Pattern analysis of serum proteome distinguishes renal cell carcinoma from other urologic diseases and healthy persons

Despite having a relatively low incidence, renal cell carcinoma (RCC) is one of the most lethal urologic cancers. For successful treatment including surgery, early detection is essential. Currently there is no screening method such as biomarker assays for early diagnosis of RCC. Surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF) is a recent technical advance that can be used to identify biomarkers for cancers. In this study, we investigated whether SELDI protein profiling and artificial intelligence analysis of serum could distinguish RCC from healthy persons and other urologic diseases (nonRCC). The SELDI-TOF data was acquired from a total of 36 serum samples with weak cation exchange-2 protein chip arrays and filtered using ProteinChip software. We used a decision tree algorithm c4.5 to classify the three groups of sera. Five proteins were identified with masses of 3900, 4107, 4153, 5352, and 5987 Da. These biomarkers can correctly separate RCC from healthy and nonRCC samples.     

Serum protein profiling to identify biomarkers for small renal cell carcinoma

Diagnostic biomarkers for early detection of renal cell carcinoma (RCC) are in great need. In the present study, we compared the serum protein profiles of patients with small RCC to those of healthy individuals to identify the differentially expressed proteins with potential to serve as biomarkers. Serum samples were collected from 10 patients with small RCC and 10 healthy individuals. The serum protein expression profiles were analyzed by two-dimensional (2-D) gel electrophoresis. Twenty-seven proteins with differences in expression levels between RCC patients and healthy volunteers were identified. Of these, 19 were expressed at different levels and eight were expressed in serum from the RCC group, but not from the control group. Six differentially expressed proteins identified by using mass spectrometry included coagulation factor XIII B, complement C3 and its precursor, misato homolog 1 (isoform CRA_b), hemopexin, and alpha-1-B-glycoprotein. Some of these serum proteins are known regulators of tumor progression in human malignancies. In conclusion, we successfully applied 2-D gel electrophoresis and identified six serum proteins differentially expressed between patients with small RCC and healthy volunteers. These proteins may provide novel biomarkers for early detection and diagnosis of human RCC.     

SELDI-TOF serum proteomics and breast cancer: which perspective?

Despite the efforts of recent years, clinicians still lack reliable biomarkers for diagnosis, prognosis and prediction of clinical outcomes in breast cancer patients. Owing to the large number of people potentially involved in the management of this clinical problem, the search for noninvasive and repeatable laboratory assays has been intensive. Recently, the proteomic profiling performed by SELDI-TOF mass spectrometry, has been proposed in order to identify new clusters of serum markers that could be potentially useful in breast cancer management. The purpose of this special report is to review the literature on SELDI-TOF technology applied on serum coming from healthy people and breast cancer patients, in order to verify the clinical applicability of such approach. We conclude that potential new biomarkers, first of all for early diagnosis of breast cancer, need to be validated in larger clinical series.     

Identification of serum proteomic biomarkers for early porcine reproductive and respiratory syndrome (PRRS) infection

ABSTRACT: BACKGROUND: Porcine reproductive and respiratory syndrome (PRRS) is one of the most significant swine diseases worldwide. Despite its relevance, serum biomarkers associated with early-onset viral infection, when clinical signs are not detectable and the disease is characterized by a weak anti-viral response and persistent infection, have not yet been identified. Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF MS) is a reproducible, accurate, and simple method for the identification of biomarker proteins related to disease in serum. This work describes the SELDI-TOF MS analyses of sera of 60 PRRSV-positive and 60 PRRSV-negative, as measured by PCR, asymptomatic Large White piglets at weaning. Sera with comparable and low content of hemoglobin (< 4.52 ug/mL) were fractionated in 6 different fractions by anion-exchange chromatography and protein profiles in the mass range 1-200 kDa were obtained with the CM10, IMAC30, and H50 surfaces. RESULTS: A total of 200 significant peaks (p < 0.05) were identified in the initial discovery phase of the study and 47 of them were confirmed in the validation phase. The majority of peaks (42) were up-regulated in PRRSV-positive piglets, while 5 were down-regulated. A panel of 14 discriminatory peaks identified in fraction 1 (pH=9), on the surface CM10, and acquired at low focus mass provided a serum protein profile diagnostic pattern that enabled to discriminate between PRRSV-positive and -negative piglets with a sensitivity and specificity of 77% and 73%, respectively. CONCLUSIONS: SELDI-TOF MS profiling of sera from PRRSV-positive and PRRSV-negative asymptomatic piglets provided a proteomic signature with large scale diagnostic potential for early identification of PRRSV infection in weaning piglets. Furthermore, SELDI-TOF protein markers represent a refined phenotype of PRRSV infection that might be useful for whole genome association studies.     

