Emerging molecular biomarkers--blood-based strategies to detect and monitor cancer. Nat Rev Clin Oncol. 2011;8:142-150. [PMID: 21364687 DOI: 10.1038/nrclinonc.2010.220]

Impact of Biomarkers on Personalized Medicine

The field of personalized medicine that involves the use of measuring biomarkers in clinical samples is an area of high interest and one that has tremendous impact on drug development. With the emergence of more sensitive and specific technologies that are now able to be run in clinical settings and the ability to accurately measure biomarkers, there is a need to understand how biomarkers are defined, how they are used in clinical trials, and most importantly how they are used in conjunction with drug treatment. Biomarker approaches have entered into early clinical trials and are increasingly being used to develop new diagnostics that help to differentiate or stratify the likely outcomes of therapeutic intervention. Tremendous efforts have been made to date to discover novel biomarkers for use in clinical practice. Still, the number of markers that make it into clinical practice is rather low. In the next following chapters, we will explain the various classifications of biomarkers, how they are applied, measured, and used in personalized medicine specifically focusing on how they are used in de-risking the 10 plus years drug development process and lastly how they are validated and transformed into companion diagnostic assays.

A highly specific and sensitive electroanalytical strategy for microRNAs based on amplified silver deposition by the synergic TiO2 photocatalysis and guanine photoreduction using charge-neutral probes

TiO₂ photocatalysis and guanine photoreduction were synergically combined for amplifying silver deposition toward sensitive electroanalysis of microRNAs using charge-neutral probes.

Personalized biomarkers to monitor disease progression in advanced non-small-cell lung cancer patients treated with icotinib

BACKGROUND

Disease-specific humoral immune response-related protein complexes in blood are associated with disease progression.

METHODS

Thirty-one patients with stage IIIB and IV non-small-cell lung cancer (NSCLC) were administered with oral dose of icotinib hydrochloride (150 mg twice daily or 125 mg 3 times daily) for a 28-continuous-day cycle until diseases progressed or unacceptable toxicity occurred. The levels of immunoinflammation-related protein complexes (IIRPCs) in a series of plasma samples from 31 NSCLC patients treated with icotinib hydrochloride were determined by an optimized native polyacrylamide gel electrophoresis.

RESULTS

Three characteristic patterns of the IIRPCs, named as patterns a, b, and c, respectively, were detected in plasma samples from 31 patients. Prior to the treatment, there were 18 patients in pattern a consisting of 5 IIRPCs, 9 in pattern b consisting of six IIRPCs, and 4 in pattern c without the IIRPCs. The levels of the IIRPCs in 27 patients were quantified. Our results indicate that the time length of humoral immune and inflammation response (TLHIIR) was closely associated with disease progression, and the median TLHIIR was 22.0 weeks, 95% confidence interval: 16.2 to 33.0 weeks, with a lead time of median 11 weeks relative to clinical imaging evidence confirmed by computed tomography or magnetic resonance imaging (the median progression-free survival, 34.0 weeks, 95% confidence interval: 27.9 to 49.0 weeks).

CONCLUSIONS

The complex relationships between humoral immune response, acquired resistance, and disease progression existed. Personalized IIRPCs could be indicators to monitor the disease progression.

Discovery and validation of new potential biomarkers for early detection of colon cancer

BACKGROUND

Accurate detection of characteristic proteins secreted by colon cancer tumor cells in biological fluids could serve as a biomarker for the disease. The aim of the present study was to identify and validate new serum biomarkers and demonstrate their potential usefulness for early diagnosis of colon cancer.

METHODS

The study was organized in three sequential phases: 1) biomarker discovery, 2) technical and biological validation, and 3) proof of concept to test the potential clinical use of selected biomarkers. A prioritized subset of the differentially-expressed genes between tissue types (50 colon mucosa from cancer-free individuals and 100 normal-tumor pairs from colon cancer patients) was validated and further tested in a series of serum samples from 80 colon cancer cases, 23 patients with adenoma and 77 cancer-free controls.

RESULTS

In the discovery phase, 505 unique candidate biomarkers were identified, with highly significant results and high capacity to discriminate between the different tissue types. After a subsequent prioritization, all tested genes (N = 23) were successfully validated in tissue, and one of them, COL10A1, showed relevant differences in serum protein levels between controls, patients with adenoma (p = 0.0083) and colon cancer cases (p = 3.2e-6).

CONCLUSION

We present a sequential process for the identification and further validation of biomarkers for early detection of colon cancer that identifies COL10A1 protein levels in serum as a potential diagnostic candidate to detect both adenoma lesions and tumor.

IMPACT

The use of a cheap serum test for colon cancer screening should improve its participation rates and contribute to decrease the burden of this disease.

Isocitrate dehydrogenase 1 is a novel plasma biomarker for the diagnosis of non-small cell lung cancer

PURPOSE

Effective biomarkers for the diagnosis of non-small cell lung cancer (NSCLC) are needed. We previously showed that isocitrate dehydrogenase 1 (IDH1) is significantly increased in NSCLC tumors. This study aimed to examine the plasma levels of IDH1 in a large patient population to evaluate its effectiveness in NSCLC diagnosis.

EXPERIMENTAL DESIGN

The plasma levels of IDH1, CA125, Cyfra21-1, and CEA were assayed by ELISA. Blood samples were obtained from 1,422 participants (943 patients with NSCLC and 479 healthy controls). The samples were randomly divided into a training set and a test set. Receiver operating characteristic and binary logistic regression analyses were applied to evaluate diagnostic efficacy and establish diagnostic mathematical models.

RESULTS

Plasma IDH1 levels were significantly higher in patients with NSCLCs than in healthy controls (P < 0.001). The diagnostic use of IDH1 in lung adenocarcinoma [area under curve (AUC): 0.858 and 0.810; sensitivity: 77.1% and 76.2%; specificity: 82.9% and 76.6%; in the training set and test set, respectively] was significantly greater than that of CA125, Cyfra21-1, or CEA (P < 0.001). The model combining IDH1 with CEA, CA125, and Cyfra21-1 was more effective for lung adenocarcinoma diagnosis than IDH1 alone (sensitivity and specificity in the training set: 75.8%, 89.6%; test set: 86.3%, 70.7%). In addition, the plasma levels of IDH1 could contribute to the diagnostic model of lung squamous cell carcinoma.

CONCLUSIONS

IDH1 can be used as a plasma biomarker for the diagnosis of NSCLCs, particularly lung adenocarcinoma, with relatively high sensitivity and specificity.

