Plasma biomarker discovery and validation for colorectal cancer by quantitative shotgun mass spectrometry and protein microarray

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Comprehensive serum glycopeptide spectra analysis to identify early-stage epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is widely recognized as the most lethal gynecological malignancy; however, its early-stage detection remains a considerable clinical challenge. To address this, we have introduced a new method, named Comprehensive Serum Glycopeptide Spectral Analysis (CSGSA), which detects early-stage cancer by combining glycan alterations in serum glycoproteins with tumor markers. We detected 1712 glycopeptides using liquid chromatography-mass spectrometry from the sera obtained from 564 patients with EOC and 1149 controls across 13 institutions. Furthermore, we used a convolutional neural network to analyze the expression patterns of the glycopeptides and tumor markers. Using this approach, we successfully differentiated early-stage EOC (Stage I) from non-EOC, with an area under the curve (AUC) of 0.924 in receiver operating characteristic (ROC) analysis. This method markedly outperforms conventional tumor markers, including cancer antigen 125 (CA125, 0.842) and human epididymis protein 4 (HE4, 0.717). Notably, our method exhibited remarkable efficacy in differentiating early-stage ovarian clear cell carcinoma from endometrioma, achieving a ROC-AUC of 0.808, outperforming CA125 (0.538) and HE4 (0.557). Our study presents a promising breakthrough in the early detection of EOC through the innovative CSGSA method. The integration of glycan alterations with cancer-related tumor markers has demonstrated exceptional diagnostic potential.

Development of EndoScreen Chip, a Microfluidic Pre-Endoscopy Triage Test for Esophageal Adenocarcinoma

The current endoscopy and biopsy diagnosis of esophageal adenocarcinoma (EAC) and its premalignant condition Barrett's esophagus (BE) is not cost-effective. To enable EAC screening and patient triaging for endoscopy, we developed a microfluidic lectin immunoassay, the EndoScreen Chip, which allows sensitive multiplex serum biomarker measurements. Here, we report the proof-of-concept deployment for the EAC biomarker Jacalin lectin binding complement C9 (JAC-C9), which we previously discovered and validated by mass spectrometry. A monoclonal C9 antibody (m26 3C9) was generated and validated in microplate ELISA, and then deployed for JAC-C9 measurement on EndoScreen Chip. Cohort evaluation (n = 46) confirmed the expected elevation of serum JAC-C9 in EAC, along with elevated total serum C9 level. Next, we asked if the small panel of serum biomarkers improves detection of EAC in this cohort when used in conjunction with patient risk factors (age, body mass index and heartburn history). Using logistic regression modeling, we found that serum C9 and JAC-C9 significantly improved EAC prediction from AUROC of 0.838 to 0.931, with JAC-C9 strongly predictive of EAC (vs. BE OR = 4.6, 95% CI: 1.6-15.6, p = 0.014; vs. Healthy OR = 4.1, 95% CI: 1.2-13.7, p = 0.024). This proof-of-concept study confirms the microfluidic EndoScreen Chip technology and supports the potential utility of blood biomarkers in improving triaging for diagnostic endoscopy. Future work will expand the number of markers on EndoScreen Chip from our list of validated EAC biomarkers.

Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Lower Gastrointestinal Cancers: A Systematic Review and Meta-Analysis

INTRODUCTION

Lower gastrointestinal (GI) cancers are a major cause of cancer deaths worldwide. Prognosis improves with earlier diagnosis, and non-invasive biomarkers have the potential to aid with early detection. Substantial investment has been made into the development of biomarkers; however, studies are often carried out in specialist settings and few have been evaluated for low-prevalence populations.

METHODS

We aimed to identify novel biomarkers for the detection of lower GI cancers that have the potential to be evaluated for use in primary care. MEDLINE, Embase, Emcare and Web of Science were systematically searched for studies published in English from January 2000 to October 2019. Reference lists of included studies were also assessed. Studies had to report on measures of diagnostic performance for biomarkers (single or in panels) used to detect colorectal or anal cancers. We included all designs and excluded studies with fewer than 50 cases/controls. Data were extracted from published studies on types of biomarkers, populations and outcomes. Narrative synthesis was used, and measures of specificity and sensitivity were meta-analysed where possible.

RESULTS

We identified 142 studies reporting on biomarkers for lower GI cancers, for 24,844 cases and 45,374 controls. A total of 378 unique biomarkers were identified. Heterogeneity of study design, population type and sample source precluded meta-analysis for all markers except methylated septin 9 (mSEPT9) and pyruvate kinase type tumour M2 (TuM2-PK). The estimated sensitivity and specificity of mSEPT9 was 80.6% (95% CI 76.6-84.0%) and 88.0% (95% CI 79.1-93.4%) respectively; TuM2-PK had an estimated sensitivity of 81.6% (95% CI 75.2-86.6%) and specificity of 80.1% (95% CI 76.7-83.0%).

CONCLUSION

Two novel biomarkers (mSEPT9 and TuM2-PK) were identified from the literature with potential for use in lower-prevalence populations. Further research is needed to validate these biomarkers in primary care for screening and assessment of symptomatic patients.

A Meta-Analysis of Proteomic Blood Markers of Colorectal Cancer

BACKGROUND

Early diagnosis will significantly improve the survival rate of colorectal cancer (CRC); however, the existing methods for CRC screening were either invasive or inefficient. There is an emergency need for novel markers in CRC's early diagnosis. Serum proteomics has gained great potential in discovering novel markers, providing markers that reflect the early stage of cancer and prognosis prediction of CRC. In this paper, the results of proteomics of CRC studies were summarized through a meta-analysis in order to obtain the diagnostic efficiency of novel markers.

METHODS

A systematic search on bibliographic databases was performed to collect the studies that explore blood-based markers for CRC applying proteomics. The detection and validation methods, as well as the specificity and sensitivity of the biomarkers in these studies, were evaluated. Newcastle- Ottawa Scale (NOS) case-control studies version was used for quality assessment of included studies.

