Validation of SELDI-TOF MS serum protein profiles for renal cell carcinoma in new populations

Toward improvement of screening through mass spectrometry-based proteomics: ovarian cancer as a case study

Ovarian cancer is one of the leading causes of cancer related deaths affecting United States women. Early-stage detection of ovarian cancer has been linked to increased survival, however, current screening methods, such as biomarker testing, have proven to be ineffective in doing so. Therefore, further developments are necessary to be able to achieve positive patient prognosis. Ongoing efforts are being made in biomarker discovery towards clinical applications in screening for early-stage ovarian cancer. In this perspective, we discuss and provide examples for several workflows employing mass spectrometry-based proteomics towards protein biomarker discovery and characterization in the context of ovarian cancer; workflows include protein identification and characterization as well as intact protein profiling. We also discuss the opportunities to merge these workflows for a multiplexed approach for biomarkers. Lastly, we provide our insight as to future developments that may serve to enhance biomarker discovery workflows while also considering translational potential.

Exploring the expression bar code of SAA variants for gastric cancer detection

We reported an integrated platform to explore serum protein variant pattern in cancer and its utility as a new class of biomarker panel for diagnosis. On the model study of serum amyloid A (SAA), we employed nanoprobe-based affinity mass spectrometry for enrichment, identification and quantitation of SAA variants from serum of 105 gastric cancer patients in comparison with 54 gastritis patients, 54 controls, and 120 patients from other cancer. The result revealed surprisingly heterogeneous and most comprehensive SAA bar code to date, which comprises 24 SAA variants including SAA1- and SAA2-encoded products, polymorphic isoforms, N-terminal-truncated forms, and three novel SAA oxidized isotypes, in which the variant-specific peptide sequence were also confirmed by LC-MS/MS. A diagnostic model was developed for dimension reduction and computational classification of the 24 SAA-variant bar code, providing good discrimination (AUC = 0.85 ± 3.2E-3) for differentiating gastric cancer group from gastritis and normal groups (sensitivity, 0.76; specificity, 0.81) and was validated with external validation cohort (sensitivity, 0.71; specificity, 0.74). Our platform not only shed light on the occurrence and modification extent of under-represented serum protein variants in cancer, but also suggested a new concept of diagnostic platform by serum protein variant profile.

Detection of Breast Cancer by Surface-enhanced Laser Desorption/Ionization Time-of-flight Mass Spectrometry Tissue and Serum Protein Profiling

Aim

Novel diagnostic breast cancer markers have been extensively searched for in the proteome, using, among others, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Thus far, the majority of SELDI-TOF MS studies have investigated samples originating from biorepositories, which hampers biomarker discovery as they likely suffer from variable adherence to collection protocols.

Material and methods

We investigated breast cancer (n=75) and control (n=26) serum and tissue samples, collected prospectively by rigorous adherence to a strictly defined protocol. Sera were collected preoperatively and postoperatively, and serum and tissue samples were analyzed by SELDI-TOF MS using the IMAC30 Ni and Q10 pH 8 array.

Results

Three serum peaks were significantly associated with breast cancer, while in tissue, 27 discriminative peaks were detected. Several peak clusters gradually increased or decreased in intensity from healthy to benign to cancer, or with increasing cancer stage. The constructed classification trees had a tenfold cross-validated performance of 67% to 87%. Two tissue peaks were identified as N-terminal albumin fragments. These are likely to have been generated by (breast) cancer-specific proteolytic activity in the tumor microenvironment.

Conclusions

These albumin fragments can potentially provide insights into the pathophysiological mechanisms associated with, or underlying, breast cancer, and aid in improving breast cancer diagnosis.

