Cancer biomarker development and two-dimensional difference gel electrophoresis (2D-DIGE)

Cancer results from the accumulation of genomic alterations. As the genome is functionally translated to the proteome and regulates tumor cell behavior, proteomics studies are expected to further the current understanding of the molecular mechanisms underlying carcinogenesis and cancer progression. Biomarkers are potential tools to classify cancers for therapy, predict responses to treatments, and support treatment-related decision-making. Biomarker development has been actively pursued in oncology by proteomic approaches. Two-dimensional difference gel electrophoresis (2D-DIGE) is a proteomics technique based on two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In 2D-DIGE, protein samples are labeled with distinct fluorescent dyes before fractionation via 2D-PAGE. 2D-DIGE offers advantages to identify biomarker candidates, including reproducibility, high sensitivity, comprehensiveness, and high throughput. 2D-DIGE has contributed to the establishment of tissue biomarkers, which potentially facilitate precision medicine. 2D-DIGE is thus expected to yield major advancements in cancer biomarker identification and development.     

Searching urinary tumor markers for bladder cancer using a two-dimensional differential gel electrophoresis (2D-DIGE) approach

Aiming at identifying biomarkers for bladder cancer, the urinary proteome was explored through a two-dimensional gel-based proteomic approach (2D-DIGE) coupled with mass spectrometry and database interrogation. The increased expression of proteins differentially expressed between patients with bladder tumors and controls such as Reg-1 and keratin 10 was confirmed to be associated with bladder cancer progression on bladder cancer cell lines by immunoblotting, and bladder tumors by immunohistochemistry. Moreover, the association of these proteins, especially Reg-1, with tumor staging and clinical outcome was confirmed by immunohistochemistry using an independent series of bladder tumors contained in tissue microarrays (n=292). Furthermore, Reg-1 was quantified using an independent series of urinary specimens (n=80) and provided diagnostic utility to discriminate patients with bladder cancer and controls (area under the curve (AUC=0.88)). Thus, the 2D-DIGE approach has identified Reg-1 as a biomarker for bladder cancer diagnostics, staging, and outcome prognosis.     

Sequential depletion of human serum for the search of osteoarthritis biomarkers

ABSTRACT: BACKGROUND: The field of biomarker discovery, development and application has been the subject of intense interest and activity, especially with the recent emergence of new technologies, such as proteomics-based approaches. In proteomics, search for biomarkers in biological fluids such as human serum is a challenging issue, mainly due to the high dynamic range of proteins present in these types of samples. Methods for reducing the content of most highly abundant proteins have been developed, including immunodepletion or protein equalization. In this work, we report for the first time the combination of a chemical sequential depletion method based in two protein precipitations with acetonitrile and DTT, with a subsequent two-dimensional difference in-gel electrophoresis (2D-DIGE) analysis for the search of osteoarthritis (OA) biomarkers in human serum. The depletion method proposed is non-expensive, of easy implementation and allows fast sample throughput. RESULTS: Following this workflow, we have compared sample pools of human serum obtained from 20 OA patients and 20 healthy controls. The DIGE study led to the identification of 16 protein forms (corresponding to 14 different proteins) that were significantly (p < 0.05) altered in OA when compared to controls (8 increased and 7 decreased). Immunoblot analyses confirmed for the first time the increase of an isoform of Haptoglobin beta chain (HPT) in sera from OA patients. CONCLUSIONS: Altogether, these data demonstrate the utility of the proposed chemical sequential depletion for the analysis of sera in protein biomarker discovery approaches, exhibit the usefulness of quantitative 2D gel-based strategies for the characterization of disease-specific patterns of protein modifications, and also provide a list of OA biomarker candidates for validation.     