RESULTS

Thirty-four studies were selected from 751 studies, in which markers detected by proteomics were summarized. In total, fifty-nine proteins were classified according to their biological function. The sensitivity, specificity, or AUC varied among these markers. Among them, Mammalian STE20-like protein kinase 1/ Serine threonine kinase 4 (MST1/STK4), S100 calcium-binding protein A9 (S100A9), and Tissue inhibitor of metalloproteinases 1 (TIMP1) were suitable for effect sizes merging, and their diagnostic efficiencies were recalculated after merging. MST1/STK4 obtained a sensitivity of 68% and a specificity of 78%. S100A9 achieved a sensitivity of 72%, a specificity of 83%, and an AUC of 0.88. TIMP1 obtained a sensitivity of 42%, a specificity of 88%, and an AUC of 0.71.

CONCLUSION

MST1/STK4, S100A9, and TIMP1 showed excellent performance for CRC detection. Several other markers also presented optimized diagnostic efficacy for CRC early detection, but further verification is still needed before they are suitable for clinical use. The discovering of more efficient markers will benefit CRC treatment.

Integrative analysis of multi-platform reverse-phase protein array data for the pharmacodynamic assessment of response to targeted therapies

Reverse-phase protein array (RPPA) technology uses panels of high-specificity antibodies to measure proteins and protein post-translational modifications in cells and tissues. The approach offers sensitive and precise quantification of large numbers of samples and has thus found applications in the analysis of clinical and pre-clinical samples. For effective integration into drug development and clinical practice, robust assays with consistent results are essential. Leveraging a collaborative RPPA model, we set out to assess the variability between three different RPPA platforms using distinct instrument set-ups and workflows. Employing multiple RPPA-based approaches operated across distinct laboratories, we characterised a range of human breast cancer cells and their protein-level responses to two clinically relevant cancer drugs. We integrated multi-platform RPPA data and used unsupervised learning to identify protein expression and phosphorylation signatures that were not dependent on RPPA platform and analysis workflow. Our findings indicate that proteomic analyses of cancer cell lines using different RPPA platforms can identify concordant profiles of response to pharmacological inhibition, including when using different antibodies to measure the same target antigens. These results highlight the robustness and the reproducibility of RPPA technology and its capacity to identify protein markers of disease or response to therapy.

[The influence of apolipoprotein A1 on the prognosis of multiple myeloma]

目的

探讨多发性骨髓瘤患者血清载脂蛋白A1水平的变化及其临床意义。

方法

统计412例多发性骨髓瘤患者的临床资料，以93名健康体检者为正常对照，使用SPSS 22.0进行数据分析。相关分析采用线性相关或Spearman秩相关系数。分析数据采用t检验、Mann-Whitney U检验或单因素方差分析。采用ROC曲线计算分界值，并与Kaplan-Meier生存分析进行比较。

结果

骨髓瘤组载脂蛋白A1水平低于正常对照组（0.89 g/L对1.24 g/L，P<0.05）。载脂蛋白A1水平随疾病的不同阶段动态变化，当疾病缓解时载脂蛋白A1水平可升高，疾病进展时载脂蛋白A1水平降低。多因素分析表明载脂蛋白A1减少是多发性骨髓瘤的独立危险因素。高载脂蛋白A1组与低载脂蛋白A1组的Kaplan-Meier生存分析显示高载脂蛋白A1组有更高的生存率和更长的无进展生存期。

结论

载脂蛋白A1是多发性骨髓瘤有效的肿瘤负荷标志物和预后因素。

Plasma protein expression differs between colorectal cancer patients depending on primary tumor location

Colorectal cancer (CRC) includes tumors in the right colon, left colon, and rectum, although they differ significantly from each other in aspects such as prognosis and treatment. Few previous mass spectrometry-based studies have analyzed differences in protein expression depending on the tumor location. In this study, we have used mass spectrometry-based proteomics to analyze plasma samples from 83 CRC patients to study if differences in plasma protein expression can be seen depending on primary tumor location (right colon, left colon, or rectum). Differences were studied between the groups both regardless of and according to tumor stage (II or III). Large differences in plasma protein expression were seen, and we found that plasma samples from patients with rectal cancer separated from samples from patients with colon cancer when analyzed by principal component analysis and hierarchical clustering. Samples from patients with cancer in the right and left colon also tended to separate from each other. Pathway analysis discovered canonical pathways involved in lipid metabolism and inflammation to be enriched. This study will help to further define CRC as distinct entities depending on tumor location, as shown by the widespread differences in plasma protein profile and dysregulated pathways.

Identification of several plasma proteins whose levels in colorectal cancer patients differ depending on outcome

Colorectal cancer (CRC) stands for 10% of the worldwide cancer burden and has recently become the second most common cause of cancer death. The 5-year survival rate depends mainly on stage at diagnosis. Mass spectrometric proteomic analysis is widely used to study the plasma proteome, which is complex and contains multitudes of proteins. In this study, we have used Ultra Performance Liquid Chromatography-Ultra Definition Mass Spectrometry (UPLC-UDMSE)-based proteomics to analyze plasma samples from 76 CRC patients. We identified several plasma proteins, such as CP, TVP23C, FETUB, and IGFBP3, of which altered levels led to significant differences in survival, as seen by Cox regression and Kaplan-Meier analysis. Additionally, during Cox regression analysis, samples were adjusted for age and/or tumor stage, enabling stringent analysis. These proteins, although in need of further validation, could be of use during patient follow-up, as their levels can non-invasively be measured from blood samples, and could be of use in predicting patient outcome. Several of these proteins additionally have roles in metabolism and inflammation, two processes central to the development and progression of cancer, further indicating their importance in cancer.