Comparing efficiency of micro-RNA and mRNA biomarker liberation with microbubble-enhanced ultrasound exposure

Blood biomarkers are potentially powerful diagnostic tools that are limited clinically by low concentrations, the inability to determine biomarker origin and unknown patient baseline. Recently, ultrasound has been shown to liberate proteins and large mRNA biomarkers, overcoming many of these limitations. We have since demonstrated that adding lipid-stabilized microbubbles elevates mRNA concentration an order of magnitude compared with ultrasound without microbubbles, in vitro. Unfortunately the large size of some mRNA molecules may limit efficiency of release and hinder efficacy as an ultrasound-liberated biomarker. We hypothesize that smaller molecules will be released more efficiently with ultrasound than larger molecules. Although investigation of large libraries of biomarkers should be performed to fully validate this hypothesis, we focus on a small subset of mRNA and micro-RNAs. Specifically, we focus on miR-21 (22 base pairs [bp]), which is upregulated in certain forms of cancer, compared with previously investigated mammaglobin mRNA (502 bp). We also report release of micro-RNA miR-155 (22 bp) and housekeeping rRNA S18 (1869 bp). More than 10 million additional miR-21 copies per 100,000 cells are released with ultrasound-microbubble exposure. The low- molecular-weight miR-21 proved to be liberated 50 times more efficiently than high-molecular-weight mammaglobin mRNA, releasing orders of magnitude more miR-21 than mammaglobin mRNA under comparable conditions.

Universal disease biomarker: can a fixed set of blood microRNAs diagnose multiple diseases?

BACKGROUND

The selection of disease biomarkers is often difficult because of their unstable identification, i.e., the selection of biomarkers is heavily dependent upon the set of samples analyzed and the use of independent sets of samples often results in a completely different set of biomarkers being identified. However, if a fixed set of disease biomarkers could be identified for the diagnosis of multiple diseases, the difficulties of biomarker selection could be reduced.

RESULTS

In this study, the previously identified universal disease biomarker (UDB) consisting of blood miRNAs that could discriminate between patients with multiple diseases and healthy controls was extended to the recently reported independent measurements of blood microRNAs (miRNAs). The performance achieved by UDB in an independent set of samples was competitive with performances achieved with biomarkers selected using lasso, a standard, heavily sample-dependent procedure. Furthermore, the development of stable feature extraction was suggested to be a key factor in constructing more efficient and stable (i.e., sample- and disease-independent) UDBs.

CONCLUSIONS

The previously proposed UDB was successfully extended to an additional seven diseases and is expected to be useful for the diagnosis of other diseases.

Detection of aberrant promoter methylation of RNF180, DAPK1 and SFRP2 in plasma DNA of patients with gastric cancer

Gastric cancer (GC) is one of the most frequently diagnosed malignancies in East Asia, particularly in China, and remains the second leading cause of cancer-associated mortality worldwide. However, no effective plasma biomarkers have been identified for the diagnosis of patients with GC. The aim of this study was to investigate the DNA methylation status of the ring finger protein 180 (RNF180), secreted frizzled-related protein 2 (SFRP2) and death-associated protein kinase 1 (DAPK1) genes in the plasma samples of 57 GC patients and 42 control individuals with no malignant disease, and to evaluate the clinical utility of these makers. A significantly higher level of methylation was observed in the plasma DNA of GC patients when compared with that of controls for the three genes investigated (RNF180, 57.89% vs. 23.81%; DAPK1, 49.12% vs. 28.57%; and SFRP2, 71.93% vs. 42.86%). No association was identified between the DAPK1 or SFRP2 methylation level in the plasma DNA and the clinicopathological parameters of patients. Notably, RNF180 methylation was found to positively correlate with tumor size (P=0.018), histological type (P=0.025), TNM stage (P=0.002), lymph node metastasis (P=0.008) and distant metastasis (P=0.018). Overall, 50 cancer patients (87.72%) exhibited methylation of at least one of the three markers, while 26 normal subjects presented methylation in plasma DNA [specificity, 38.1%; odds ratio (OR), 4.4]. The combined use of RNF180 and SFRP2 as methylation markers appeared to be the most preferable predictor with regard to predictive power and cost-performance (OR, 5.57; P=0.0002). The results of the present study indicate that aberrant promoter methylation of genes in the plasma may be detected in a substantial proportion of GC patients and thus, these genes must be evaluated in the screening and surveillance of GC.

Reproductive and hormonal risk factors for antinuclear antibodies (ANA) in a representative sample of U.S. women

BACKGROUND

Autoantibodies are of growing interest in cancer research as potential biomarkers; yet, the determinants of autoimmunity are not well understood. Antinuclear antibodies (ANA) are common in the general population and are more prevalent in women and older adults. Here, we examined the relationship of ANA with reproductive and hormonal factors in a representative sample of U.S. women.

METHODS

We analyzed data on reproductive history and exogenous hormone use in relation to serum ANA in 2,037 females ages 12 years and older from the National Health and Nutrition Examination Survey (NHANES; 1999-2004). Estimated ANA prevalences were adjusted for sampling weights. Prevalence ORs (POR) and 95% confidence intervals (CI) were adjusted for age, race, and poverty-income ratio, and models were stratified by menopause status.

RESULTS

In premenopausal women ages 20 years and older, ANA prevalence was associated with parity (P < 0.001; parous vs. nulliparous POR = 2.0; 95% CI, 1.2-3.4), but in parous women, ANA did not vary by number of births, age at first birth, years since last birth, or breastfeeding. In postmenopausal women, ANA prevalence was associated with an older age at menarche (P = 0.019; age 16-20 vs. 10-12 years POR = 3.0; 95% CI, 1.6-5.9), but not with parity. Oral contraceptives and estrogen therapy were not associated with a higher ANA prevalence.

CONCLUSIONS

Childbearing (having had one or more births) may explain age-associated elevations in ANA prevalence seen in premenopausal women.

IMPACT

These findings highlight the importance of considering reproductive history in studies of autoimmunity and cancer in women.

Serum biomarkers reflecting specific tumor tissue remodeling processes are valuable diagnostic tools for lung cancer

Extracellular matrix (ECM) proteins, such as collagen type I and elastin, and intermediate filament (IMF) proteins, such as vimentin are modified and dysregulated as part of the malignant changes leading to disruption of tissue homeostasis. Noninvasive biomarkers that reflect such changes may have a great potential for cancer. Levels of matrix metalloproteinase (MMP) generated fragments of type I collagen (C1M), of elastin (ELM), and of citrullinated vimentin (VICM) were measured in serum from patients with lung cancer (n = 40), gastrointestinal cancer (n = 25), prostate cancer (n = 14), malignant melanoma (n = 7), chronic obstructive pulmonary disease (COPD) (n = 13), and idiopathic pulmonary fibrosis (IPF) (n = 10), as well as in age-matched controls (n = 33). The area under the receiver operating characteristics (AUROC) was calculated and a diagnostic decision tree generated from specific cutoff values. C1M and VICM were significantly elevated in lung cancer patients as compared with healthy controls (AUROC = 0.98, P < 0.0001) and other cancers (AUROC = 0.83 P < 0.0001). A trend was detected when comparing lung cancer with COPD+IPF. No difference could be seen for ELM. Interestingly, C1M and VICM were able to identify patients with lung cancer with a positive predictive value of 0.9 and an odds ratio of 40 (95% CI = 8.7–186, P < 0.0001). Biomarkers specifically reflecting degradation of collagen type I and citrullinated vimentin are applicable for lung cancer patients. Our data indicate that biomarkers reflecting ECM and IMF protein dysregulation are highly applicable in the lung cancer setting. We speculate that these markers may aid in diagnosing and characterizing patients with lung cancer.