Identification of αB-Crystallin, a Biomarker of Renal Cell Carcinoma by SELDI-TOF MS

Spectrometric-based surface-enhanced laser desorption/ionization ProteinChip (SELDI-TOF) facilitates rapid and easy analysis of protein mixtures and is often exploited to define potential diagnostic markers from sera. However, SELDI-TOF is a relatively insensitive technique and unable to detect circulating proteins at low levels even if they are differentially expressed in cancer patients. Therefore, we applied this technology to study tissues from renal cell carcinomas (RCC) in comparison to healthy controls. We found that different biomarkers are identified from tissues than those previously identified in serum, and that serum markers are often not produced by the tumors themselves at detectable levels, reflecting the nonspecific nature of many circulating biomarkers. We detected and characterized αB-crystallin as an overexpressed protein in RCC tissues and showed differential expression by immunohistochemistry. We conclude that SELDI-TOF is more useful for the identification of biomarkers that are synthesized by diseased tissues than for the identification of serum biomarkers and identifies a separate set of markers. We suggest that SELDI-TOF should be used to screen human cancer tissues to identify potential tissue-specific proteins and simpler and more sensitive techniques can then be applied to determine their validity as biomarkers in biological fluids.

Expression of inflammatory lipopolysaccharide binding protein (LBP) predicts the progression of conventional renal cell carcinoma - a short report

BACKGROUND

The mortality of conventional renal cell carcinoma (RCC) correlates directly with the presence or postoperative development of metastases. The aim of this study was to identify new markers associated with the postoperative progression of conventional RCC.

METHODS

Tissue microarrays (TMA) of conventional RCC from a cohort of 414 patients were analysed by immunohistochemistry for expression of the lipopolysaccharide binding protein (LBP), which was identified as a candidate biomarker through Affymetrix U133 Plus 2.0 array analysis. Univariate and multivariate Cox regression models were addressed to cancer-specific survival in association with age, sex, clinicopathological parameters and LBP expression. The survival time of the patients was estimated by Kaplan-Meier analyses, and comparisons of survival curves were made using the Log rank test.

RESULTS

Univariate analysis revealed an association of patient survival with all clinicopathological parameters tested and LBP expression. In multivariate analysis only T classification, grade and LBP staining showed a significant association with postoperative cancer-specific survival (p < 0.001). LBP expression was found to be associated with a poor patient survival in Kaplan-Meier analyses. The estimated median survival time for patients with tumours showing LBP expression was 74 months, whereas the overall survival time was 142 months.

CONCLUSION

LBP expression in conventional RCC defines a group of patients at a high risk of postoperative progression and may help to direct optimized active surveillance and timely adjuvant therapy.

Differences between chronic lymphocytic leukaemia and small lymphocytic lymphoma cells by proteomic profiling and SNP microarray analysis

The majority of malignant cells in chronic lymphocytic leukaemia (CLL) circulate in the peripheral blood whereas small lymphocytic lymphoma (SLL) cells reside in tissues. The aim of this study was to detect differences in chemokine receptor expression, DNA single nucleotide polymorphism (SNP) microarray analysis and proteomic profiling to help elucidate why the cells remain in their respective environments. We identified by flow cytometric studies of chemokine receptors and DNA SNP microarray analysis significant differences between cells from CLL and SLL patients. Proteomic analysis revealed two potential markers (m/z 3091 and 8707) to distinguish the two disorders. There was a significantly greater expression of leucocyte trafficking receptor CXCR3 (CD183) and migration and homing receptor CXCR4 (CD184), and significantly lower expression of cell adhesion molecule integrin α₄ chain (CD49d), on CLL cells, compared with SLL cells. Conversely, SNP microarrays revealed greater numbers of copy-neutral loss of heterozygosity chromosomal aberrations, as well as gross chromosomal aberrations, in the SLL group, compared with the CLL group. These findings revealed that there was a significantly greater expression of trafficking, migration and homing receptors and significantly lower expression of adhesion molecules on CLL cells than on SLL cells, and that SLL may be a more progressive disease than CLL, with a more complex genotype.