Role of C5b-9 and RGC-32 in Cancer

The complement system represents an effective arsenal of innate immunity as well as an interface between innate and adaptive immunity. Activation of the complement system culminates with the assembly of the C5b-9 terminal complement complex on cell membranes, inducing target cell lysis. Translation of this sequence of events into a malignant setting has traditionally afforded C5b-9 a strict antitumoral role, in synergy with antibody-dependent tumor cytolysis. However, in recent decades, a plethora of evidence has revised this view, highlighting the tumor-promoting properties of C5b-9. Sublytic C5b-9 induces cell cycle progression by activating signal transduction pathways (e.g., Gi protein/ phosphatidylinositol 3-kinase (PI3K)/Akt kinase and Ras/Raf1/ERK1) and modulating the activation of cancer-related transcription factors, while shielding malignant cells from apoptosis. C5b-9 also induces Response Gene to Complement (RGC)-32, a gene that contributes to cell cycle regulation by activating the Akt and CDC2 kinases. RGC-32 is expressed by tumor cells and plays a dual role in cancer, functioning as either a tumor promoter by endorsing malignancy initiation, progression, invasion, metastasis, and angiogenesis, or as a tumor suppressor. In this review, we present recent data describing the versatile, multifaceted roles of C5b-9 and its effector, RGC-32, in cancer.

High-Density Lipoprotein Components and Functionality in Cancer: State-of-the-Art

Cancer is the second leading cause of death in western countries, and thus represents a major global public health issue. Whilst it is well-recognized that diet, obesity, and smoking are risk factors for cancer, the role of low levels of high-density lipoprotein cholesterol (HDL-C) in cancer is less well appreciated. Conflicting evidence suggests that serum HDL-C levels may be either positively or negatively associated with cancer incidence and mortality. Such disparate associations are supported in part by the multitude of high-density lipoprotein (HDL) functions that can all have an impact on cancer cell biology. The aim of this review is to provide a comprehensive overview of the crosstalk between HDLs and cancer, focusing on the molecular mechanisms underlying this association.

Reproducibility and Crossplatform Validation of Reverse-Phase Protein Array Data

Reverse-phase protein array (RPPA) technology is a high-throughput antibody- and microarray-based approach for the rapid profiling of levels of proteins and protein posttranslational modifications in biological specimens. The technology consumes small amounts of samples, can sensitively detect low-abundance proteins and posttranslational modifications, enables measurements of multiple signaling pathways in parallel, has the capacity to analyze large sample numbers, and offers robust interexperimental reproducibility. These features of RPPA experiments have motivated and enabled the use of RPPA technology in various biomedical, translational, and clinical applications, including the delineation of molecular mechanisms of disease, profiling of druggable signaling pathway activation, and search for new prognostic markers. Owing to the complexity of many of these applications, such as developing multiplex protein assays for diagnostic laboratories or integrating posttranslational modification-level data using large-scale proteogenomic approaches, robust and well-validated data are essential. There are many distinct components of an RPPA workflow, and numerous possible technical setups and analysis parameter options exist. The differences between RPPA platform setups around the world offer opportunities to assess and minimize interplatform variation. Crossplatform validation may also aid in the evaluation of robust, platform-independent protein markers of disease and response to therapy.

Hypoxia restrains the expression of complement component 9 in tumor-associated macrophages promoting non-small cell lung cancer progression

The tumor microenvironment, including stroma cells, signaling molecules, and the extracellular matrix, critically regulates the growth and survival of cancer cells. Dissecting the active molecules in tumor microenvironment may uncover the key factors that can impact cancer progression. Human NSCLC tumor tissue-conditioned medium (TCM) and adjacent nontumor tissue-conditioned medium (NCM) were used to treat two NSCLC cells LSC1 and LAC1, respectively. Cell growth and foci formation assays were applied to assess the effects of TCM and NCM on cancer cells. The active factors were identified by protein mass spectrometry. Cell growth and foci formation assays showed that 8 of 26 NCM and none of TCM could effectively lead to tumor cell lysis, which was known as tumoricidal activity. And then protein mass spectrometry analysis and functional verifications confirmed that complement component 9 (C9) played a crucial role in the complement-dependent cytotoxicity (CDC)-mediated tumoricidal activity in vitro. Furthermore, immunofluorescent staining revealed that C9 specifically expressed in most alveolar macrophages (AMs) in adjacent lung tissues and a small fraction of tumor-associated macrophages (TAMs) in NSCLC tissues. Most importantly, the percentage of C9-positive cells in AMs or TAMs was responsible for the tumoricidal activity of NCM and TCM. Herein, we found that high expression of C9 in TAMs was a significant independent prognostic factor (P = 0.029), and associated with beneficial overall survival (P = 0.012) and disease-free survival (P = 0.016) for patients with NSCLC. Finally, we unveiled that hypoxic tumor microenvironment could switch the phenotype of macrophages from M1 to M2 forms, accompanying with the downregulation of C9 in TAMs. Collectively, our findings elucidated a novel role of TAMs expressing C9 in the prognosis of NSCLC patients, which provided a promising strategy in the development of anticancer treatments based on the CDC-mediated tumoricidal activity.

The relevance of tyrosine kinase inhibitors for global metabolic pathways in cancer

Tumor metabolism is a thrilling discipline that focuses on mechanisms used by cancer cells to earn crucial building blocks and energy to preserve growth and overcome resistance to various treatment modalities. At the same time, therapies directed specifically against aberrant signalling pathways driven by protein tyrosine kinases (TKs) involved in proliferation, metastasis and growth count for several years to promising anti-cancer approaches. In this respect, small molecule inhibitors are the most widely used clinically relevant means for targeted therapy, with a rising number of approvals for TKs inhibitors. In this review, we discuss recent observations related to TKs-associated metabolism and to metabolic feedback that is initialized as cellular response to particular TK-targeted therapies. These observations provide collective evidence that therapeutic responses are primarily linked to such pathways as regulation of lipid and amino acid metabolism, TCA cycle and glycolysis, advocating therefore the development of further effective targeted therapies against a broader spectrum of TKs to treat patients whose tumors display deregulated signalling driven by these proteins.