Proteomics profiling of microdissected low- and high-grade prostate tumors identifies Lamin A as a discriminatory biomarker

Proteomics screening methods for the identification of diagnostic and prognostic biomarkers in cancer are still lagging behind DNA- or RNA-based analysis. We used two-dimensional differential gel electrophoresis (2D-DIGE) in combination with laser capture microdissection (LCM) and MALDI-TOF/TOF mass spectrometry to determine differentially abundant proteins and candidate biomarkers in prostate cancer. Paired (benign and tumor) samples were isolated from 23 Gleason Score 6 (GS 6) and 23 Gleason Score 8 and higher (GS 8+) radical prostatectomy specimens and subjected to 2D-DIGE analysis. Minimal fluorescent dye labeling was applied and electrophoresis performed with triple samples (paired benign and tumor; internal control) for each case of tumor. Nineteen differently abundant proteins were identified by mass spectrometry and further validated. One half of them were associated with glycolysis and the Warburg effect; these were upregulated in tumors. The upregulation correlated with tumor dedifferentiation and might be relevant for selection of therapeutic strategies. Among the other proteins, heat shock protein 60 (HSP60) was significantly upregulated in tumor tissue compared to its benign counterpart. Furthermore, lamin A was statistically highly discriminatory between low and high Gleason score tumors and might serve as a new biomarker of tumor differentiation and prognosis.     

The advancement of biomarker-based diagnostic tools for ovarian, breast, and pancreatic cancer through the use of urine as an analytical biofluid

Despite considerable advancements, the development of effective cancer screening tools based on serum biomarker measurements has thus far failed to achieve a meaningful clinical impact. The incremental progress observed over the course of serum biomarker development suggests that further refinements based on novel approaches may yet result in a breakthrough. The use of urine as an analytical biofluid for biomarker development may represent such an approach. The unique characteristics of urine including a high level of stability, ease of sampling, and an inactive and low-complexity testing matrix offer several potential advantages over the use of serum. A number of recent reports have demonstrated the utility of urine in the identification of novel cancer biomarkers and also the improved performance of biomarkers previously evaluated in serum. In this review, advancements related to the use of urine biomarkers within the settings of ovarian, breast, and pancreatic cancer are presented and discussed. Findings regarding the identification of specific urine biomarkers for each disease are highlighted along with comparative analyses of urine and serum biomarkers as diagnostic tools.     

Tissue proteomics for cancer biomarker development: laser microdissection and 2D-DIGE

Novel cancer biomarkers are required to achieve early diagnosis and optimized therapy for individual patients. Cancer is a disease of the genome, and tumor tissues are a rich source of cancer biomarkers as they contain the functional translation of the genome, namely the proteome. Investigation of the tumor tissue proteome allows the identification of proteomic signatures corresponding to clinico-pathological parameters, and individual proteins in such signatures will be good biomarker candidates. Tumor tissues are also a rich source for plasma biomarkers, because proteins released from tumor tissues may be more cancer specific than those from non-tumor cells. Two-dimensional difference gel electrophoresis (2D-DIGE) with novel ultra high sensitive fluorescent dyes (CyDye DIGE Fluor satulation dye) enables the efficient protein expression profiling of laser-microdissected tissue samples. The combined use of laser microdissection allows accurate proteomic profiling of specific cells in tumor tissues. To develop clinical applications using the identified biomarkers, collaboration between research scientists, clinicians and diagnostic companies is essential, particularly in the early phases of the biomarker development projects. The proteomics modalities currently available have the potential to lead to the development of clinical applications, and channeling the wealth of produced information towards concrete and specific clinical purposes is urgent.     

Identification of a seven glycopeptide signature for malignant pleural mesothelioma in human serum by selected reaction monitoring

Background

Serum biomarkers can improve diagnosis and treatment of malignant pleural mesothelioma (MPM). However, the evaluation of potential new serum biomarker candidates is hampered by a lack of assay technologies for their clinical evaluation. Here we followed a hypothesis-driven targeted proteomics strategy for the identification and clinical evaluation of MPM candidate biomarkers in serum of patient cohorts.

Results

Based on the hypothesis that cell surface exposed glycoproteins are prone to be released from tumor-cells to the circulatory system, we screened the surfaceome of model cell lines for potential MPM candidate biomarkers. Selected Reaction Monitoring (SRM) assay technology allowed for the direct evaluation of the newly identified candidates in serum. Our evaluation of 51 candidate biomarkers in the context of a training and an independent validation set revealed a reproducible glycopeptide signature of MPM in serum which complemented the MPM biomarker mesothelin.