PGRMC1 Is a Novel Potential Tumor Biomarker of Human Renal Cell Carcinoma Based on Quantitative Proteomic and Integrative Biological Assessments

Progesterone receptor membrane component 1 (PGRMC1) is widely observed with an elevated level in multiple human cancers. However, the roles of PGRMC1 in renal cancer are not clear and merit further study. In this report, we made a systematic, integrative biological assessment for PGRMC1 in renal cell carcinoma (RCC) by a quantitative proteomic identification, immunohistochemical detection, and its clinic pathologic significance analysis. We found that PGRMC1 abundance is increased by 3.91-fold in RCC tissues compared with its autologous para-cancerous tissues by a quantitative proteome identification. To validate the proteomic result with more confidence, 135 clinic RCC tissues were recruited to measure PGRMC1 abundance by immunohistochemical staining, and 63.7% RCC samples (n = 86) showed a higher abundance of PGRMC1 than the noncancerous counterparts. And the elevated PGRMC1 level was related to the tumor malignancy degree and overall survival of RCC patients. Meanwhile the average serum PGRMC1 concentration for RCC patients (n = 18) was significantly increased by 1.67 fold compared with healthy persons. Moreover an exogenous elevated abundance of PGRMC1 by plasmid transfections significantly enhanced cell proliferation of renal cancer cells in vitro. Our findings demonstrate PGRMC1, which promotes RCC progression phenotypes in vitro and in vivo, is a novel potential biomarker and therapeutic target for RCC.

Improving peptide relative quantification in MALDI-TOF MS for biomarker assessment

Proteomic profiling by MALDI-TOF MS presents various advantages (speed of analysis, ease of use, relatively low cost, sensitivity, tolerance against detergents and contaminants, and possibility of automation) and is being currently used in many applications (e.g. peptide/protein identification and quantification, biomarker discovery, and imaging MS). Earlier studies by many groups indicated that moderate reproducibility in relative peptide quantification is a major limitation of MALDI-TOF MS. In the present work, we examined and demonstrate a clear effect, in cases apparently random, of sample dilution in complex samples (urine) on the relative quantification of peptides by MALDI-TOF MS. Results indicate that in urine relative abundance of peptides cannot be assessed with confidence based on a single MALDI-TOF MS spectrum. To account for this issue, we developed and propose a novel method of determining the relative abundance of peptides, taking into account that peptides have individual linear quantification ranges in relation to sample dilution. We developed an algorithm that calculates the range of dilutions at which each peptide responds in a linear manner and normalizes the received peptide intensity values accordingly. This concept was successfully applied to a set of urine samples from patients diagnosed with diabetes presenting normoalbuminuria (controls) and macroalbuminuria (cases).

MALDI-MS-Based Profiling of Serum Proteome: Detection of Changes Related to Progression of Cancer and Response to Anticancer Treatment

Mass spectrometry-based analyses of the low-molecular-weight fraction of serum proteome allow identifying proteome profiles (signatures) that are potentially useful in detection and classification of cancer. Several published studies have shown that multipeptide signatures selected in numerical tests have potential values for diagnostics of different types of cancer. However due to apparent problems with standardization of methodological details, both experimental and computational, none of the proposed peptide signatures analyzed directly by MALDI/SELDI-ToF spectrometry has been approved for routine diagnostics. Noteworthy, several components of proposed cancer signatures, especially those characteristic for advanced cancer, were identified as fragments of blood proteins involved in the acute phase and inflammatory response. This indicated that among cancer biomarker candidates to be possibly identified by serum proteome profiling were rather those reflecting overall influence of a disease (and the therapy) upon the human organism, than products of cancer-specific genes. Current paper focuses on changes in serum proteome that are related to response of patient's organism to progressing malignancy and toxicity of anticancer treatment. In addition, several methodological issues that affect robustness and interlaboratory reproducibility of MS-based serum proteome profiling are discussed.

Application of SELDI-TOF-MS and LCM to screen protein markers for early diagnosis of liver metastasis of colorectal carcinoma

AIM: To screen protein markers for liver metastases of colorectal cancer using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein chip (SELDI-TOF-MS) in combination with laser capture microdissection (LCM) technology.

METHODS: Normal colorectal cells, primary tumor cells and liver metastatic cells were obtained from 24 colorectal cancer patients with liver metastases using the LCM technology. Protein profiling was performed using SELDI-TOF-MS technology. Differentially expressed proteins were analyzed using Biomarker Wizard software and identified by querying the database.