Proteomic Profiling of Serial Prediagnostic Serum Samples for Early Detection of Colon Cancer in the U.S. Military

Background: Serum proteomic biomarkers offer a promising approach for early detection of cancer. In this study, we aimed to identify proteomic profiles that could distinguish colon cancer cases from controls using serial prediagnostic serum samples.Methods: This was a nested case-control study of active duty military members. Cases consisted of 264 patients diagnosed with colon cancer between 2001 and 2009. Controls were matched to cases on age, gender, race, serum sample count, and collection date. We identified peaks that discriminated cases from controls using random forest data analysis with a 2/3 training and 1/3 validation dataset. We then included epidemiologic data to see whether further improvement of model performance was obtainable. Proteins that corresponded to discriminatory peaks were identified.Results: Peaks with m/z values of 3,119.32, 2,886.67, 2,939.23, and 5,078.81 were found to discriminate cases from controls with a sensitivity of 69% and a specificity of 67% in the year before diagnosis. When smoking status was included, sensitivity increased to 76% while histories of other cancer and tonsillectomy raised specificity to 76%. Peaks at 2,886.67 and 3,119.32 m/z were identified as histone acetyltransferases while 2,939.24 m/z was a transporting ATPase subunit.Conclusions: Proteomic profiles in the year before cancer diagnosis have the potential to discriminate colon cancer patients from controls, and the addition of epidemiologic information may increase the sensitivity and specificity of discrimination.Impact: Our findings indicate the potential value of using serum prediagnostic proteomic biomarkers in combination with epidemiologic data for early detection of colon cancer. Cancer Epidemiol Biomarkers Prev; 26(5); 711-8. ©2016 AACR.

Identification of IGFBP2 and IGFBP3 As Compensatory Biomarkers for CA19-9 in Early-Stage Pancreatic Cancer Using a Combination of Antibody-Based and LC-MS/MS-Based Proteomics

Pancreatic cancer is one of the most lethal tumors, and reliable detection of early-stage pancreatic cancer and risk diseases for pancreatic cancer is essential to improve the prognosis. As 260 genes were previously reported to be upregulated in invasive ductal adenocarcinoma of pancreas (IDACP) cells, quantification of the corresponding proteins in plasma might be useful for IDACP diagnosis. Therefore, the purpose of the present study was to identify plasma biomarkers for early detection of IDACP by using two proteomics strategies: antibody-based proteomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. Among the 260 genes, we focused on 130 encoded proteins with known function for which antibodies were available. Twenty-three proteins showed values of the area under the curve (AUC) of more than 0.8 in receiver operating characteristic (ROC) analysis of reverse-phase protein array (RPPA) data of IDACP patients compared with healthy controls, and these proteins were selected as biomarker candidates. We then used our high-throughput selected reaction monitoring or multiple reaction monitoring (SRM/MRM) methodology, together with an automated sample preparation system, micro LC and auto analysis system, to quantify these candidate proteins in plasma from healthy controls and IDACP patients on a large scale. The results revealed that insulin-like growth factor-binding protein (IGFBP)2 and IGFBP3 have the ability to discriminate IDACP patients at an early stage from healthy controls, and IGFBP2 appeared to be increased in risk diseases of pancreatic malignancy, such as intraductal papillary mucinous neoplasms (IPMNs). Furthermore, diagnosis of IDACP using the combination of carbohydrate antigen 19-9 (CA19-9), IGFBP2 and IGFBP3 is significantly more effective than CA19-9 alone. This suggests that IGFBP2 and IGFBP3 may serve as compensatory biomarkers for CA19-9. Early diagnosis with this marker combination may improve the prognosis of IDACP patients.

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer

Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers.

Volunteer study and serum protein profiling to understand inflammatory response induced by Satsuma mandarin

It has been observed that consumption of a certain amount of Satsuma, lychee, and longan often caused a symptom characterized by dry or sore throat, gum swelling and even mouth ulcer, which significantly impaired the life quality of a large population. We define the adverse reaction to Satsuma as Satsuma-induced syndrome (SIS). Volunteers were assigned to oral Satsuma challenge in an open manner. The results showed that SIS was characterized with symptoms affecting the throat, oral cavity, face, gastrointestinal system and eye either individually or in combination. A comparative proteomic study was performed to investigate the differences of serum proteins in the Post-SC (after Satsuma challenge) and Pre-SC (before Satsuma challenge) serum samples of 15 volunteers with severe SIS. Ten proteins were identified to be differentially expressed (P<0.05). Of these, levels of complement component C9 precursor were elevated significantly in the Post-SC serum samples and were further verified by enzyme-linked immunosorbent assay, indicating that the complement system may be activated and plays a significant role in inflammatory response. Meanwhile, serum samples were subjected to immobilized metal affinity capture (IMAC3) protein chip surfaces and tested by surface-enhanced laser desorption/ionization-time of flight-mass spectrometry. The data were analyzed by Ciphergen ProteinChip Software. A diagnostic model was constructed to discriminate the SIS from normal samples, using principal component analysis. A total of 50 detected biomarkers were found to be different with statistical significance (P<0.05). The multivariate logistic analysis demonstrates a complete distinction between the two groups. Our findings suggest that these assays may provide potential biomarkers for the diagnosis of SIS.

Reverse Phase Protein Arrays-Quantitative Assessment of Multiple Biomarkers in Biopsies for Clinical Use

Reverse Phase Protein Arrays (RPPA) represent a very promising sensitive and precise high-throughput technology for the quantitative measurement of hundreds of signaling proteins in biological and clinical samples. This array format allows quantification of one protein or phosphoprotein in multiple samples under the same experimental conditions at the same time. Moreover, it is suited for signal transduction profiling of small numbers of cultured cells or cells isolated from human biopsies, including formalin fixed and paraffin embedded (FFPE) tissues. Owing to the much easier sample preparation, as compared to mass spectrometry based technologies, and the extraordinary sensitivity for the detection of low-abundance signaling proteins over a large linear range, RPPA have the potential for characterization of deregulated interconnecting protein pathways and networks in limited amounts of sample material in clinical routine settings. Current aspects of RPPA technology, including dilution curves, spotting, controls, signal detection, antibody validation, and calculation of protein levels are addressed.