Conclusions

Our study shows that SRM assay technology enables the direct clinical evaluation of protein-derived candidate biomarker panels for which clinically reliable ELISA’s currently do not exist.     

MicroRNA expression profile in serum reveals novel diagnostic biomarkers for endometrial cancer

Purpose: Circulating microRNAs (miRNAs) prove to be promising diagnostic biomarkers for various cancers, including endometrial cancer (EC). The present study aims to identify serum microRNAs that can serve as potential biomarkers for EC diagnosis.Patients and methods: A total of 92 EC and 102 normal control (NC) serum samples were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) in this four-phase experiment. The logistic regression method was used to construct a diagnostic model based on the differentially expressed miRNAs in serum. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value. To further validate the diagnostic capacity of the identified signature, the 6-miRNA marker was compared with previously reported biomarkers and verified in three public datasets. In addition, the expression characteristics of the identified miRNAs were further explored in tissue and serum exosomes samples.Results: Six miRNAs (miR-143-3p, miR-195-5p, miR-20b-5p, miR-204-5p, miR-423-3p, and miR-484) were significantly overexpressed in the serum of EC compared with NCs. Areas under the ROC of the 6-miRNA signatures were 0.748, 0.833, and 0.967 for the training, testing, and the external validation phases, respectively. The identified signature has a very stable diagnostic performance in the large cohorts of three public datasets. Compared with previously identified miRNA biomarkers, the 6-miRNA signature in the present study has superior performance in diagnosing EC. Moreover, the expression of miR-143-3p and miR-195-5p in tissues and the expression of miR-20b-5p in serum exosomes were consistent with those in serum.Conclusions: We established a 6-miRNA signature in serum and they could function as potential non-invasive biomarker for EC diagnosis.     

Cancer-associated carbohydrate antigens as potential biomarkers for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common human malignancies. Therefore, developing the early, high-sensitivity diagnostic biomarkers to prevent HCC is urgently needed. Serum a-fetoprotein (AFP), the clinical biomarker in current use, is elevated in only ~60% of patients with HCC; therefore, identification of additional biomarkers is expected to have a significant impact on public health. In this study, we used glycan microarray analysis to explore the potential diagnostic value of several cancer-associated carbohydrate antigens (CACAs) as biomarkers for HCC. We used glycan microarray analysis with 58 different glycan analogs for quantitative comparison of 593 human serum samples (293 HCC samples; 133 chronic hepatitis B virus (HBV) infection samples, 134 chronic hepatitis C virus (HCV) infection samples, and 33 healthy donor samples) to explore the diagnostic possibility of serum antibody changes as biomarkers for HCC. Serum concentrations of anti-disialosyl galactosyl globoside (DSGG), anti-fucosyl GM1 and anti-Gb2 were significantly higher in patients with HCC than in chronic HBV infection individuals not in chronic HCV infection patients. Overall, in our study population, the biomarker candidates DSGG, fucosyl GM1 and Gb2 of CACAs achieved better predictive sensitivity than AFP. We identified potential biomarkers suitable for early detection of HCC. Glycan microarray analysis provides a powerful tool for high-sensitivity and high-throughput detection of serum antibodies against CACAs, which may be valuable serum biomarkers for the early detection of persons at high risk for HCC.     