RESULTS: Fifteen differentially expressed proteins were found between primary tumor cells and normal colorectal cells, of which 12 were up-regulated and 3 down-regulated. Nine differentially expressed proteins were found between liver metastatic cells and primary tumor cells, of which 5 were up-regulated and 4 down-regulated. Twenty differentially expressed proteins were identified by querying ExPasy protein database, including integral membrane protein 2C, DNA repair protein RAD51 homolog 4, cell cycle checkpoint protein RAD1, human epididymis protein 4, centromere protein R, and pleckstrin homology domain family member 3. Apoptosis regulator Bax-γ, S100A11, Raf kinase inhibitor protein (RKIP) and heat shock protein 27 (HSP-27) displayed most obvious differential expression among normal colorectal cells, primary tumor cells and liver metastatic cells (all P < 0. 01).

CONCLUSION: SELDI-TOF-MS technology combined with LCM may allow to screen highly sensitive and specific protein markers for colorectal cancer and liver metastases of colorectal cancer.

Early diagnostic protein biomarkers for breast cancer: how far have we come?

Many studies have used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to search for blood-based proteins that are related to the presence of breast cancer. We review the biomarkers discovered or targeted measured by these methods and discuss the strengths and weaknesses of these studies. We highlight two proteins that were most often related to breast cancer: C3a des-arginine anaphylatoxin (C3adesArg) (molecular weight: 8,938 Da) and fragments of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4). In addition, we elaborate on three important methodological aspects related to these studies: protein identification, specificity of the markers, and disease heterogeneity. Finally, we propose some points to be addressed in future studies. These include the use of other analytical measurement techniques, need of protein identification, the importance of identical sample handling protocols for cases and controls, and the stratification of the results according to molecular subtypes and stages of breast cancer. Ultimately this may lead to the discovery of new and valid breast cancer specific biomarkers.

Dietary whey hydrolysate with exercise alters the plasma protein profile: a comprehensive protein analysis

OBJECTIVE

It has been shown that dietary whey protein accelerates glucose uptake by altering glycoregulatory enzyme activity in skeletal muscle. In the present study, we investigated the effect of dietary whey protein on endurance and glycogen resynthesis and attempted to identify plasma proteins that reflected the physical condition by a comprehensive proteomics approach.

METHODS

Male c57BL/6 mice were divided into four groups: sedentary, sedentary with whey protein hydrolysate, exercise, and exercise with whey protein hydrolysate. The mice in the exercise groups performed treadmill running exercise five times per week for 4 wk. Protein profiling of plasma sample obtained from individuals was performed, as were measurements of endurance performance and the glycogen content of gastrocnemius muscle.

RESULTS

After the training period, the endurance of mice fed the whey diet was improved compared with that of mice fed the control diet. Muscle glycogen content was significantly increased after 4 wk of exercise, and intake of whey protein led to a further increase in glycogen. Apolipoproteins A-II and C-I and β(2)-glycoprotein-1 were found to be altered by training combined with the intake of whey protein, without significant changes induced by exercise or whey protein alone.

CONCLUSION

Results of the present study suggest that these three proteins may be potential biomarkers of improved endurance and glycogen resynthesis and part of the mechanism that mediates the benefits of whey protein.

ProteoMiner™ and SELDI-TOF-MS: a robust and highly reproducible combination for biomarker discovery from whole blood serum

Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) has been recognized as an appropriate technology for biomarker discovery. Nevertheless, whenever human blood serum is studied, its sensitivity is restricted due to the wide dynamic range of serum protein concentrations. In this context, sample pre-fractionation targeting the low abundant proteins may help to overcome these limitations. Here, we evaluate the combination of ProteoMiner™ pre-fractionation and SELDI based protein profiling. We introduce a simplified workflow and demonstrate the high sensitivity and reproducibility of this combined profiling approach. Our analyses show that this combination is suitable for large-scale serum proteome profiling studies yielding reliable and reproducible results.