A blood-based proteomic classifier for the molecular characterization of pulmonary nodules

Each year, millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. Because most of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, we identified 371 protein candidates and developed a multiple reaction monitoring (MRM) assay for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and stage IA lung cancer matched for nodule size, age, gender, and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a negative predictive value (NPV) of 90%. Validation performance on samples from a nondiscovery clinical site showed an NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, and FOS) that are associated with lung cancer, lung inflammation, and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history, and age, which are risk factors used for clinical management of pulmonary nodules. Thus, this molecular test provides a potential complementary tool to help physicians in lung cancer diagnosis.

Current status of circulating protein biomarkers to aid the early detection of lung cancer

ABSTRACT: 

Considerable efforts have been undertaken to produce an effective screening method to reduce lung cancer mortality. Imaging tools such as low-dose computed tomography has shown an increase in the detection of early disease and a reduction in the rate of death. This screening modality has, however, several limitations, such as overdiagnosis and a high rate of false positives. Therefore, new screening methods, such as the use of circulating protein biomarkers, have emerged as an option that could complement imaging studies. In this review, current imaging techniques applied to lung cancer screening protocols are presented, as well as up-to-date status of circulating protein biomarker panels that may improve lung cancer diagnosis. Additionally, diverse statistical and artificial intelligence tools applied to the design and optimization of these panels are discussed along with the presentation of two commercially available blood tests recently developed to help detect lung cancer early.

Plasma DNA integrity as a biomarker for primary and metastatic breast cancer and potential marker for early diagnosis

Circulating or cell-free DNA (cfDNA) has been evaluated as a biomarker in many cancers including breast cancer. In particular, integrity of cfDNA has been shown to be altered in cancers. We have estimated the biomarker potential of cfDNA in primary (PBC) and metastatic breast cancer (MBC). cfDNA integrity (cfDI) and concentration were determined in plasma of 383 individuals, including 82 PBC and 201 MBC cases, as well as 100 healthy controls, by measuring ALU and LINE1 repetitive DNA elements using quantitative PCR. The MBC patient group was further sub-divided into patients with detectable circulating tumour cells (CTCpos-MBC, n = 100) and those without (CTCneg-MBC, n = 101). A hierarchical decrease in cfDI and increase in cfDNA concentration from healthy controls to PBC and further onto MBC patients were observed. Investigation of cfDNA in media of cell lines was in concordance with these results. Combination of cfDI and cfDNA concentration could differentiate PBC cases from controls (area under the curve, AUC = 0.75), MBC cases from controls (AUC = 0.81 for CTCneg-MBC, AUC = 0.93 for CTCpos-MBC), and CTCneg-MBC from CTCpos-MBC cases (AUC = 0.83). cfDI additionally demonstrated a positive correlation to progression-free (HR of 0.46 for ALU, P = 0.0025) and overall survival (HR of 0.15 for ALU and 0.20 for LINE1, P < 0.0001) in MBC, and had lower prediction error than CTC status. Our findings show that reduced cfDI and increased cfDNA concentration can serve as diagnostic markers for PBC and MBC, and cfDI as a prognostic marker for MBC, thereby making them attractive candidates for blood-based multi-marker assays.

From mice to men: GEMMs as trial patients for new NSCLC therapies

Given the large socio-economic burden of cancer, there is an urgent need for in vivo animal cancer models that can provide a rationale for personalised therapeutic regimens that are translatable to the clinic. Recent developments in establishing mouse models that closely resemble human lung cancers involve the application of genetically engineered mouse models (GEMMs) for use in drug efficacy studies or to guide patient therapy. Here, we review recent applications of GEMMs in non-small cell lung cancer research for drug development and their potential in aiding biomarker discovery and understanding of biological mechanisms behind clinical outcomes and drug interactions.

Vibrational spectroscopy of biofluids for disease screening or diagnosis: translation from the laboratory to a clinical setting

There remains a need for objective and cost-effective approaches capable of diagnosing early-stage disease in point-of-care clinical settings. Given an increasingly ageing population resulting in a rising prevalence of chronic diseases, the need for screening to facilitate the personalising of therapies to prevent or slow down pathology development will increase. Such a tool needs to be robust but simple enough to be implemented into clinical practice. There is interest in extracting biomarkers from biofluids (e.g., plasma or serum); techniques based on vibrational spectroscopy provide an option. Sample preparation is minimal, techniques involved are relatively low-cost, and data frameworks are available. This review explores the evidence supporting the applicability of vibrational spectroscopy to generate spectral biomarkers of disease in biofluids. We extend the inter-disciplinary nature of this approach to hypothesise a microfluidic platform that could allow such measurements. With an appropriate lightsource, such engineering could revolutionize screening in the 21(st) century.

Fully automated circulating tumor cell isolation platform with large-volume capacity based on lab-on-a-disc

Full automation with high purity for circulating tumor cell (CTC) isolation has been regarded as a key goal to make CTC analysis a "bench-to-bedside" technology. Here, we have developed a novel centrifugal microfluidic platform that can isolate the rare cells from a large volume of whole blood. To isolate CTCs from whole blood, we introduce a disc device having the biggest sample capacity as well as manipulating blood cells for the first time. The fully automated disc platform could handle 5 mL of blood by designing the blood chamber having a triangular obstacle structure (TOS) with lateral direction. To guarantee high purity that enables molecular analysis with the rare cells, CTCs were bound to the microbeads covered with anti-EpCAM to discriminate density between CTCs and blood cells and the CTCs being heavier than blood cells were only settled under a density gradient medium (DGM) layer. To understand the movement of CTCs under centrifugal force, we performed computational fluid dynamics simulation and found that their major trajectories were the boundary walls of the DGM chamber, thereby optimizing the chamber design. After whole blood was inserted into the blood chamber of the disc platform, size- and density-amplified cancer cells were isolated within 78 min, with minimal contamination as much as approximately 12 leukocytes per milliliter. As a model of molecular analysis toward personalized cancer treatment, we performed epidermal growth factor receptor (EGFR) mutation analysis with HCC827 lung cancer cells and the isolated cells were then successfully detected for the mutation by PCR clamping and direct sequencing.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

Breast cancer metastasis suppressor-1 promoter methylation in cell-free DNA provides prognostic information in non-small cell lung cancer

BACKGROUND

Breast-cancer metastasis suppressor 1 (BRMS1) gene encodes for a predominantly nuclear protein that differentially regulates the expression of multiple genes, leading to suppression of metastasis without blocking orthotropic tumour growth. The aim of the present study was to evaluate for the first time the prognostic significance of BRMS1 promoter methylation in cell-free DNA (cfDNA) circulating in plasma of non-small cell lung cancer (NSCLC) patients. Towards this goal, we examined the methylation status of BRMS1 promoter in NSCLC tissues, matched adjacent non-cancerous tissues and corresponding cfDNA as well as in an independent cohort of patients with advanced NSCLC and healthy individuals.