Evaluation of proteomics-identified CCL18 and CXCL1 as circulating tumor markers for differential diagnosis between ovarian carcinomas and benign pelvic masses

A lack of sensitive and specific tumor markers for early diagnosis and treatment is a major cause for the high mortality rate of ovarian cancer. The purpose of this study was to identify potential proteomics-based biomarkers useful for the differential diagnosis between ovarian cancer and benign pelvic masses. Serum samples from 41 patients with ovarian cancer, 32 patients with benign pelvic masses, and 41 healthy female blood donors were examined, and proteomic profiling of the samples was assessed by surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectroscopy (MS). A confirmatory study was also conducted with serum specimens from 58 patients with ovarian carcinoma, 37 patients with benign pelvic masses, and 48 healthy women. A classification tree was established using Biomarker Pattern Software. Six differentially expressed proteins (APP, CA 125, CCL18, CXCL1, IL-8, and ITIH4) were separated by high-performance liquid chromatography and identified by matrix-assisted laser desorption/ionization (MALDI)-MS/MS and database searches. Two of the proteins overexpressed in ovarian cancer patients, chemokine CC2 motif ligand 18 (CCL18) and chemokine CXC motif ligand 1 (CXCL1), were automatically selected in a multivariate predictive model. These two protein biomarkers were then validated and evaluated by enzyme-linked immunosorbent assay (ELISA) in 535 serum specimens (130 ovarian cancer, 64 benign ovarian masses, 36 lung cancer, 60 gastric cancer, 55 nasopharyngeal carcinoma, 48 hepatocellular carcinoma, and 142 healthy women). The combined use of CCL18 and CXCL1 as biomarkers for ovarian cancer had a sensitivity of 92% and a specificity of 97%. The multivariate ELISA analysis of the two putative markers in combination with CA 125 resulted in a sensitivity of 99% for healthy women and 94% for benign pelvic masses, and a specificity of 92% for both groups; these values were significantly higher than those obtained with CA 125 alone (p and lt;0.05). We conclude that serum CCL18 and CXCL1 are potentially useful as novel circulating tumor markers for the differential diagnosis between ovarian cancer and benign ovarian masses.     

The nucleotide-independent Fe(III)-binding site is located on beta subunit of the mitochondrial F(1)-ATPase

The need for methods to identify disease biomarkers is underscored by the survival-rate of patients diagnosed at early stages of cancer progression. Surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) is a novel approach to biomarker discovery that combines two powerful techniques: chromatography and mass spectrometry. One of the key features of SELDI-TOF MS is its ability to provide a rapid protein expression profile from a variety of biological and clinical samples. It has been used for biomarker identification as well as the study of protein-protein, and protein-DNA interaction. The versatility of SELDI-TOF MS has allowed its use in projects ranging from the identification of potential diagnostic markers for prostate, bladder, breast, and ovarian cancers and Alzheimer's disease, to the study of biomolecular interactions and the characterization of posttranslational modifications. In this minireview we discuss the application of SELDI-TOF MS to protein biomarker discovery and profiling.     

Protein signature of lung cancer tissues

Lung cancer remains the most common cause of cancer-related mortality. We applied a highly multiplexed proteomic technology (SOMAscan) to compare protein expression signatures of non small-cell lung cancer (NSCLC) tissues with healthy adjacent and distant tissues from surgical resections. In this first report of SOMAscan applied to tissues, we highlight 36 proteins that exhibit the largest expression differences between matched tumor and non-tumor tissues. The concentrations of twenty proteins increased and sixteen decreased in tumor tissue, thirteen of which are novel for NSCLC. NSCLC tissue biomarkers identified here overlap with a core set identified in a large serum-based NSCLC study with SOMAscan. We show that large-scale comparative analysis of protein expression can be used to develop novel histochemical probes. As expected, relative differences in protein expression are greater in tissues than in serum. The combined results from tissue and serum present the most extensive view to date of the complex changes in NSCLC protein expression and provide important implications for diagnosis and treatment.     

