Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics

Selected reaction monitoring (SRM) - also known as multiple reaction monitoring (MRM) - has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for, e.g. detecting low-abundance biomarkers likely present at the low ng/mL to pg/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in cells or tissues. Herein, we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides including posttranslational modifications, as well as advances in MS instrumentation which have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low- to sub-ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed.     

应用蛋白质组学筛选宫颈癌患者尿液中的肿瘤标志物

通过比较健康女性和宫颈癌患者的尿蛋白质组,发现并分析差异表达蛋白,从中筛选潜在的宫颈癌的标志物。研究对象由43名宫颈癌患者（CC）和47名健康女性（HW）组成。用超速离心法沉淀尿蛋白,再用一维凝胶电泳（SDS-PAGE）与液相色谱-质谱联用技术（LC-MS/MS）鉴定尿液中的蛋白质,蛋白质定量采用无标定量。比较患者尿蛋白质组、健康对照的尿蛋白质组和宫颈癌组织蛋白质组,有1910个蛋白质是患者和健康对照共有的尿蛋白,这其中有746个蛋白质也存在于宫颈癌组织蛋白质组。在这746个蛋白质中找到84个上调蛋白和82下调蛋白。通过生物信息学分析发现牛皮癣素（S100A7）和癌胚抗原相关细胞黏附分子8（CEACAM8）是宫颈癌尿液样本独有蛋白质。在验证组的70例样本中,双盲法测试S100A7、CEACAM8以及两者联合诊断宫颈癌的敏感性能达到73%、87%、93%。结果提示,宫颈癌患者的尿蛋白质组与健康女性的尿蛋白质组不同,并且S100A7和CEACAM8可以作为宫颈癌潜在的肿瘤标志物。     

Development of protein biomarkers in cerebrospinal fluid for secondary progressive multiple sclerosis using selected reaction monitoring mass spectrometry (SRM-MS)

ABSTRACT: BACKGROUND: Multiple sclerosis (MS) is a chronic inflammatory disorder of the central nervous system (CNS). It involves damage to the myelin sheath surrounding axons and to the axons themselves. MS most often presents with a series of relapses and remissions but then evolves over a variable period of time into a slowly progressive form of neurological dysfunction termed secondary progressive MS (SPMS). The reasons for this change in clinical presentation are unclear. The absence of a diagnostic marker means that there is a lag time of several years before the diagnosis of SPMS can be established. At the same time, understanding the mechanisms that underlie SPMS is critical to the development of rational therapies for this untreatable stage of the disease. RESULTS: Using LC coupled mass spectrometry; we have established a highly specific and sensitive multiplex selected reaction monitoring (SRM) assay. Our SRM assay has facilitated the simultaneous detection of surrogate peptides originating from 28 proteins present in cerebrospinal fluid (CSF). Protein levels in CSF are generally ~200-fold lower than that in human sera. A limit of detection (LOD) was determined to be as low as one femtomole per uL. We processed and analysed CSF samples from a total of 22 patients with SPMS, 12 patients with non-inflammatory neurological disorders (NIND) and 10 age-matched healthy controls in parallel for the levels of 28 selected potential protein biomarkers, followed by principal component analysis (PCA) for clustering protein biomarkers. Our SRM data suggested different levels of agrin, kallikrein and putative myosin-XVB in SPMS patients as compared to healthy controls. PCA reveals that these proteins are correlated, can be grouped into four principal components. Overall, we established an efficient platform to verify protein biomarkers in CSF, which can be easily adapted to other proteins of interest related to neurodegenerative diseases. CONCLUSIONS: A highly specific and sensitive multiplex SRM-MS assay was established for verifying CSF protein biomarkers in SPMS. Three proteins were found to be expressed significantly differently in SPMS patients as compared to health controls, which will help further our current understanding of SPMS disease pathology and/or therapeutic intervention.     

RAS and RHO family GTPase mutations in cancer: twin sons of different mothers?

Abstract

The RAS and RHO family comprise two major branches of the RAS superfamily of small GTPases. These proteins function as regulated molecular switches and control cytoplasmic signaling networks that regulate a diversity of cellular processes, including cell proliferation and cell migration. In the early 1980s, mutationally activated RAS genes encoding KRAS, HRAS and NRAS were discovered in human cancer and now comprise the most frequently mutated oncogene family in cancer. Only recently, exome sequencing studies identified cancer-associated alterations in two RHO family GTPases, RAC1 and RHOA. RAS and RHO proteins share significant identity in their amino acid sequences, protein structure and biochemistry. Cancer-associated RAS mutant proteins harbor missense mutations that are found primarily at one of three mutational hotspots (G12, G13 and Q61) and have been identified as gain-of-function oncogenic alterations. Although these residues are conserved in RHO family proteins, the gain-of-function mutations found in RAC1 are found primarily at a distinct hotspot. Unexpectedly, the cancer-associated mutations found with RHOA are located at different hotspots than those found with RAS. Furthermore, since the RHOA mutations suggested a loss-of-function phenotype, it has been unclear whether RHOA functions as an oncogene or tumor suppressor in cancer development. Finally, whereas RAS mutations are found in a broad spectrum of cancer types, RHOA and RAC1 mutations occur in a highly restricted range of cancer types. In this review, we focus on RHOA missense mutations found in cancer and their role in driving tumorigenesis, with comparisons to cancer-associated mutations in RAC1 and RAS GTPases.     