METHODS

Methylation of BRMS1 promoter was examined in 57 NSCLC tumours and adjacent non-cancerous tissues, in cfDNA isolated from 48 corresponding plasma samples, in cfDNA isolated from plasma of 74 patients with advanced NSCLC and 24 healthy individuals.

RESULTS

The BRMS1 promoter was highly methylated both in operable NSCLC primary tissues (59.6%) and in corresponding cfDNA (47.9%) but not in cfDNA from healthy individuals (0%), while it was also highly methylated in cfDNA from advanced NSCLC patients (63.5%). In operable NSCLC, Kaplan-Meier estimates were significantly different in favour of patients with non-methylated BRMS1 promoter in cfDNA, concerning both disease-free interval (DFI) (P=0.048) and overall survival (OS) (P=0.007). In advanced NSCLC, OS was significantly different in favour of patients with non-methylated BRMS1 promoter in their cfDNA (P=0.003). Multivariate analysis confirmed that BRMS1 promoter methylation has a statistical significant influence both on operable NSCLC patients' DFI time and OS and on advanced NSCLC patients' PFS and OS.

CONCLUSIONS

Methylation of BRMS1 promoter in cfDNA isolated from plasma of NSCLC patients provides important prognostic information and merits to be further evaluated as a circulating tumour biomarker.

Role of miR-191/425 cluster in tumorigenesis and diagnosis of gastric cancer

Gastric cancer (GC) is among the most frequent types of cancer worldwide. Therefore, understanding the biology of GC tumorigenesis is important for appropriate diagnosis and patient surveillance. The miR-191/425 cluster has been reported to be overexpressed in various human cancers, but the tumorigenic role and clinical significance of miR-191/425 overexpression in gastric carcinogenesis is currently undefined. In this study, the expression of miR-191 and miR-425 in GC tissue and serum was assessed, and the relationship between miRNA expression and clinicopathological data was analyzed. We found that miR-191 and miR-425 were both significantly increased in human GC tissues relative to adjacent normal controls. In addition, miR-191 levels correlated with GC tumor stage and metastatic state. Furthermore, the level of serum miR-191 was significantly higher in the GC group than in the control group when using serum miR-16 as an endogenous control. Finally, inhibition of miR-191 or miR-425 in the GC cell lines HGC-27 not only reduced cell proliferation and cell cycle progression but also impaired cell migration and invasion. Taken together, our results revealed the oncogenic roles of miR-191 and miR-425 in gastric carcinogenesis, and indicated the potential use of serum miR-191 as a novel and stable biomarker for GC diagnosis.

Clinical relevance of circulating cell-free microRNAs in cancer

Efficient patient management relies on early diagnosis of disease and monitoring of treatment. In this regard, much effort has been made to find informative, blood-based biomarkers for patients with cancer. Owing to their attributes-which are specifically modulated by the tumour-circulating cell-free microRNAs found in the peripheral blood of patients with cancer may provide insights into the biology of the tumour and the effects of therapeutic interventions. Moreover, the role of microRNAs in the regulation of different cellular processes points to their clinical utility as blood-based biomarkers and future therapeutic targets. MicroRNAs are optimal biomarkers owing to high stability under storage and handling conditions and their presence in blood, urine and other body fluids. In particular, detection of levels of microRNAs in blood plasma and serum has the potential for an earlier cancer diagnosis and to predict prognosis and response to therapy. This Review article considers the latest developments in the use of circulating microRNAs as prognostic and predictive biomarkers and discusses their utility in personalized medicine.

Autoantibody profiling for lung cancer screening longitudinal retrospective analysis of CT screening cohorts

Recommendations for lung cancer screening present a tangible opportunity to integrate predictive blood-based assays with radiographic imaging. This study compares performance of autoantibody markers from prior discovery in sample cohorts from two CT screening trials. One-hundred eighty non-cancer and 6 prevalence and 44 incidence cancer cases detected in the Mayo Lung Screening Trial were tested using a panel of six autoantibody markers to define a normal range and assign cutoff values for class prediction. A cutoff for minimal specificity and best achievable sensitivity were applied to 256 samples drawn annually for three years from 95 participants in the Kentucky Lung Screening Trial. Data revealed a discrepancy in quantile distribution between the two apparently comparable sample sets, which skewed the assay’s dynamic range towards specificity. This cutoff offered 43% specificity (102/237) in the control group and accurately classified 11/19 lung cancer samples (58%), which included 4/5 cancers at time of radiographic detection (80%), and 50% of occult cancers up to five years prior to diagnosis. An apparent ceiling in assay sensitivity is likely to limit the utility of this assay in a conventional screening paradigm. Pre-analytical bias introduced by sample age, handling or storage remains a practical concern during development, validation and implementation of autoantibody assays. This report does not draw conclusions about other logical applications for autoantibody profiling in lung cancer diagnosis and management, nor its potential when combined with other biomarkers that might improve overall predictive accuracy.

Detection of cell carcinogenic transformation by a quadruplex DNA binding fluorescent probe

Cancer can be easily treated when found early. A probe capable of detecting cell transformation may increase the success rate of early diagnosis of cancer. In this report we have tested the ability of a fluorescent, quadruplex DNA binding probe, 3,6-bis(1-methyl-4- vinylpyridinium) carbazole diiodide (BMVC), to detect cell transformation in vitro. BMVC was applied to living cells in several different models of cell transformation, and the fluorescence signals of BMVC were measured. The degrees of cell transformation in these models were characterized by alterations in cellular morphological phenotype and subcellular organization. When BMVC probes were applied, the number of BMVC-positive cells increased in accordance with the degree of transformation. BMVC was capable of significantly detecting formation of foci, increased cellular motility, cell proliferation, cell apoptosis, anchorage-independent growth, and increased invasiveness of transformed cells. These results demonstrate the ability of BMVC probes to detect cell transformation and indicate that BMVC is of promise for use as a probe in early cancer detection.