On the identification of biomarkers for non-small cell lung cancer in serum and pleural effusion

The current imperative need for new biomarkers of non-small cell lung cancer (NSCLC) prompted us to compare the proteome of serum and pleural effusion samples from cancer patients with those with benign lung diseases as pneumonia or tuberculosis. Samples were prefractionated through affinity chromatography prior to 2D-DIGE to detect proteins with altered expression in cancer patients. Overall, we identified more potential biomarkers in pleural effusion, which is closer to the affected organ, than in serum. Nevertheless, in both cases principal component analysis demonstrated that the pattern of significantly altered proteins discriminates between disease groups.The biomarker candidates comprise proteins increased in malignant pleural effusions as gelsolin and the metalloproteinase inhibitor 2, and others with lower levels as S100-A8 and S100-A9. The most interesting protein was the pigment epithelium-derived factor (PEDF), which is related to angiogenesis inhibition, and was significantly overexpressed both in serum and pleural effusion from NSCLC patients. More than 12 PEDF isoforms were specifically immunodetected in both fluids in 2-D blots, most of them overexpressed in NSCLC. Thus, further validation would be ideally directed to quantify individual PEDF isoforms, as it may be only one or some of them the ones altered in the cancer process.     

Markers of small cell lung cancer

Lung cancer is the number one cause of cancer death; however, no specific serum biomarker is available till date for detection of early lung cancer. Despite good initial response to chemotherapy, small-cell lung cancer (SCLC) has a poor prognosis. Therefore, it is important to identify molecular markers that might influence survival and may serve as potential therapeutic targets. The review aims to summarize the current knowledge of serum biomarkers in SCLC to improve diagnostic efficiency in the detection of tumor progression in lung cancer. The current knowledge on the known serum cytokines and tumor biomarkers of SCLC is emphasized. Recent findings in the search for novel diagnostic and therapeutic molecular markers using the emerging genomic technology for detecting lung cancer are also described. It is believed that implementing these new research techniques will facilitate and improve early detection, prognostication and better treatment of SCLC.     

Prospects for developing an accurate diagnostic biomarker panel for low prevalence cancers

Background

Early detection screening of asymptomatic populations for low prevalence cancers requires a highly specific test in order to limit the cost and anxiety produced by falsely positive identifications. Most solid cancers are a heterogeneous collection of diseases as they develop from various combinations of genetic lesions and epigenetic modifications. Therefore, it is unlikely that a single test will discriminate all cases of any particular cancer type. We propose a novel, intuitive biomarker panel design that accommodates disease heterogeneity by allowing for diverse biomarker selection that increases diagnostic accuracy.

Methods

Using characteristics of nine pancreatic ductal adenocarcinoma (PDAC) biomarkers measured in human sera, we modeled the behavior of biomarker panels consisting of a sum of indicator variables representing a subset of biomarkers within a larger biomarker data set. We then chose a cutoff for the sum to force specificity to be high and delineated the number of biomarkers required for adequate sensitivity of PDAC in our panel design.

Results

The model shows that a panel consisting of 40 non-correlated biomarkers characterized individually by 32% sensitivity at 95% specificity would require any 7 biomarkers to be above their respective thresholds and would result in a panel specificity and sensitivity of 99% each.

Conclusions

A highly accurate blood-based diagnostic panel can be developed from a reasonable number of individual serum biomarkers that are relatively weak classifiers when used singly. A panel constructed as described is advantageous in that a high level of specificity can be forced, accomplishing a prerequisite for screening asymptomatic populations for low-prevalence cancers.

     

Critical dependence of blood-borne biomarker concentrations on the half-lives of their carrier proteins

Until recently, the low-abundance (LA) range of the serum proteome was an unexplored reservoir of diagnostic information. Today it is increasingly appreciated that a diagnostic goldmine of LA biomarkers resides in the blood stream in complexed association with more abundant higher molecular weight carrier proteins such as albumin and immunoglobulins. As we now look to the possibility of harvesting these LA biomarkers more efficiently through engineered nano-scale particles, mathematical approaches are needed in order to reveal the mechanisms by which blood carrier proteins act as molecular ‘mops’ for LA diagnostic cargo, and the functional relationships between bound LA biomarker concentrations and other variables of interest such as biomarker intravasation and clearance rates and protein half-lives in the bloodstream. Here we show, by simple mathematical modeling, how the relative abundance of large carrier proteins and their longer half-lives in the bloodstream work together to amplify the total blood concentration of these tiny biomarkers. The analysis further suggests that alterations in the production of biomarkers lead to gradual rather than immediate changes in biomarker levels in the blood circulation. The model analysis also points to the characteristics of artificial nano-particles that would render them more efficient harvesters of tumor biomarkers in the circulation, opening up possibilities for the early detection of curable disease, rather than simply better detection of advanced disease.     