Plasma clusterin as a candidate pre-diagnosis marker of colorectal cancer risk in the Florence cohort of the European Prospective Investigation into Cancer and Nutrition: a pilot study

BACKGROUND

Colorectal cancer is one of the major causes of cancer mortality world-wide. Prevention would improve if at-risk subjects could be identified. The aim of this study was to characterise plasma protein biomarkers associated with the risk of colorectal cancer in samples collected prospectively, before the disease diagnosis.

METHODS

After an exploratory study on the comprehensive plasma proteome analysis by liquid chromatography-tandem mass spectrometry from ten colorectal cancer cases enrolled at diagnosis, and ten matched controls (Phase 1), a similar preliminary study was performed on prospective plasma samples from ten colorectal cancer cases, enrolled years before disease development, and ten matched controls identified in a nested case-control study within the Florence cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC) study (Phase 2); in Phase 3 the validation of the candidate biomarkers by targeted proteomics on 48 colorectal cancer cases and 48 matched controls from the Florence-EPIC cohort, and the evaluation of the disease risk were performed.

RESULTS

Systems biology tools indicated that both in the Phase 1 and Phase 2 studies circulating protein levels differing in cases more than 1.5 times from controls, were involved in inflammation and/or immune response. Eight proteins including apolipoprotein C-II, complement C4-B, complement component C9, clusterin, alpha-2-HS-glycoprotein, mannan-binding lectin serine-protease, mannose-binding protein C, and N-acetylmuramoyl-L-alanine amidase were selected as promising candidate biomarkers. Targeted proteomics of the selected proteins in the EPIC samples showed significantly higher clusterin levels in cases than controls, but only in men (mean ± SD, 1.98 ± 0.46 and 1.61 ± 0.43 nmol/mL respectively, Mann-Whitney U, two-tailed P = 0.0173). The remaining proteins were unchanged. Using multivariate logistic models a significant positive association emerged for clusterin, with an 80% increase in the colorectal cancer risk with protein's unit increase, but only in men.

CONCLUSIONS

The results show that plasma proteins can be altered years before colorectal cancer detection. The high circulating clusterin in pre-diagnostic samples suggests this biomarker can improve the identification of people at risk of colorectal cancer and might help in designing preventive interventions.

Colorectal cancer biomarker discovery and validation using LC-MS/MS-based proteomics in blood: truth or dare?

Globally, colorectal cancer (CRC) is the third most common malignant neoplasm. However, highly sensitive, specific, noninvasive tests that allow CRC diagnosis at an early stage are still needed. As circulatory blood reflects the physiological status of an individual and/or the disease status for several disorders, efforts have been undertaken to identify candidate diagnostic CRC markers in plasma and serum. In this review, the challenges, bottlenecks and promising properties of mass spectrometry (MS)-based proteomics in blood are discussed. More specifically, important aspects in clinical design, sample retrieval, sample preparation, and MS analysis are presented. The recent developments in targeted MS approaches in plasma or serum are highlighted as well.

Proteomics for discovery of candidate colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers.

Identification of a circulating microRNA signature for colorectal cancer detection

Prognosis of patients with colorectal cancer (CRC) is generally poor because of the lack of simple, convenient, and noninvasive tools for CRC detection at the early stage. The discovery of microRNAs (miRNAs) and their different expression profiles among different kinds of diseases has opened a new avenue for tumor diagnosis. We built a serum microRNA expression profile signature and tested its specificity and sensitivity as a biomarker in the diagnosis of CRC. We also studied its possible role in monitoring the progression of CRC. We conducted a two phase case-control test to identify serum miRNAs as biomarkers for CRC diagnosis. Using quantitative reverse transcription polymerase chain reactions, we tested ten candidate miRNAs in a training set (30 CRCs vs 30 controls). Risk score analysis was used to evaluate the diagnostic value of the serum miRNA profiling system. Other independent samples, including 83 CRCs and 59 controls, were used to validate the diagnostic model. In the training set, six serum miRNAs (miR-21, let-7g, miR-31, miR-92a, miR-181b, and miR-203) had significantly different expression levels between the CRCs and healthy controls. Risk score analysis demonstrated that the six-miRNA-based biomarker signature had high sensitivity and specificity for distinguishing the CRC samples from cancer-free controls. The areas under the receiver operating characteristic (ROC) curve of the six-miRNA signature profiles were 0.900 and 0.923 for the two sets of serum samples, respectively. However, for the same serum samples, the areas under the ROC curve used by the tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were only 0.649 and 0.598, respectively. The expression levels of the six serum miRNAs were also correlated with CRC progression. Thus, the identified six-miRNA signature can be used as a noninvasive biomarker for the diagnosis of CRC, with relatively high sensitivity and specificity.

Proteomics, genomics and transcriptomics: their emerging roles in the discovery and validation of colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cancer in females and the third in males. Since CRC is often diagnosed at an advanced stage when prognosis is poor, identification of biomarkers for early diagnosis is urgently required. Recent advances in proteomics, genomics and transcriptomics have facilitated high-throughput profiling of data generated from CRC-related genes and proteins, providing a window of information for biomarker discovery and validation. However, transfer of candidate biomarkers from bench to bedside remains a dilemma. In this review, we will discuss emerging proteomic technologies and highlight various sample types utilized for proteomics-based identification of CRC biomarkers. Moreover, recent breakthroughs in genomics and transcriptomics for the identification of CRC biomarkers, with particular emphasis on the merits of emerging methylomic and miRNAomic strategies, will be discussed. Integration of proteomics, genomics and transcriptomics will facilitate the discovery and validation of CRC biomarkers leading to the emergence of personalized medicine.

Identification of candidate biomarkers for hepatocellular carcinoma in plasma of HCV-infected cirrhotic patients by 2-D DIGE

BACKGROUND

The current methods available for screening and detecting hepatocellular carcinoma (HCC) have insufficient sensitivity and specificity, and only a low percentage of diagnosis of small tumours is based on these assays. Because HCC is usually asymptomatic at potentially curative stages, identification of biomarkers for the early detection of HCC is essential to improve patient survival.