Solid phase nucleic acid extraction technique in a microfluidic chip using a novel non-chaotropic agent: dimethyl adipimidate

Here, we present a silicon microfluidic system for the purification and extraction of nucleic acids from human body fluid samples utilizing a dimethyl adipimidate (DMA)-based solid-phase extraction method. We propose DMA, which has been used as an amino-reactive cross-linking agent within cells and proteins, as a non-chaotropic reagent for the capture of nucleic acids to overcome the limitations of existing chaotropic and non-chaotropic techniques such as low binding efficiency, PCR inhibition and so on. DMA contains bi-functional imidoesters that form reversible cross-linking structures with DNA therefore providing a high surface-area to volume ratio for capturing DNA without structurally modifying microfluidic channels. In this work, we have first demonstrated highly efficient capture and purification of genomic DNA (T24 cell line) with DMA using a label-free silicon microring resonator sensor device. In addition, we observed the improvement of the DNA amplification efficiency by using the proposed technique for both the genetic (HRAS) and epigenetic (RARβ) analysis of DNA biomarkers. Particularly, we confirmed that the DMA-based solid-phase extraction technique can be applied for the extraction of genomic DNA with higher purity (p < 0.001) using human body fluids (blood and urine) in silicon microfluidic devices compared to other chaotropic methods. Therefore, the proposed technique would be able to harmonize with a micro-total analysis system platform for the analysis of genetic and epigenetic DNA biomarkers related to human diseases in the field of point-of-care (POC) diagnostic applications.

Mass spectrometry in cancer biomarker research: a case for immunodepletion of abundant blood-derived proteins from clinical tissue specimens

The discovery of clinically relevant cancer biomarkers using mass spectrometry (MS)-based proteomics has proven difficult, primarily because of the enormous dynamic range of blood-derived protein concentrations and the fact that the 22 most abundant blood-derived proteins constitute approximately 99% of the total plasma protein mass. Immunodepletion of clinical body fluid specimens (e.g., serum/plasma) for the removal of highly abundant proteins is a reasonable and reproducible solution. Often overlooked, clinical tissue specimens also contain a formidable amount of highly abundant blood-derived proteins present in tissue-embedded networks of blood/lymph capillaries and interstitial fluid. Hence, the dynamic range impediment to biomarker discovery remains a formidable obstacle, regardless of clinical sample type (solid tissue and/or body fluid). Thus, we optimized and applied simultaneous immunodepletion of blood-derived proteins from solid tissue and peripheral blood, using clear cell renal cell carcinoma as a model disease. Integrative analysis of data from this approach and genomic data obtained from the same type of tumor revealed concordant key pathways and protein targets germane to clear cell renal cell carcinoma. This includes the activation of the lipogenic pathway characterized by increased expression of adipophilin (PLIN2) along with 'cadherin switching', a phenomenon indicative of transcriptional reprogramming linked to renal epithelial dedifferentiation. We also applied immunodepletion of abundant blood-derived proteins to various tissue types (e.g., adipose tissue and breast tissue) showing unambiguously that the removal of abundant blood-derived proteins represents a powerful tool for the reproducible profiling of tissue proteomes. Herein, we show that the removal of abundant blood-derived proteins from solid tissue specimens is of equal importance to depletion of body fluids and recommend its routine use in the context of biological discovery and/or cancer biomarker research. Finally, this perspective presents the background, rationale and strategy for using tissue-directed high-resolution/accuracy MS-based shotgun proteomics to detect genuine tumor proteins in the peripheral blood of a patient diagnosed with nonmetastatic cancer, employing concurrent liquid chromatography-MS analysis of immunodepleted clinical tissue and blood specimens.

Personalized therapy for breast cancer: a dream or a reality?

Breast cancer oncology represents one of the disciplines where personalized cancer medicine has been most actively pursued. The class-discovery studies conceptually advanced the field, underlining the molecular heterogeneity governing this common disease. The advent of high-throughput molecular profiling technologies holds great promise for the advance of all aspects of personalized cancer medicine, namely accurate prognostication, prediction of response to common systemic therapies and individualized monitoring of the disease. Moreover, an ever-expanding arsenal of targeted therapeutic compounds under clinical development, coupled with emerging powerful tools for comprehensive molecular and functional characterization, pose significant promise for improved clinical outcomes for breast cancer patients. Interrogation of the germline genetic variation offers further promise towards tailoring of breast cancer management. Well-conducted prospective validation studies are needed if breast cancer personalized therapy is to transform from a dream into a reality.

Direct detection of alternative open reading frames translation products in human significantly expands the proteome

A fully mature mRNA is usually associated to a reference open reading frame encoding a single protein. Yet, mature mRNAs contain unconventional alternative open reading frames (AltORFs) located in untranslated regions (UTRs) or overlapping the reference ORFs (RefORFs) in non-canonical +2 and +3 reading frames. Although recent ribosome profiling and footprinting approaches have suggested the significant use of unconventional translation initiation sites in mammals, direct evidence of large-scale alternative protein expression at the proteome level is still lacking. To determine the contribution of alternative proteins to the human proteome, we generated a database of predicted human AltORFs revealing a new proteome mainly composed of small proteins with a median length of 57 amino acids, compared to 344 amino acids for the reference proteome. We experimentally detected a total of 1,259 alternative proteins by mass spectrometry analyses of human cell lines, tissues and fluids. In plasma and serum, alternative proteins represent up to 55% of the proteome and may be a potential unsuspected new source for biomarkers. We observed constitutive co-expression of RefORFs and AltORFs from endogenous genes and from transfected cDNAs, including tumor suppressor p53, and provide evidence that out-of-frame clones representing AltORFs are mistakenly rejected as false positive in cDNAs screening assays. Functional importance of alternative proteins is strongly supported by significant evolutionary conservation in vertebrates, invertebrates, and yeast. Our results imply that coding of multiple proteins in a single gene by the use of AltORFs may be a common feature in eukaryotes, and confirm that translation of unconventional ORFs generates an as yet unexplored proteome.

Circulating miRNA biomarkers for Alzheimer's disease

A minimally invasive diagnostic assay for early detection of Alzheimer's disease (AD) is required to select optimal patient groups in clinical trials, monitor disease progression and response to treatment, and to better plan patient clinical care. Blood is an attractive source for biomarkers due to minimal discomfort to the patient, encouraging greater compliance in clinical trials and frequent testing. MiRNAs belong to the class of non-coding regulatory RNA molecules of ∼22 nt length and are now recognized to regulate ∼60% of all known genes through post-transcriptional gene silencing (RNAi). They have potential as useful biomarkers for clinical use because of their stability and ease of detection in many tissues, especially blood. Circulating profiles of miRNAs have been shown to discriminate different tumor types, indicate staging and progression of the disease and to be useful as prognostic markers. Recently their role in neurodegenerative diseases, both as diagnostic biomarkers as well as explaining basic disease etiology has come into focus. Here we report the discovery and validation of a unique circulating 7-miRNA signature (hsa-let-7d-5p, hsa-let-7g-5p, hsa-miR-15b-5p, hsa-miR-142-3p, hsa-miR-191-5p, hsa-miR-301a-3p and hsa-miR-545-3p) in plasma, which could distinguish AD patients from normal controls (NC) with >95% accuracy (AUC of 0.953). There was a >2 fold difference for all signature miRNAs between the AD and NC samples, with p-values<0.05. Pathway analysis, taking into account enriched target mRNAs for these signature miRNAs was also carried out, suggesting that the disturbance of multiple enzymatic pathways including lipid metabolism could play a role in AD etiology.