Effects of post-mortem intervals on regional brain protein profiles in rats using SELDI-TOF-MS analysis

Identification of disease-associated proteins is critical for elucidating CNS disease mechanisms and elaborating novel treatment strategies. It requires post-mortem tissue analysis which can be significantly affected by the collection process, post-mortem intervals (PMIs), and storage conditions. To assess the effect of time and storage conditions on brain protein stability, SELDI-TOF-MS protein profiles were assessed in rat frontal cortex, caudate-putamen, hippocampus and medulla samples collected after various PMIs (0, 6, 12, 24, 48, and 72 h) at 4 °C or at room temperature (RT) storage. Regions of interest were isolated from cryosections (tissue apposition, TA), or micropunched from cryosections apposed on filter paper (paper apposition, PA), and applied onto an NP20 ProteinChip array. Protein alterations, while greater at RT than at 4 °C, were detected at 6h then differentially evolved in the various brain regions, with greater alterations in the caudate-putamen (60%) and the cortex (48%). Overall, our sensitive analytical method allowed unveiling of different patterns of protein susceptibility to PMI and to storage temperature in the various brain regions. Some protein peaks were altered in all brain regions and may potentially serve as markers of the PMI status of the brain, or for reference values when studying new proteins. Changes in disease-related proteins within post-mortem samples can be greatly affected by PMI and storage conditions, particularly when studying fragile and/or low abundant protein/peptides in tissues sampled from the caudate-putamen and neocortex.

Association of serum amyloid A protein and peptide fragments with prognosis in renal cancer

BACKGROUND

In renal cell carcinoma (RCC), the discovery of biomarkers for clinical use is a priority. This study aimed to identify and validate diagnostic and prognostic serum markers using proteomic profiling.

METHODS

Pre-operative sera from 119 patients with clear cell RCC and 69 healthy controls was analysed by surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry with stringent in-house quality control and analysis routines. Following identification of one prognostic peak as a fragment of serum amyloid A (SAA), total serum SAA and CRP were also determined by immunoassay for further validation.

RESULTS

Several peptides were identified as having independent prognostic but not diagnostic significance on multivariable analysis. One was subsequently identified as a 1525 Da fragment of SAA (hazard ratio (HR)=0.26, 95% CI 0.08-0.85, P=0.026). This was weakly negatively correlated with total SAA, which was also of independent prognostic significance (HR=2.46, 95% CI 1.17-5.15, P=0.017). Both potentially strengthened prognostic models based solely on pre-operative variables.

CONCLUSIONS

This is the first description of the prognostic value of this peptide in RCC and demonstrates proof of principle of the approach. The subsequent examination of SAA protein considerably extends previous studies, being the first study to focus solely on pre-operative samples and describing potential clinical utility in pre-operative prognostic models.

Serum proteomics and disease-specific biomarkers of patients with advanced gastric cancer

Gastric cancer is a commonly diagnosed solid tumor which is associated with a dismal prognosis making early diagnosis essential. Thus, this study aimed to identify novel biomarkers in gastric cancer. Serum of patients with advanced gastric cancer was collected according to a predefined schedule: prior to first-line chemotherapy with epirubicin (50 mg/m(2), day 1), cisplatin (60 mg/m(2), day 1) and capecitabine (1,000 mg/m(2), twice daily on days 1-14). The serum was collected serially before the treatment cycles and then analyzed by SELDI-TOF MS. Normal control subjects were matched according to age, gender and serum collection. Serum proteomic mass spectrometry data of all subjects were processed using the tbimass R-package and compared. We analyzed i) whether proteomic profile changes were associated with a response to chemotherapy and survival, and ii) whether changes in proteomic profiles occurring during the time period of chemotherapy were associated with tumor response. In total, 82 patients with adenocarcinoma of the stomach (mean age 57 years, males 69.5%) were treated with a mean number of five chemotherapy cycles. The overall tumor response rate, complete and partial remission combined, was 37%, median time to progression was 7 months (95% CI, 6-8) and median overall survival 11 months (95% CI, 9.5-12). By comparing 77 serum samples of patients with normal matched controls, we identified 32 proteins which discriminated the two groups. By selecting the most differentiating proteins, we built a classification model that correctly categorized 81% of the gastric cancer patients and 90% of the normal controls. Furthermore, we found a statistically significant correlation between the pre-treatment intensity of serum amyloid-α (SAA) and overall survival in gastric cancer patients, whereby a low intensity of SAA predicted a longer patient survival. A classification model, based on the 32 most discriminating proteins differentiating gastric cancer from normal controls, correctly classified subjects with relatively high sensitivity and specificity.