AIM

The aim of this study was to identify candidate markers for HCC development in the plasma from hepatitis C virus (HCV)-infected cirrhotic patients.

METHODS

We compared protein expression profiles of plasma samples from HCV-infected cirrhotic patients with and without HCC, using two-dimensional fluorescence difference gel electrophoresis (2-D DIGE) coupled with MALDI-TOF/TOF mass spectrometry. The 2-D DIGE results were analysed statistically using Decyder™ software, and verified by western blot and enzyme-linked immunosorbent assay (ELISA).

RESULTS

In the plasma of HCV-infected HCC patients, we observed decreased expression of complement component 9, ficolin-3 (FCN3), serum amyloid P component (SAP), fibrinogen-gamma and immunoglobulin gamma-1 chain, and increased expression of vitronectin (VTN) and galectin-3 binding protein (G3BP) by DIGE analysis. ELISA confirmed DIGE results for VTN and G3BP but not for SAP or FCN3 in a larger patient population.

CONCLUSIONS

The proteins VTN and SAP are candidate biomarkers for HCC development in HCV-infected cirrhotic patients.

Galectin-7 as a potential predictive marker of chemo- and/or radio-therapy resistance in oral squamous cell carcinoma

Treatment of advanced oral squamous cell carcinoma (OSCC) requires the integration of multimodal approaches. The aim of this study was to identify predictors of tumor sensitivity to preoperative radiotherapy/chemotherapy for OSCC in order to allow oncologists to determine optimum therapeutic strategies without the associated adverse effects. Here, the protein expression profiles of formalin-fixed paraffin-embedded (FFPE) tissue samples from 18 OSCC patients, termed learning cases, who received preoperative chemotherapy and/or radiotherapy followed by surgery were analyzed by quantitative proteomics and validated by immunohistochemistry in 68 test cases as well as in the 18 learning cases. We identified galectin-7 as a potential predictive marker of chemotherapy and/or radiotherapy resistance, and the sensitivity and specificity of the galectin-7 prediction score (G7PS) in predicting this resistance was of 96.0% and 39.5%, respectively, in the 68 test cases. The cumulative 5-year disease-specific survival rate was 75.2% in patients with resistant prediction using G7PS and 100% in patients with sensitive prediction. In vitro overexpression of galectin-7 significantly decreased cell viability in OSCC cell line. Therefore, our findings suggest that galectin-7 is a potential predictive marker of chemotherapy and/or radiotherapy resistance in patients with OSCC.

Identification of proteins differentially expressed in OSSC samples from patients sensitive or resistant. The samples were processed by LC-MS and analyzed with 2DICAL.

Developing proteomics-based biomarkers for colorectal neoplasms for clinical practice: opportunities and challenges

Colorectal cancer (CRC) arises from the normal colon epithelium through the accumulation of genetic mutations and epigenetic alterations that are associated with progression along the histological adenoma-adenocarcinoma sequence. Elucidating the molecular alterations underlying disease progression will not only provide insight into the behavior of the tumors, but also could lead to the discovery of useful biomarkers for diagnosis, monitoring treatment responsiveness, or predicting disease outcomes. In the past a few years, there have been several evaluating differentially expressed protein biomarkers by employing proteomics technologies coupled with mass spectrometry. In the current review, we will briefly summarize the results from selected recent studies using tissue or serum samples from CRC patients in the past 5 years and discuss the opportunities and challenges in translating these findings from the research setting to clinical practice.

Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.

Aptamer based, non-PCR, non-serological detection of Chagas disease biomarkers in Trypanosoma cruzi infected mice

Chagas disease affects about 5 million people across the world. The etiological agent, the intracellular parasite Trypanosoma cruzi (T. cruzi), can be diagnosed using microscopy, serology or PCR based assays. However, each of these methods has their limitations regarding sensitivity and specificity, and thus to complement these existing diagnostic methods, alternate assays need to be developed. It is well documented that several parasite proteins called T. cruzi Excreted Secreted Antigens (TESA), are released into the blood of an infected host. These circulating parasite antigens could thus be used as highly specific biomarkers of T. cruzi infection. In this study, we have demonstrated that, using a SELEx based approach, parasite specific ligands called aptamers, can be used to detect TESA in the plasma of T. cruzi infected mice. An Enzyme Linked Aptamer (ELA) assay, similar to ELISA, was developed using biotinylated aptamers to demonstrate that these RNA ligands could interact with parasite targets. Aptamer L44 (Apt-L44) showed significant and specific binding to TESA as well as T. cruzi trypomastigote extract and not to host proteins or proteins of Leishmania donovani, a related trypanosomatid parasite. Our result also demonstrated that the target of Apt-L44 is conserved in three different strains of T. cruzi. In mice infected with T. cruzi, Apt-L44 demonstrated a significantly higher level of binding compared to non-infected mice suggesting that it could detect a biomarker of T. cruzi infection. Additionally, Apt-L44 could detect these circulating biomarkers in both the acute phase, from 7 to 28 days post infection, and in the chronic phase, from 55 to 230 days post infection. Our results show that Apt-L44 could thus be used in a qualitative ELA assay to detect biomarkers of Chagas disease.

Chagas disease, caused by the parasite Trypanosoma cruzi, is a major health concern for people living in Latin America. There are no vaccines to prevent this disease and only two drugs are prescribed for treatment. Current methods to diagnose patients are not always successful and thus new methods need to be developed. One approach to develop an alternate method is to detect proteins and metabolites that are secreted by parasites into the blood of infected individuals. We have utilized a selection based method to isolate ligands that bind to these secreted proteins. These ligands, called aptamers, have been used to develop an assay that can detect the circulating parasite targets in the plasma or serum of an infected host. In an animal model of Chagas disease, our assay can detect parasite biomarkers as early as seven days after infection and as late as 230 days post infection. As the laboratory instruments and procedures are similar to performing an ELISA, the aptamer assay reported here could be easily performed at diagnostic facilities. Further improvement in this assay can lead to a new quantitative diagnostic test for Chagas disease. A similar selection based approach could also be used to develop ligands for the detection of biomarkers in other diseases.