Ultrarapid generation of femtoliter microfluidic droplets for single-molecule-counting immunoassays

We report a microfluidic droplet-based approach enabling the measurement of chemical reactions of individual enzyme molecules and its application to a single-molecule-counting immunoassay. A microfluidic device is used to generate and manipulate <10 fL droplets at rates of up to 1.3 × 10(6) per second, about 2 orders of magnitude faster than has previously been reported. The femtodroplets produced with this device can be used to encapsulate single biomolecular complexes tagged with a reporter enzyme; their small volume enables the fluorescent product of a single enzyme molecule to be detected within 10 min of on-chip incubation. Our prototype system is validated by detection of a biomarker for prostate cancer in buffer, down to a concentration of 46 fM. This work demonstrates a highly flexible and sensitive diagnostic platform that exploits extremely high-speed generation of monodisperse femtoliter droplets for the counting of individual analyte molecules.

Gold nanoparticle-based activatable probe for sensing ultralow levels of prostate-specific antigen

It is still in high demand to develop extremely sensitive and accurate clinical tools for biomarkers of interest for early diagnosis and monitoring of diseases. In this report, we present a highly sensitive and compatible gold nanoparticle (AuNP)-based fluorescence-activatable probe for sensing ultralow levels of prostate-specific antigen (PSA) in patient serum samples. The limit of detection of the newly developed probe for PSA was pushed down to 0.032 pg/mL, which is more than 2 orders of magnitude lower than that of the conventional fluorescence probe. The ultrahigh sensitivity of this probe was attributed to the high loading efficiency of the dyes on AuNP surfaces and high fluorescence quenching-unquenching abilities of the dye-AuNP pairs. The efficiency and robustness of this probe were investigated in patient serum samples, demonstrating the great potential of this probe in real-world applications.

Cancer diagnosis and prognosis decoded by blood-based circulating microRNA signatures

In the recent years, circulating microRNAs (miRNAs) have garnered a lot of attention and interest in the field of disease biomarkers. With characteristics such as high stability, low cost, possibility of repeated sampling and minimal invasiveness, circulating miRNAs are ideal for development into diagnostic tests. There have been many studies reported on the potential of circulating miRNAs as early detection, prognostic, and predictive biomarkers in cancer. Here, we have reviewed the application of plasma and serum miRNAs as biomarkers for cancer focusing on epithelial carcinomas [prostate, breast, lung, colorectal, and gastric cancer (GC)] and hematological malignancies (leukemia and lymphoma). We have also addressed the common challenges that need to be overcome to achieve a successful bench to bedside transition.

Serum proteomic profiling for the early diagnosis of colorectal cancer

No ideal serum biomarker currently exists for the early diagnosis of colorectal cancer (CRC). Magnetic bead-based fractionation coupled with MALDI-TOF MS was used to screen serum samples from CRC patients, healthy controls, and other cancer patients. A diagnostic model with five proteomic features (m/z 1778.97, 1866.16, 1934.65, 2022.46, and 4588.53) was generated using Fisher algorithm with best performance. The Fisher-based model could discriminate CRC patients from the controls with 100% (46/46) sensitivity and 100% (35/35) specificity in the training set, 95.6% (43/45) sensitivity and 83.3% (35/42) specificity in the test set. We further validated the model with 94.4% (254/269) sensitivity and 75.5% (83/110) specificity in the external independent group. In other cancers group, the Fisher-based model classified 25 of 46 samples (54.3%) as positive and the other 21 as negative. With FT-ICR-MS, the proteomic features of m/z 1778.97, 1866.16, 1934.65, and 2022.46, of which intensities decreased significantly in CRC, were identified as fragments of complement C3f. Therefore, the Fisher-based model containing five proteomic features was able to effectively differentiate CRC patients from healthy controls and other cancers with a high sensitivity and specificity, and may be CRC-specific. Serum complement C3f, which was significantly decreased in CRC group, may be relevant to the incidence of CRC.

Multiplexed electrochemical protein detection and translation to personalized cancer diagnostics

Measuring diagnostic panels of multiple proteins promises a new, personalized approach to early detection and therapy of diseases like cancer. Levels of biomarker proteins in patient serum can provide a continually updated record of disease status. Research in electrochemical detection of proteins has produced exquisitely sensitive approaches. Most utilize ELISA-like sandwich immunoassays incorporating various aspects of nanotechnology. Several of these ultrasensitive methodologies have been extended to microfluidic multiplexed protein detection, but engineered solutions are needed to measure more proteins in a single device from a small patient sample such as a drop of blood or tissue lysate. To achieve clinical or point-of-care (POC) use, simplicity and low cost are essential. In multiplexed microfluidic immunoassays, required reagent additions and washing steps pose a significant problem calling for creative engineering. A grand challenge is to develop a general cancer screening device to accurately measure 50-100 proteins in a simple, cost-effective fashion. This will require creative solutions to simplified reagent addition and multiplexing.

Microbubble-enhanced ultrasound liberation of mRNA biomarkers in vitro

Blood-borne biomarkers have great potential in diagnostic medicine, but low concentrations, inability to determine their source and lack of a patient baseline have limited their success in both research and clinical medicine. D'Souza et al. previously demonstrated that ultrasound-induced sonoporation can be used to liberate protein biomarkers from a colorectal cancer into the surrounding serum, overcoming many of the limitations of blood-borne biomarkers. In this study we build on D'Souza's work, extending this technique to nucleic acids, specifically mammaglobin mRNA-a potential diagnostic biomarker for breast cancer metastases. Furthermore, we propose to use ultrasound contrast agents, lipid-stabilized microbubbles, to enhance the effects of sonoporation and further amplify the biomarker levels. We demonstrate that microbubbles can enhance mammaglobin mRNA levels by two to three orders of magnitude greater than background levels and one to two orders of magnitude greater than ultrasound alone.

Gene expression analysis of peripheral blood cells reveals Toll-like receptor pathway deregulation in colorectal cancer

Colorectal cancer is the leading cause of cancer-related deaths worldwide. The disease is curable when detected at an early stage. However, the compliance rate with current screening recommendations remains poor. An accurate, minimally invasive blood test that has the potential for greater patient compliance would be a welcome addition to the current methods. Recent data have shown that gene expression profile of peripheral blood cells can reflect disease states and thus have diagnostic value. In this study, genome-wide gene expression profiling of peripheral blood cells from 20 healthy controls and 20 colorectal cancer patients were performed using PAXgene™ technology and Affymetrix GeneChip® microarrays. We identified a list of 1,469 genes that were differentially expressed between the healthy controls and cancer patients. Gene annotation and functional enrichment analysis revealed that those genes are mainly related to immune functions. Particularly, a set of genes belonging to the Toll-Like Receptor pathways were up-regulated in the colorectal cancer patients. These findings provide a new understanding of blood gene expression profile in colorectal cancer. Our result may serve as the basis for further development of blood biomarkers for the diagnosis and treatment of colorectal cancer.