The ovarian cancer-derived secretory/releasing proteome: A repertoire of tumor markers

Ovarian cancer is the most lethal gynecological malignancy worldwide, and early detection of this disease using serum or plasma biomarkers may improve its clinical outcome. In the present study, a large scale protein database derived from ovarian cancer was created to enable tumor marker discovery. First, primary organ cultures were established with the tumor tissues and corresponding normal tissues obtained from six ovarian cancer patients, and the serum-free conditioned medium (CM) samples were collected for proteomic analysis. The total proteins from the CM sample were separated by SDS-PAGE, digested with trypsin and then analyzed by LC-MS/MS. Combining data from the tumor tissues and the normal tissues, 1129 proteins were identified in total, of which those categorized as "extracellular proteins" and "plasma membrane proteins" accounted for 21.4% and 16.9%, respectively. For validation, three secretory proteins (NID1, TIMP2, and VCAN) involved in "organ development"-associated subnetwork, showed significant differences between their levels in the circulating plasma samples from ovarian cancer patients and healthy women. In conclusion, this ovarian cancer-derived protein database provides a credible repertoire of potential biomarkers in blood for this malignant disease, and deserves mining further.     

Quantitative proteomic analysis by iTRAQ<Superscript>®</Superscript> for the identification of candidate biomarkers in ovarian cancer serum

Background

Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ^®.

Results

Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ^® to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified.

Conclusions

This study provides the first analysis of immunodepleted serum in combination with iTRAQ^® to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

     

Proteomic analysis in clear cell renal cell carcinoma: identification of differentially expressed protein by 2-D DIGE

Renal cell carcinoma (RCC), the most common neoplasm affecting the adult kidney, is characterised by heterogeneity of histological subtypes, drug resistance, and absence of molecular markers. Two-dimensional difference gel electrophoresis (2-D DIGE) technology in combination with mass spectrometry (MS) was applied to detect differentially expressed proteins in 20 pairs of RCC tissues and matched adjacent normal kidney cortex (ANK), in order to search for RCC markers. After gel analysis by DeCyder 6.5 and EDA software, differentially expressed protein spots were excised from Deep Purple stained preparative 2DE gel. A total of 100 proteins were identified by MS out of 2500 spots, 23 and 77 of these were, respectively, over- and down-expressed in RCC. The Principal Component Analysis applied to gels and protein spots exactly separated the two sample classes in two groups: RCC and ANK. Moreover, some spots, including ANXA2, PPIA, FABP7 and LEG1, resulted highly differential. The DIGE data were also confirmed by immunoblotting analysis for these proteins. In conclusion, we suggest that applying 2-D DIGE to RCC may provide the basis for a better molecular characterization and for the discovery of candidate biomarkers.     

Discovery of Novel Serum Biomarkers for Prenatal Down Syndrome Screening by Integrative Data Mining

Background

To facilitate the experimental search for novel maternal serum biomarkers in prenatal Down Syndrome screening, we aimed to create a set of candidate biomarkers using a data mining approach.

Methodology/Principal Findings

Because current screening markers are derived from either fetal liver or placental trophoblasts, we reasoned that new biomarkers can primarily be found to be derived from these two tissues. By applying a three-stage filtering strategy on publicly available data from different sources, we identified 49 potential blood-detectable protein biomarkers. Our set contains three biomarkers that are currently widely used in either first- or second-trimester screening (AFP, PAPP-A and fβ-hCG), as well as ten other proteins that are or have been examined as prenatal serum markers. This supports the effectiveness of our strategy and indicates the set contains other markers potentially applicable for screening.

Conclusions/Significance

We anticipate the set will help support further experimental studies for the identification of new Down Syndrome screening markers in maternal blood.     

Identification of complement C3a as a candidate biomarker in human chronic hepatitis C and HCV-related hepatocellular carcinoma using a proteomics approach

Although the significant risk factors for hepatocellular carcinoma (HCC) are well known from epidemiological studies, diagnosis of this disease at an early stage is difficult, and HCC remains one of the leading causes of cancer death worldwide. Thus, to identify any useful HCC-related biomarkers is still a need. We performed SELDI-TOF MS to identify differentially expressed proteins in HCC serum using weak cation exchange protein chips. Protein characterization was performed by 2-DE separation and nano flow LC-MS/MS. A total of 55 sera were collected from HCC patients and compared with those from 48 patients with chronic hepatitis and 9 healthy individuals. A candidate marker of about 8900 Da was detected as differentially expressed in patients with chronic hepatitis C and hepatitis C virus (HCV)-related HCC. We identified this differentially expressed protein as complement C3a. The expression of C3a in HCC sera was further validated by PS20 chip immunoassay and Western blotting. Complement C3a was found to be elevated in patients with chronic hepatitis C and HCV-related HCC. The combination of SELDI-TOF MS and 2-DE provides a solution to identify disease-associated serum biomarkers.     

