee on Cancer [AJCC] stage I) and 104 advanced stage (AJCC stage IV) melanoma patients were analyzed by matrix-assisted laser desorption/ionisation (MALDI) time-of-flight (ToF; MALDI-ToF) mass spectrometry utilizing protein chip technology and artificial neural networks (ANN). Serum samples from 55 additional patients after complete dissection of regional lymph node metastases (AJCC stage III), with 28 of 55 patients relapsing within the first year of follow-up, were analyzed in an attempt to predict disease recurrence. Serum S100-beta was measured using a sandwich immunoluminometric assay. RESULTS: Analysis of 205 stage I/IV serum samples, utilizing a training set of 94 of 205 and a test set of 15 of 205 samples for 32 different ANN models, revealed correct stage assignment in 84 (88%) of 96 of a blind set of 96 of 205 serum samples. Forty-four (80%) of 55 stage III serum samples could be correctly assigned as progressors or nonprogressors using random sample cross-validation statistical methodologies. Twenty-three (82%) of 28 stage III progressors were correctly identified by MALDI-ToF combined with ANN, whereas only six (21%) of 28 could be detected by S100-beta. CONCLUSION: Validation of these findings may enable proteomic profiling to become a valuable tool for identifying high-risk melanoma patients eligible for adjuvant therapeutic interventions.

Disease Progression↗