Exploratory proteomic analysis of hypobaric hypoxia and acute mountain sickness in humans

Our objective in this exploratory study was to identify novel biomarkers of importance for acute mountain sickness (AMS) using discovery-based proteomic methods. Peripheral blood samples were collected and AMS symptoms were assessed in 20 healthy volunteers prior to [-15 h (baseline) and 0 h; 1,609 m; barometric pressure = 625 mmHg] and after a 9-h exposure to hypobaric hypoxia (9 h; 4,875 m; barometric pressure = 425 mmHg). AMS status was assessed using the Lake Louise Questionnaire. Plasma samples were pooled according to AMS status at each time point. Protein composition of the samples was determined by a GeLC-MS/MS approach using two analytical platforms (LTQ-XL linear ion trap mass spectrometer and a LTQ-FT ultra hybrid mass spectrometer) for technical replication. Spectral counting was used to make semiquantitative comparisons of protein abundance between AMS-susceptible (AMS) and AMS-resistant (AMS·R) subjects with exposure to hypobaric hypoxia. After 9 h of hypoxia, the abundance of proteins with antioxidant properties (i.e., peroxiredoxin 6, glutathione peroxidase, and sulfhydryl oxidase 1) rose in AMS but not AMS·R. Our exploratory analyses suggest that exposure to hypobaric hypoxia enhances enzymatic antioxidant systems in AMS vs. AMS·R, which, we propose, may be an overcompensation for hypoxia-induced oxidant production. On the basis of our findings we 1) speculate that quenching oxidant activity may have adverse downstream effects that are of pathophysiological importance for AMS such as interrupting oxidant-sensitive cell signaling and gene transcription and 2) question the existing assumption that increased oxidant production in AMS is pathological.

Proteomic and cytokine plasma biomarkers for predicting progression from colorectal adenoma to carcinoma in human patients

In the present study, we screened proteomic and cytokine biomarkers between patients with adenomatous polyps and colorectal cancer (CRC) in order to improve our understanding of the molecular mechanisms behind turmorigenesis and tumor progression in CRC. To this end, we performed comparative proteomic analysis of plasma proteins using a combination of 2DE and MS as well as profiled differentially regulated cytokines and chemokines by multiplex bead analysis. Proteomic analysis identified 11 upregulated and 13 downregulated plasma proteins showing significantly different regulation patterns with diagnostic potential for predicting progression from adenoma to carcinoma. Some of these proteins have not previously been implicated in CRC, including upregulated leucine-rich α-2-glycoprotein, hemoglobin subunit β, Ig α-2 chain C region, and complement factor B as well as downregulated afamin, zinc-α-2-glycoprotein, vitronectin, and α-1-antichymotrypsin. In addition, plasma levels of three cytokines/chemokines, including interleukin-8, interferon gamma-induced protein 10, and tumor necrosis factor α, were remarkably elevated in patients with CRC compared to those with adenomatous polyps. Although further clinical validation is required, these proteins and cytokines can be established as novel biomarkers for CRC and/or its progression from colon adenoma.

Quantitative targeted absolute proteomics-based large-scale quantification of proline-hydroxylated α-fibrinogen in plasma for pancreatic cancer diagnosis

Pancreatic cancer is a devastating disease and early diagnosis and treatment are essential to improve the prognosis. We previously showed that α-fibrinogen containing hydroxylated proline residues at positions 530 and 565 is increased in plasma of pancreatic cancer patients. However, no antibody specific for hydroxylated proline-530 is available. Therefore, the purposes of this study were to develop a quantification method specific for both proline-hydroxylated α-fibrinogens by selected/multiple reaction monitoring (SRM/MRM), and to validate these modifications as pancreatic cancer markers. The target peptide for hydroxylated proline-530 contained methionine, and since variable partial oxidation of this residue would affect the quantification, hydrogen peroxide treatment was carried out to ensure complete oxidation. Quantification values of modified and unmodified α-fibrinogen were well correlated with those obtained by immunoblotting. Concentrations of modified and unmodified α-fibrinogen were quantified in 70 pancreatic cancer patients and 27 healthy controls. Percent hydroxylation of α-fibrinogen and concentration of hydroxylated α-fibrinogen were significantly greater in the plasma of patients. Furthermore, among 8 carbohydrate antigen 19-9 (CA19-9)-negative patients in stages I/II, 6 were positive for proline-hydroxylated α-fibrinogen. These results indicate that plasma concentration of proline-hydroxylated α-fibrinogen measured by SRM/MRM analysis may be a good pancreatic cancer marker, especially in CA19-9-negative patients.

The application of quantification techniques in proteomics for biomedical research

The systematic analysis of biological processes requires an understanding of the quantitative expression patterns of proteins, their interacting partners and their subcellular localization. This information was formerly difficult to accrue as the relative quantification of proteins relied on antibody-based methods and other approaches with low throughput. The advent of soft ionization techniques in mass spectrometry plus advances in separation technologies has aligned protein systems biology with messenger RNA, DNA, and microarray technologies to provide data on systems as opposed to singular protein entities. Another aspect of quantitative proteomics that increases its importance for the coming few years is the significant technical developments underway both for high pressure liquid chromatography and mass spectrum devices. Hence, robustness, reproducibility and mass accuracy are still improving with every new generation of instruments. Nonetheless, the methods employed require validation and comparison to design fit for purpose experiments in advanced protein analyses. This review considers the newly developed systematic protein investigation methods and their value from the standpoint that relative or absolute protein quantification is required de rigueur in biomedical research.