MicroRNAs in renal cell carcinoma: diagnostic implications of serum miR-1233 levels

Background

MicroRNA expression is altered in cancer cells, and microRNAs could serve as diagnostic/prognostic biomarker for cancer patients. Our study was designed to analyze circulating serum microRNAs in patients with renal cell carcinoma (RCC).

Methodology/Principal Findings

We first explored microRNA expression profiles in tissue and serum using TaqMan Low Density Arrays in each six malignant and benign samples: Although 109 microRNAs were circulating at higher levels in cancer patients'' serum, we identified only 36 microRNAs with up-regulation in RCC tissue and serum of RCC patients. Seven candidate microRNAs were selected for verification based on the finding of up-regulation in serum and tissue of RCC patients: miR-7-1*, miR-93, miR-106b*, miR-210, miR-320b, miR-1233 and miR-1290 levels in serum of healthy controls (n = 30) and RCC (n = 33) patients were determined using quantitative real-time PCR (TaqMan MicroRNA Assays). miR-1233 was increased in RCC patients, and thus validated in a multicentre cohort of 84 RCC patients and 93 healthy controls using quantitative real-time PCR (sensitivity 77.4%, specificity 37.6%, AUC 0.588). We also studied 13 samples of patients with angiomyolipoma or oncocytoma, whose serum miR-1233 levels were similar to RCC patients. Circulating microRNAs were not correlated with clinical-pathological parameters.

Conclusions/Significance

MicroRNA levels are distinctly increased in cancer patients, although only a small subset of circulating microRNAs has a tumor-specific origin. We identify circulating miR-1233 as a potential biomarker for RCC patients. Larger-scaled studies are warranted to fully explore the role of circulating microRNAs in RCC.     

Integrated Proteomic Analysis of Human Cancer Cells and Plasma from Tumor Bearing Mice for Ovarian Cancer Biomarker Discovery

Background

The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery.

Methodology/Principal Findings

We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease.

Conclusions/Significance

Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.     

Searching for consistently reported up- and down-regulated biomarkers in colorectal cancer: a systematic review of proteomic studies

The cumulative lifetime risk for the development of colorectal cancer in the general population is 6 %. In many cases, early detection by fecal occult blood test is limited regarding sensitivity. Therefore, there is an urgent need for improved diagnostic tests in colorectal cancer. The recent development of high-throughput molecular analytic techniques should allow the rapid evaluation of new diagnostic markers. However, researchers are faced with an overwhelming number of potential markers form numerous colorectal cancer protein expression profiling studies. To address the challenge, we have carried out a comprehensive systematic review of colorectal cancer biomarkers from 13 published studies that compared the protein expression profiles of colorectal cancer and normal tissues. A protein ranking system that considers the number of comparisons in agreement, total sample sizes, average fold-change and direction of differential expression was devised. We observed that some proteins were consistently reported by multiple studies as differentially expressed with a statistically significant frequency (P < 0.05) in cancer versus normal tissues comparison. Our systematic review method identified proteins that were consistently reported as differentially expressed. A review of the top four candidates revealed proteins described previously as having diagnostic value as well as novel candidate biomarkers. These candidates should help to develop a panel of biomarkers with sufficient sensitivity and specificity for the diagnosis of colorectal cancer in a clinical setting.     

Protein expression profiling of endometrial malignancies reveals a new tumor marker: chaperonin 10

Endometrial carcinoma is a common malignancy in women, being exceeded in incidence only by that of breast, lung, and colorectal cancers. At present, no serum tumor markers are available for the monitoring of endometrial carcinoma patients, and patients with recurrent disease are detected only following the development of symptoms or abnormalities in imaging assessments. Similarly, no screening tools are available for endometrial carcinoma. Protein profiling by matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has proven to be a sensitive and fast method of analysis for small proteins or peptides to yield specific biomarkers. In this study, a variety of normal and malignant endometrial tissue samples were fractionated and analyzed by SELDI-TOF MS (SELDI is a version of MALDI utilizing protein "chips"). A number of proteins displayed differential expression in malignant endometrial tissues. One of the prominent proteins fractionated by weak cation exchange chromatography and displaying enhanced expression in these malignant tissues was identified as chaperonin 10. The increased expression of chaperonin 10 in malignant endometrial tissues was further confirmed by parallel Western blot and immunohistochemistry analyses.     