Proteomics reveals plasma profiles for monitoring the toxicity caused by chromium compounds

BACKGROUND

Today, various heavy metals are widespread in the ecosystem and have become important environmental contaminants. Exposure to these hazardous metals such as chromium usually results in cytotoxicity and large-scale protein changes which reflect pathologic states.

METHODS

We used a comprehensive proteomic tool to survey changes in plasma proteins elicited by two chromium species (Cr(6+) and Cr(3+)). RT-PCR was applied to evaluate levels of cytokines associated with adverse responses. Lectin blotting was used to investigate the contents of fucosylated proteins.

RESULTS

Protein profiles revealed statistically significant changes in the intensity of 12 proteins. The network analysis implied that Cr(6+) application strongly induced the IL-6-stimulated inflammatory pathway. mRNA levels of specific cytokines were also correlated with inflammatory events. Increased IL-6 modulation of the fucosylation of haptoglobin was also identified in Cr(6+)-treated samples.

CONCLUSIONS

These results suggest that Cr(6+) may induce IL-6-mediated inflammatory responses which result in hepatic injury. This paper highlights the applications of functional proteomics of plasma profiles and fucosylated glycoproteins as a predictive tool to monitor human health in contact with chromium.

Detection of TFPI2 methylation in the serum of hepatocellular carcinoma patients

BACKGROUND

DNA methylation plays a key role in hepatocellular carcinogenesis and progression. Analysis of aberrant methylation in serum DNA might provide a strategy for noninvasive detection of hepatocellular carcinoma (HCC).

METHODS

To explore the feasibility of this approach, we compared TFPI2 methylation status in serum samples of HCC, chronic hepatitis B (CHB) patients and normal control groups using methylation-specific polymerase chain reaction.

RESULTS

Our results showed that the percentage of serum TFPI2 promoter methylation was significantly higher in the HCC group (46.5 %, 20/43) compared with the CHB group (16.7 %, 4/24; p = 0.015) and the normal control group (19.2 %, 5/26; p = 0.022), respectively, indicating that TFPI2 methylation frequently existed in the serum of HCC patients. In our study, the detection rate of HCC using serum TFPI2 methylation was 46.5 % (20/43), which was quite close to the reported detection rate of α-fetoprotein (54 %). In cases where we combined both markers, the detection rate was 61.0 %, suggesting that serum TFPI2 methylation could be used as a potential marker for noninvasive detection of HCC. Then, we evaluated the correlation between the serum TFPI2 methylation status of HCC patients and their clinicopathological parameters. Patients with advanced TNM stage (III-IV) showed a significantly elevated serum methylation percentage of TFPI2 in comparison with those with early TNM stage (I-II) (p = 0.025). Moreover, TFPI2 methylation was observed more frequently according to the progression of TNM stage.

CONCLUSIONS

Our present study suggested that TFPI2 methylation in serum tended to be detected more easily in patients with advanced HCC and might be used as a predictor of HCC progression.

A negative selection system PowerMag for effective leukocyte depletion and enhanced detection of EpCAM positive and negative circulating tumor cells

BACKGROUND

Circulating tumor cells (CTCs) can be enriched from peripheral blood by leukocyte depletion. In this study, a PowerMag system was designed to enhance leukocyte depletion and CTC detection.

METHODS

The efficiency of PowerMag in leukocyte depletion and recovery of CTCs was evaluated. The cell populations in leukocyte-depleted cell filtrate were characterized by immunofluorescence staining using anti-EpCAM and anti-CD45 antibodies. The suitability of PowerMag in monitoring cancer patient CTCs was assessed by analyzing blood samples collected at baseline and 2 weeks after baseline from the patients with colorectal cancer (CRC, n=24) and head and neck squamous cell carcinoma (HNSCC, n=28).

RESULTS

Only few contaminated CD45(+)-leukocytes were retained in the leukocyte-depleted cell filtrate. The enriched CTCs were viable with a recovery rate of 46-62%. Immunofluorescence staining of the nucleated cells enriched by PowerMag revealed 2 major cell populations EpCAM(+)CD45(-) and EpCAM(-)CD45(-). The number for both cell types was significantly increased in cancer patients when compared to healthy control. After chemotherapy, the number of EpCAM(+)CD45(-) and EpCAM(-)CD45(-) cells was decreased more prominently for CRC and HNSCC patients, respectively.

CONCLUSIONS

PowerMag holds great promise as a platform for leukocyte depletion and CTC detection in a clinical setting.

Identification of potential glycan cancer markers with sialic acid attached to sialic acid and up-regulated fucosylated galactose structures in epidermal growth factor receptor secreted from A431 cell line

We have used powerful HPLC-mass spectrometric approaches to characterize the secreted form of epidermal growth factor receptor (sEGFR). We demonstrated that the amino acid sequence lacked the cytoplasmic domain and was consistent with the primary sequence reported for EGFR purified from a human plasma pool. One of the sEGFR forms, attributed to the alternative RNA splicing, was also confirmed by transcriptional analysis (RNA sequencing). Two unusual types of glycan structures were observed in sEGFR as compared with membrane-bound EGFR from the A431 cell line. The unusual glycan structures were di-sialylated glycans (sialic acid attached to sialic acid) at Asn-151 and N-acetylhexosamine attached to a branched fucosylated galactose with N-acetylglucosamine moieties (HexNAc-(Fuc)Gal-GlcNAc) at Asn-420. These unusual glycans at specific sites were either present at a much lower level or were not observable in membrane-bound EGFR present in the A431 cell lysate. The observation of these di-sialylated glycan structures was consistent with the observed expression of the corresponding α-N-acetylneuraminide α-2,8-sialyltransferase 2 (ST8SiA2) and α-N-acetylneuraminide α-2,8-sialyltransferase 4 (ST8SiA4), by quantitative real time RT-PCR. The connectivity present at the branched fucosylated galactose was also confirmed by methylation of the glycans followed by analysis with sequential fragmentation in mass spectrometry. We hypothesize that the presence of such glycan structures could promote secretion via anionic or steric repulsion mechanisms and thus facilitate the observation of these glycan forms in the secreted fractions. We plan to use this model system to facilitate the search for novel glycan structures present at specific sites in sEGFR as well as other secreted oncoproteins such as Erbb2 as markers of disease progression in blood samples from cancer patients.