Proteomic analysis of maternal serum in down syndrome: identification of novel protein biomarkers

Down syndrome (DS) is the most prevalent chromosomal disorder, accounting for significant morbidity and mortality. Definitive diagnosis requires invasive amniocentesis, and current maternal serum-based testing requires a false-positive rate of about 5% to detect 85% of affected pregnancies. We have performed a comprehensive proteomic analysis to identify potential serum biomarkers to detect DS. First- and second-trimester maternal serum samples of DS and gestational age-matched controls were analyzed using multiple, complementary proteomic approaches, including fluorescence 2-dimensional gel electrophoresis (2D-DIGE), 2-dimensional liquid chromatography-chromatofocusing (2D-CF), multidimensional protein identification technology (MudPIT; LC/LC-MS/MS), and MALDI-TOF-MS peptide profiling. In total, 28 and 26 proteins were differentially present in first- and second-trimester samples, respectively. Of these, 19 were specific for the first trimester and 16 for the second trimester, and 10 were differentially present in both trimesters. Analysis of MALDI-TOF-MS peptide profiles with pattern-recognition software also discriminated between DS and controls in both trimesters, with an average recognition capability approaching 96%. A majority of the biomarkers identified are serum glycoproteins that may play a role in cellular differentiation and growth of fetus. Further characterization and quantification of these markers in a larger cohort of subjects may provide the basis for new tests for improved DS screening.     

Proteomic profiling of cerebrospinal fluid identifies biomarkers for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of motor neurons. We tested the hypothesis that proteomic analysis will identify protein biomarkers that provide insight into disease pathogenesis and are diagnostically useful. To identify ALS specific biomarkers, we compared the proteomic profile of cerebrospinal fluid (CSF) from ALS and control subjects using surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). We identified 30 mass ion peaks with statistically significant (p < 0.01) differences between control and ALS subjects. Initial analysis with a rule-learning algorithm yielded biomarker panels with diagnostic predictive value as subsequently assessed using an independent set of coded test subjects. Three biomarkers were identified that are either decreased (transthyretin, cystatin C) or increased (carboxy-terminal fragment of neuroendocrine protein 7B2) in ALS CSF. We validated the SELDI-TOF-MS results for transthyretin and cystatin C by immunoblot and immunohistochemistry using commercially available antibodies. These findings identify a panel of CSF protein biomarkers for ALS.     

High-sensitivity blood-based detection of breast cancer by multi photon detection diagnostic proteomics

We have developed several new methods for blood-based cancer detection by diagnostic proteomics. Ultrasensitive methods of immunoassay using multiphoton-detection (IA/MPD) increase sensitivity by 200- to 1,000-fold (1 femtogram/mL). This has allowed the measurement of cancer biomarkers with very low concentrations in blood that could not be measured for full patient cohorts with conventional immunoassays. Sensitivity and specificity in cancer detection have been found to be potentiated by use of immunoassay panels which include tissue-specific cancer biomarkers as well as cytokines and angiogenic factors. The ultrasensitive immunoassays revealed that patient to patient variations in the concentrations of individual biomarkers in blood can extend over many orders of magnitude (up to six) and that the distributions of biomarker concentrations over patient cohorts are non-Gaussian. New methods of data analysis which correlate abundances of multiple, different biomarkers have been developed to deal with such data sets. Sensitivity and specificity of about 95% have been achieved for blood-based detection of breast cancer in pilot studies on 250 patients and 95 controls. Pilot studies indicate that this methodology may also allow differentiation of malignant breast cancer from benign lesions and can provide similar sensitivity and specificity for other epithelial cancers such as prostate cancer, ovarian cancer and melanoma. The methods developed for selection, application, and evaluation of very high sensitivity biomarker panels are expected to have general relevance for diagnostic proteomics.     