Challenges for biomarker discovery in body fluids using SELDI-TOF-MS

Protein profiling using SELDI-TOF-MS has gained over the past few years an increasing interest in the field of biomarker discovery. The technology presents great potential if some parameters, such as sample handling, SELDI settings, and data analysis, are strictly controlled. Practical considerations to set up a robust and sensitive strategy for biomarker discovery are presented. This paper also reviews biological fluids generally available including a description of their peculiar properties and the preanalytical challenges inherent to sample collection and storage. Finally, some new insights for biomarker identification and validation challenges are provided.

SELDI-TOF biomarker signatures for cystic fibrosis, asthma and chronic obstructive pulmonary disease

OBJECTIVES

The aim of this work was to establish protein profiles in serum and nasal epithelial cells of cystic fibrosis individuals in comparison with controls, asthma and chronic obstructive pulmonary disease patients for specific biomarker signatures identification.

DESIGN AND METHODS

Protein extracts were analyzed by Surface Enhanced Laser Desorption/Ionization Time-Of-Flight Mass-Spectrometry (SELDI-TOF-MS).

RESULTS

The mass spectra revealed a set of peaks with differential expression in serum and nasal cells among the different groups studied, resulting into peak signatures representative/specific of each pathology. Logistic regressions were applied to those peaks; sensitivity, specificity, Youden's indexes and area under the curve (AUC) of the respective receiver operating characteristic (ROC) curves were compared.

DISCUSSION

Multivariate analysis demonstrated that combination of peaks has a better predictive value than the individual ones. These protein signatures may serve as diagnostic/prognostic markers for the studied diseases with common clinical features, or as follow-up assessment markers of therapeutic interventions.

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

When one chip is not enough: augmenting the validity of SELDI-TOF proteomic profiles of clinical specimens

To improve recovery, selectivity and reproducibility of SELDI-TOF analyses, we found it necessary to modify manufacturer's recommended protocols on sample and chip preparation. To yield reproducible denaturing conditions we verified concentrations of denaturing, reducing and lipid-solubilizing agents. We improved sorption of molecules of interest and reproducibility of analyses by introducing the preconditioning step and alkaline/acidic elutions for normal phase chips. The ratio that reproducibly decomposed the specimen was urea 9 mol l(-1) + DTT 10 mmol l(-1) + CHAPS 20 g l(-1). For sample denaturation, 100 microl of the fresh mixture was added to 100 microl of the specimen. Our modification of a chip processing increased recovery of the NP20 chip by up to 400% as assessed by total ion current. We obtained the range of mass accuracy of 0.02-0.04% and response precision between 30-40% of m/z+. We observed about 50% peak overlap. To obtain approximately 92% of possible peaks three chip selectivities, IMAC, H50 and normal phase with alkaline wash should be used. The selectivity of the SELDI chips is affected by unspecific interactions of a sample with a chip backbone. The system is compatible with matrix-based biological materials and does not suffer from urea interference and sensitivity to covalently bound alkaline ions. The technique is reasonably suitable for semiquantitative screening in the mammalian low-molecular weight cellular, tissue and plasma proteome.

From bench to bedside: current and future applications of molecular profiling in renal cell carcinoma

Among the adult population, renal cell carcinoma (RCC) constitutes the most prevalent form of kidney neoplasm. Unfortunately, RCC is relatively asymptomatic and there are no tumor markers available for diagnostic, prognostic or predictive purposes. Molecular profiling, the global analysis of gene and protein expression profiles, is an emerging promising tool for new biomarker identification in RCC. In this review, we summarize the existing knowledge on RCC regarding clinical presentation, treatment options, and tumor marker status. We present a general overview of the more commonly used approaches for molecular profiling at the genomic, transcriptomic and proteomic levels. We also highlight the emerging role of molecular profiling as not only revolutionizing the process of new tumor marker discovery, but also for providing a better understanding of the pathogenesis of RCC that will pave the way towards new targeted therapy discovery. Furthermore, we discuss the spectrum of clinical applications of molecular profiling in RCC in the current literature. Finally, we highlight some of the potential challenging that faces the era of molecular profiling and its transition into clinical practice, and provide an insight about the future perspectives of molecular profiling in RCC.