Fourier-transform infrared spectroscopy coupled with a classification machine for the analysis of blood plasma or serum: a novel diagnostic approach for ovarian cancer

Currently available screening tests do not deliver the required sensitivity and specificity for accurate diagnosis of ovarian or endometrial cancer. Infrared (IR) spectroscopy of blood plasma or serum is a rapid, versatile, and relatively non-invasive approach which could characterize biomolecular alterations due to cancer and has potential to be utilized as a screening or diagnostic tool. In the past, no such approach has been investigated for its applicability in screening and/or diagnosis of gynaecological cancers. We set out to determine whether attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy coupled with a proposed classification machine could be applied to IR spectra obtained from plasma and serum for accurate class prediction (cancer vs. normal). Plasma and serum samples were obtained from ovarian cancer cases (n = 30), endometrial cancer cases (n = 30) and non-cancer controls (n = 30), and subjected to ATR-FTIR spectroscopy. Four derived datasets were processed to estimate the real-world diagnosis of ovarian and endometrial cancer. Classification results for ovarian cancer were remarkable (up to 96.7%), whereas endometrial cancer was classified with a relatively high accuracy (up to 81.7%). The results from different combinations of feature extraction and classification methods, and also classifier ensembles, were compared. No single classification system performed best for all different datasets. This demonstrates the need for a framework that can accommodate a diverse set of analytical methods in order to be adaptable to different datasets. This pilot study suggests that ATR-FTIR spectroscopy of blood is a robust tool for accurate diagnosis, and carries the potential to be utilized as a screening test for ovarian cancer in primary care settings. The proposed classification machine is a powerful tool which could be applied to classify the vibrational spectroscopy data of different biological systems (e.g., tissue, urine, saliva), with their potential application in clinical practice.

Novel methodologies in metabolic profiling with a focus on molecular diagnostic applications

The metabolome contains all the biological end points of genomic, transcriptomic and proteomic perturbations, also including the influence of gut microbiota and the environment, giving a direct picture of an organism's ongoing metabolic state. Metabolomics thus has the potential to be an effective tool for early diagnosis of disease, and also to be a predictor of treatment response and survival. In recent years, the development of instrumental systems has enabled more comprehensive coverage of the metabolome. Advances in mass spectrometry and chromatography have particularly improved both the efficiency of nontargeted metabolic profiling as well as the sensitivity and reliability of targeted analyses. Mass spectrometric techniques are also increasingly becoming accepted as a routine diagnostic tool in clinical laboratories. This review summarizes the most recent advances and current challenges in metabolomics, with a focus on mass spectrometric methods utilized in biomarker research, highlighted with selected examples.

Highly efficient binding of paramagnetic beads bioconjugated with 100,000 or more antibodies to protein-coated surfaces

We report here the first kinetic characterization of 1 μm diameter superparamagnetic particles (MP) decorated with over 100,000 antibodies binding to protein antigens attached to flat surfaces. Surface plasmon resonance (SPR) was used to show that these antibody-derivatized MPs (MP-Ab(2)) exhibit irreversible binding with 100-fold increased association rates compared to free antibodies. The estimated upper limit for the dissociation constant of MP-Ab(2) from the SPR sensor surface is 5 fM, compared to 3-8 nM for the free antibodies. These results are explained by up to 2000 interactions of MP-Ab(2) with protein-decorated surfaces. Findings are consistent with highly efficient capture of protein antigens in solution by the MP-Ab(2) and explain in part the utility of these beads for ultrasensitive protein detection into the fM and aM range. Aggregation of these particles on the SPR chip, probably due to residual magnetic microdomains in the particles, also contributes to ultrasensitive detection and may also help drive the irreversible binding.

Sensitive and direct detection of circulating tumor cells by multimarker µ-nuclear magnetic resonance

Identifying circulating tumor cells (CTCs) with greater sensitivity could facilitate early detection of cancer and rapid assessment of treatment response. Most current technologies use EpCAM expression as a CTC identifier. However, given that a significant fraction of cancer patients have low or even absent EpCAM levels, there is a need for better detection methods. Here, we hypothesize that a multimarker strategy combined with direct sensing of CTC in whole blood would increase the detection of CTC in patients. Accordingly, molecular profiling of biopsies from a patient cohort revealed a four-marker set (EpCAM, HER-2, EGFR, and MUC-1) capable of effectively differentiating cancer cells from normal host cells. Using a point-of-care micro-nuclear magnetic resonance (µNMR) system, we consequently show that this multimarker combination readily detects individual CTC directly in whole blood without the need for primary purification. We also confirm these results in a comparative trial of patients with ovarian cancer. This platform could potentially benefit a broad range of applications in clinical oncology.

Serum sarcosine increases the accuracy of prostate cancer detection in patients with total serum PSA less than 4.0 ng/ml

BACKGROUND

Sarcosine is reported to be a differential metabolite that is greatly increased during prostate cancer (PCa) progression. In this study, we assessed the role of serum sarcosine as a biomarker for PCa, as well as any association between sarcosine levels and clinical-pathological parameters.

METHODS

Sarcosine was measured by fluorometric assay in serum samples from 290 PCa patients and 312 patients with no evidence of malignancy (NEM), confirmed by 8-12 core prostate biopsies. Nonparametric statistical tests and receiver operating characteristics (ROC) analyses were performed to assess the diagnostic performance of sarcosine in different (prostate-specific antigen) PSA ranges.

RESULTS

ROC analyses in subjects with PSA < 4 ng/ml showed a higher predictive value of sarcosine (AUC = 0.668) versus total PSA (AUC = 0.535) (P = 0.03), whereas for the other two PSA ranges (4-10 ng/ml and >10 ng/ml), percent ratio of free to total PSA (%fPSA) showed a predictive superiority over sarcosine. Moreover, in patients with a PSA < 4 ng/ml, the percentage of low/intermediate-grade cancers was positively associated with sarcosine levels (P = 0.005). The specificities for serum sarcosine, %fPSA, PSA, and the logistic regression model at 95% sensitivity were 24.4, 3.41, 2.22, and 28.4%, respectively.

CONCLUSIONS

We provide evidence that serum sarcosine has a higher predictive value than tPSA and %fPSA in patients with PSA < 4 ng/ml. Moreover, sarcosine levels were significantly different in low grade versus high grade cancers in this subset of patients, suggesting that this marker may be a further tool not only for diagnosing PCa in normal PSA and abnormal DRE/TRUS patients but also for selecting candidates for non-aggressive therapies and active surveillance.

Quantification of the N-glycosylated secretome by super-SILAC during breast cancer progression and in human blood samples

Cells secrete a large number of proteins to communicate with their surroundings. Furthermore, plasma membrane proteins and intracellular proteins can be released into the extracellular space by regulated or non-regulated processes. Here, we profiled the supernatant of 11 cell lines that are representative of different stages of breast cancer development by specifically capturing N-glycosylated peptides using the N-glyco FASP technology. For accurate quantification we developed a super-SILAC mix from several labeled breast cancer cell lines and used it as an internal standard for all samples. In total, 1398 unique N-glycosylation sites were identified and quantified. Enriching for N-glycosylated peptides focused the analysis on classically secreted and membrane proteins. N-glycosylated secretome profiles correctly clustered the different cell lines to their respective cancer stage, suggesting that biologically relevant differences were detected. Five different profiles of glycoprotein dynamics during cancer development were detected, and they contained several proteins with known roles in breast cancer. We then used the super-SILAC mix in plasma, which led to the quantification of a large number of the previously identified N-glycopeptides in this important body fluid. The combination of quantifying the secretome of cancer cell lines and of human plasma with a super-SILAC approach appears to be a promising new approach for finding markers of disease.