Sex-Specific Urinary Biomarkers for Diagnosing Bipolar Disorder

Sex-based differences are prominent in affective disorders, but there are no biomarkers available to support sex-specific, laboratory-based diagnostics for male and female bipolar disorder (BD) patients. Here, a NMR-based metabonomic approach was used to preliminarily identify sex-specific urinary metabolite biomarkers for diagnosing male and female BD patients. A male-specific biomarker panel consisting of four metabolites (α-hydroxybutyrate, choline, formate, and N-methylnicotinamide) effectively discriminated between male BD and healthy controls (HC) subjects, achieving an area under the receiver operating characteristic curve (AUC) of 0.942. A female-specific biomarkers panel consisting of four metabolites (α-hydroxybutyrate, oxalacetate, acetone, and N-methylnicotinamide) effectively discriminated between female BD and HC subjects, achieving an AUC of 0.909. The male-specific biomarker panel displayed low discriminatory power in the female group, and the female-specific biomarker panel displayed low discriminatory power in the male group. Moreover, several other metabolites showed different trends between male and female BD subjects. These findings suggest that male and female BD patients have distinct biomarker fingerprints and that these two sex-specific biomarker panels may serve as effective diagnostic tools in distinguishing male and female BD patients from their healthy counterparts. Our work may provide a window into the mechanisms underlying the pathoetiology of BD in both men and women.     

Tissue and serum proteomic profiling for diagnostic and prognostic bladder cancer biomarkers

A panel of biomarkers for the early detection of bladder cancer has not yet been identified. Many different molecules, including DNA, RNA or proteins have been reported but none have provided adequate sensitivity for a single-tier screening test or a test to replace cystoscopy. Therefore, multimarker panels are discussed at present to give a more-precise answer to the biomarker quest. Mass spectrometry or 2D gel-electrophoresis have evolved greatly within recent years and are capable of analyzing multiple proteins or peptides in parallel with high sensitivity and specificity. However, transmission of screening results from one laboratory to another is still the main pitfall of those methods; a fact that emphasizes the need for consistent and standardized procedures as suggested by the Human Proteome Organization (HUPO). In this article, recent results in screening approaches and other proteomic techniques used for biomarker evaluation in bladder cancer are discussed with a focus on serum and tissue biomarkers.     

Diagnosis of Alzheimer's disease based on disease-specific autoantibody profiles in human sera

After decades of Alzheimer's disease (AD) research, the development of a definitive diagnostic test for this disease has remained elusive. The discovery of blood-borne biomarkers yielding an accurate and relatively non-invasive test has been a primary goal. Using human protein microarrays to characterize the differential expression of serum autoantibodies in AD and non-demented control (NDC) groups, we identified potential diagnostic biomarkers for AD. The differential significance of each biomarker was evaluated, resulting in the selection of only 10 autoantibody biomarkers that can effectively differentiate AD sera from NDC sera with a sensitivity of 96.0% and specificity of 92.5%. AD sera were also distinguishable from sera obtained from patients with Parkinson's disease and breast cancer with accuracies of 86% and 92%, respectively. Results demonstrate that serum autoantibodies can be used effectively as highly-specific and accurate biomarkers to diagnose AD throughout the course of the disease.     

Tissue and serum proteomic profiling for diagnostic and prognostic bladder cancer biomarkers

A panel of biomarkers for the early detection of bladder cancer has not yet been identified. Many different molecules, including DNA, RNA or proteins have been reported but none have provided adequate sensitivity for a single-tier screening test or a test to replace cystoscopy. Therefore, multimarker panels are discussed at present to give a more-precise answer to the biomarker quest. Mass spectrometry or 2D gel-electrophoresis have evolved greatly within recent years and are capable of analyzing multiple proteins or peptides in parallel with high sensitivity and specificity. However, transmission of screening results from one laboratory to another is still the main pitfall of those methods; a fact that emphasizes the need for consistent and standardized procedures as suggested by the Human Proteome Organization (HUPO). In this article, recent results in screening approaches and other proteomic techniques used for biomarker evaluation in bladder cancer are discussed with a focus on serum and tissue biomarkers.