Serum amyloid A: an acute-phase protein involved in tumour pathogenesis

The synthesis of acute-phase protein serum amyloid A (SAA) is largely regulated by inflammation- associated cytokines and a high concentration of circulating SAA may represent an ideal marker for acute and chronic inflammatory diseases. However, SAA is also synthesized in extrahepatic tissues, e.g. human carcinoma metastases and cancer cell lines. An increasing body of in vitro data supports the concept of involvement of SAA in carcinogenesis and neoplastic diseases. Accumulating evidence suggests that SAA might be included in a group of biomarkers to detect a pattern of physiological events that reflect the growth of malignancy and host response. This review is meant to provide a broad overview of the many ways that SAA could contribute to tumour development, and accelerate tumour progression and metastasis, and to gain a better understanding of this acute-phase reactant as a possible link between chronic inflammation and neoplasia.

Serum amyloid A as indicator of distant metastases but not as early tumor marker in patients with renal cell carcinoma

The aim of the present study was to evaluate the clinical significance of the concentration of serum amyloid A (SAA) in patients with renal cell carcinoma (RCC). SAA protein was determined with enzyme-linked immunosorbent assay in serum samples of 55 healthy controls and 98 RCC patients subdivided into groups with localized tumor (N0M0, n=40), with lymph node metastases (N1M0, n=13), and distant metastases (M1, n=45). SAA concentrations in controls and N0M0 group of RCC were not different while SAA concentrations were significantly elevated in M1 patients compared to the N1M0 and N0M0 patients. In this respect, SAA provided an accurate detection of distant metastases with the area under the ROC curve of 0.86. SAA was identified as a significant independent factor of survival in RCC patients using the multivariate Cox proportional hazards regression model. SAA could be a useful analyte in predicting the survival outcome of RCC patients.

Gene network and canonical pathway analysis in prostate cancer: a microarray study

The molecular mechanism playing a role in the development of prostate cancer (PCA) is not well defined. We decided to determine the changes in gene expression in PCA tissues and to compare them to those in non-cancerous samples. Prostate tissue samples were collected by needle biopsy from 21 PCA and 10 benign prostate hyperplasic (BPH) patients. Total RNA was isolated, cDNA was synthesized, and gene expression levels were determined by microarray method. In the progression to PCA, 738 up-regulated and 515 down-regulated genes were detected in samples. Analysis using Ingenuity Pathway Analysis (IPA) software revealed that 466 network and 423 functions-pathways eligible genes were up-regulated, and 363 network and 342 functions-pathways eligible genes were down-regulated. Up-regulated networks were identified around IL-1beta and insulin-like growth factor-1 (IGF-1) genes. The NFKB gene was centered around two up- and down-regulated networks. Up-regulated canonical pathways were assigned and four of them were evaluated in detail: acute phase response, hepatic fibrosis, actin cytoskeleton, and coagulation pathways. Axonal guidance signaling was the most significant down-regulated canonical pathway. Our data provide not only networks between the genes for understanding the biologic properties of PCA but also useful pathway maps for future understanding of disease and the construction of new therapeutic targets.

Population proteomics: investigation of protein diversity in human populations

Outlined in this review is the concept of population proteomics, its aspects, enabling approaches, and significance in understanding proteins' roles in physiological processes and diseases. Population proteomics addresses the need for individual assessment of proteins across large populations to delineate the existence of structural variations, determine their frequency, and explore the association of the modifications with specific diseases. Besides the basic concepts and underlying reasons for such protein diversity studies, also reviewed here are the results of two fundamental studies that investigated human plasma protein diversity across the healthy population in the United States. Such studies of protein diversity are needed to map all the post-expression protein modifications and determine the wild-type protein profiles, similar to the human diversity studies at the genome level that have helped redefine the "normal" human genome.