Identification of Protein Markers Specific for Papillary Renal Cell Carcinoma Using Imaging Mass Spectrometry

Since the emergence of proteomics methods, many proteins specific for renal cell carcinoma (RCC) have been identified. Despite their usefulness for the specific diagnosis of RCC, such proteins do not provide spatial information on the diseased tissue. Therefore, the identification of cancer-specific proteins that include information on their specific location is needed. Recently, matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) based imaging mass spectrometry (IMS) has emerged as a new tool for the analysis of spatial distribution as well as identification of either proteins or small molecules in tissues. In this report, surgical tissue sections of papillary RCC were analyzed using MALDI-IMS. Statistical analysis revealed several discriminative cancer-specific m/z-species between normal and diseased tissues. Among these m/z-species, two particular proteins, S100A11 and ferritin light chain, which are specific for papillary RCC cancer regions, were successfully identified using LC-MS/MS following protein extraction from independent RCC samples. The expressions of S100A11 and ferritin light chain were further validated by immunohistochemistry of human tissues and tissue microarrays (TMAs) of RCC. In conclusion, MALDI-IMS followed by LC-MS/MS analysis in human tissue identified that S100A11 and ferritin light chain are differentially expressed proteins in papillary RCC cancer regions.     

Proteomic changes in renal cancer and co-ordinate demonstration of both the glycolytic and mitochondrial aspects of the Warburg effect

Renal cell carcinoma (RCC) is the tenth most common cancer although the incidence is increasing. The main clinical problems stem from the relatively late presentation of many patients due to the often asymptomatic nature of the illness, and the relative insensitivity of metastatic disease to conventional chemotherapy and radiotherapy. Despite increasing knowledge of some of the genetic changes underlying sporadic renal cancer such as those involving the Von Hippel Lindau (VHL) gene, many of the underlying pathophysiological changes are ill-defined and there remains a need for the identification of disease markers for use in diagnosis and prognosis or as potential therapeutic targets. This study has used a proteomic approach, based on two-dimensional gel electrophoresis and mass spectrometry, to compare the protein profiles of conventional RCC tissue with patient-matched normal kidney cortex. Sequencing of 32 protein spots with significantly increased expression in RCC samples (>/= 4/6 patients) and 41 proteins whose levels decreased (6/6 patients) confirmed several previously known RCC-associated changes such as increases in Mn-superoxide dismutase, lactate dehydrogenase-A, aldolase A and C, pyruvate kinase M2, and thymidine phosphorylase. Additionally, several previously unknown changes were identified, including increased expression of three members of the annexin family and increased levels of the actin depolymerisation factor cofilin. The Warburg effect was also demonstrated with the identification of increases in proteins involved in the majority of steps in the glycolytic pathway and decreases in the gluconeogenic reactions, together with a parallel decrease in several mitochondrial enzymes. A number of the alterations seen were further confirmed in additional samples by immunohistochemistry, Western blotting, and laser capture microdissection.     

Mass spectrometric identification of human prostate cancer-derived proteins in serum of xenograft-bearing mice

Lack of sensitivity and specificity of current tumor markers has intensified research efforts to find new biomarkers. The identification of potential tumor markers in human body fluids is hampered by large variability and complexity of both control and patient samples, laborious biochemical analyses, and the fact that the identified proteins are unlikely produced by the diseased cells but are due to secondary body defense mechanisms. In a new approach presented here, we eliminate these problems by performing proteomic analysis in a prostate cancer xenograft model in which human prostate cancer cells form a tumor in an immune-incompetent nude mouse. Using this concept, proteins present in mouse serum that can be identified as human will, by definition, originate from the human prostate cancer xenograft and might have potential diagnostic and prognostic value. Using one-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry, we identified tumor-derived human nm23/nucleoside-diphosphate kinase (NME) in the serum of a nude mouse bearing the androgen-independent human prostate cancer xenograft PC339. NME is known to be involved in the metastatic potential of several tumor cells, including prostate cancer cells. Furthermore we identified six human enzymes involved in glycolysis (fructose-bisphosphate aldolase A, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, alpha enolase, and lactate dehydrogenases A and B) in the serum of the tumor-bearing mice. The presence of human NME and glyceraldehyde-3-phosphate dehydrogenase in the serum of PC339-bearing mice was confirmed by Western blotting. Although the putative usefulness of these proteins in predicting prognosis of prostate cancer remains to be determined, the present data illustrate that our approach is a promising tool for the focused discovery of new prostate cancer biomarkers.