Proteomic approaches to the discovery of cancer biomarkers for early detection and personalized medicine

Cancer biomarkers for the early detection of malignancies and selection of therapeutic strategies have been requested in the clinical field. Accurate and informative cancer biomarkers hold significant promise for improvements in the early detection of disease and in the selection of the most effective therapeutic strategies. Recently, significant progress in the comprehensive analysis of the human genome, epigenome, transcriptome, proteome and metabolome has led to revolutionary changes in the discovery of cancer biomarkers. The Human Proteome Organization has launched a global Human Proteome Project to map the entire human protein set. The Human Proteome Project research group has focused on three working proteomic pillars-mass spectrometry-based, antibody-based and knowledge-based proteomics-and each of these technologies is advancing rapidly. In this review, we introduce the proteomic platforms that are currently being used for cancer biomarker discovery, and describe examples of novel cancer biomarkers that were identified with each proteomic technology.

Carbonic anhydrase I as a new plasma biomarker for prostate cancer

Serum prostate-specific antigen (PSA) levels ranging from 4 to 10 ng/mL is considered a diagnostic gray zone for detecting prostate cancer because biopsies reveal no evidence of cancer in 75% of these subjects. Our goal was to discover a new highly specific biomarker for prostate cancer by analyzing plasma proteins using a proteomic technique. Enriched plasma proteins from 25 prostate cancer patients and 15 healthy controls were analyzed using a label-free quantitative shotgun proteomics platform called 2DICAL (2-dimensional image converted analysis of liquid chromatography and mass spectrometry) and candidate biomarkers were searched. Among the 40,678 identified mass spectrum (MS) peaks, 117 peaks significantly differed between prostate cancer patients and healthy controls. Ten peaks matched carbonic anhydrase I (CAI) by tandem MS. Independent immunological assays revealed that plasma CAI levels in 54 prostate cancer patients were significantly higher than those in 60 healthy controls (P = 0.022, Mann-Whitney U test). In the PSA gray-zone group, the discrimination rate of prostate cancer patients increased by considering plasma CAI levels. CAI can potentially serve as a valuable plasma biomarker and the combination of PSA and CAI may have great advantages for diagnosing prostate cancer in patients with gray-zone PSA level.

Development of multiplexed bead-based immunoassays for the detection of early stage ovarian cancer using a combination of serum biomarkers

CA125 as a biomarker of ovarian cancer is ineffective for the general population. The aim of this study was to evaluate multiplexed bead-based immunoassay of multiple ovarian cancer-associated biomarkers such as transthyretin and apolipoprotein A1, together with CA125, to improve the identification and evaluation of prognosis of ovarian cancer. We measured the serum levels of CA125, transthyretin, and apolipoprotein A1 from the serum of 61 healthy individuals, 84 patients with benign ovarian disease, and 118 patients with ovarian cancer using a multiplex liquid assay system, Luminex 100. The results were then analyzed according to healthy and/or benign versus ovarian cancer subjects. When CA125 was combined with the other biomarkers, the overall sensitivity and specificity were significantly improved in the ROC curve, which showed 95% and 97% sensitivity and specificity, respectively. At 95% specificity for all stages the sensitivity increased to 95.5% compared to 67% for CA125 alone. For stage I+II, the sensitivity increased from 30% for CA125 alone to 93.9%. For stage III+IV, the corresponding values were 96.5% and 91.6%, respectively. Also, the three biomarkers were sufficient for maximum separation between noncancer (healthy plus benign group) and stage I+II or all stages (I-IV) of disease. The new combination of transthyretin, and apolipoprotein A1 with CA125 improved both the sensitivity and the specificity of ovarian cancer diagnosis compared with those of individual biomarkers. These findings suggest the benefit of the combination of these markers for the diagnosis of ovarian cancer.

Mass Spectrometry-based Proteomics and Peptidomics for Systems Biology and Biomarker Discovery

The scientific community has shown great interest in the field of mass spectrometry-based proteomics and peptidomics for its applications in biology. Proteomics technologies have evolved to produce large datasets of proteins or peptides involved in various biological and disease progression processes producing testable hypothesis for complex biological questions. This review provides an introduction and insight to relevant topics in proteomics and peptidomics including biological material selection, sample preparation, separation techniques, peptide fragmentation, post-translation modifications, quantification, bioinformatics, and biomarker discovery and validation. In addition, current literature and remaining challenges and emerging technologies for proteomics and peptidomics are presented.

Biomarker Discovery of Pancreatic and Gastrointestinal Cancer by 2DICAL: 2-Dimensional Image-Converted Analysis of Liquid Chromatography and Mass Spectrometry

Biomarkers tested by blood sample are of great use to clinicians as they provide useful information to aid an early and accurate diagnosis. Comprehensive “omics” studies are expected to facilitate the identification of such new biomarkers, and much research is being performed in this area. Our proteomics analysis system of 2-dimensional image-converted analysis of liquid chromatography and mass spectrometry (2DICAL) has successfully identified several new blood biomarkers from the clinical blood samples of pancreatic and colorectal cancer patients.

Fucosylated glycoproteomic approach to identify a complement component 9 associated with squamous cell lung cancer (SQLC)

Human lung cancer is a major cause of cancer mortality worldwide. Understanding the pathophysiological features and the development of novel biomarkers for diagnosis as well as treatment are major tasks. In the present study, sera from ten SQLC patients and healthy control (HEC) were collected and pooled, respectively. The pooled sera were depleted via an immunoaffinity method and further subjected to fucosylation enrichment. Enriched fucosylated glycoproteins were resolved by SDS-PAGE and subsequently analyzed by LC-ESI-MS/MS. From comparative proteomic analysis, we selected the C9 protein. C9 protein levels were validated by Western blot, protein arrays and the fucosylation levels of C9 by hybrid lectin ELISA (HLE) in the sera of 120 HEC and 118 SQLC patients. The C9 protein level was 6.4-fold higher in SQLC patients compared to HEC, as determined by Western blot analysis. The results were concurrently confirmed by a protein array that showed a C9 level significantly higher in SQLC patients, as compared to HEC, with a sensitivity of 53% and a specificity of 89%. C9 fucosylation levels were significantly higher in SQLC patients compared to HEC (p<0.05) when tested by HLE. These findings suggest that C9 and fucosylated form could serve as a useful marker for SQLC.