Serum differential protein identification of Xinjiang Kazakh esophageal cancer patients based on the two-dimensional liquid-phase chromatography and LTQ MS

The aim of this study was to investigate the impact of chemo-radiotherapy on serum protein expression of the esophageal cancer patients and discover potential biomarkers by detecting serum proteins mass spectrometry of the healthy Kazakh people in Xinjiang as well as the patients before and after their chemo-radiotherapy. In order to separate and compare the three serum samples (the healthy group’s, the patients’ before and after chemo-radiotherapy) with two-dimensional protein liquid chromatography system (Proteome LabTM PF-2D), then detect the differential protein spots with linear trap quadruple mass spectrometer (LTQ MS/MS). (1) The Kazakh esophageal cancer patients got 21 expressed protein spots peaks with significant difference after chemo-radiotherapy compared with before; before the treatment there were 10 different expressed protein spots compared with the healthy group, and after it there were four peaks in the expression of protein spots compared with the healthy group. (2) After LTQ mass spectrometric detection, 22 proteins were up-regulated in serum samples of the healthy group, 22 were up-regulated of the patients before medical treatment and 5 were up-regulated after chemo-radiotherapy. (3) 8 proteins including APOA1 can be served as serum markers in Kazakh esophageal cancer diagnosis, and proteins like CLU can be served as serum markers in judging the resistance and sensitivity towards chemo-radiotherapy. (4) The abnormal expressions of APOC2, APOC3, Antithrombin-III in esophageal cancer were discovered for the first time. Specific protein spots related to Xinjiang Kazakh esophageal cancer diagnosis and chemo-radiotherapy can be identified in the serum, which will probably become a maker in Kazakh esophageal cancer diagnosis and therapeutic evaluation.     

Comparison of targeted proteomics approaches for detecting and quantifying proteins derived from human cancer tissues

Targeted mass spectrometry‐based proteomics approaches enable the simultaneous and reproducible quantification of multiple protein analytes across numerous conditions in biology and clinical studies. These approaches involve e.g. selected reaction monitoring (SRM) typically conducted on a triple quadrupole mass spectrometer, its high‐resolution variant named pseudo‐SRM (p‐SRM), carried out in a quadrupole coupled with an TOF analyzer (qTOF), and “sequential window acquisition of all theoretical spectra” (SWATH). Here we compared these methods in terms of signal‐to‐noise ratio (S/N), coefficient of variance (CV), fold change (FC), limit of detection and quantitation (LOD, LOQ). We have shown the highest S/N for p‐SRM mode, followed by SRM and SWATH, demonstrating a trade‐off between sensitivity and level of multiplexing for SRM, p‐SRM, and SWATH. SRM was more sensitive than p‐SRM based on determining their LOD and LOQ. Although SWATH has the worst S/N, it enables peptide multiplexing with post‐acquisition definition of the targets, leading to better proteome coverage. FC between breast tumors of different clinical‐pathological characteristics were highly correlated (R²>0.97) across three methods and consistent with the previous study on 96 tumor tissues. Our technical note presented here, therefore, confirmed that outputs of all the three methods were biologically relevant and highly applicable to cancer research.     

基于质谱的选择反应监测技术相关策略和方法的研究进展

随着蛋白质组学研究的不断深入,基于质谱的选择反应监测技术(SRM)已经成为以发现生物标志物为代表的定向蛋白质组学研究的重要手段.SRM技术根据假设信息,特异性地获取符合假设条件的质谱信号,去除不符合条件的离子信号干扰,从而得到特定蛋白质的定量信息.SRM技术具有更高的灵敏度和精确性、更大的动态范围等优势.该技术可分为实验设计、数据获取和数据分析三个步骤.在这几个步骤中,最重要的是利用生物信息学手段总结当前实验数据的结果,并用机器学习方法和总结的经验规则进行SRM实验的母离子和子离子对的预测.针对数据质控和定量的生物信息学方法研究在提高SRM数据可靠性方面具有重要作用.此外,为方便SRM的研究,本文还收集、汇总了SRM技术相关的软件、工具和数据库资源.随着质谱仪器的不断发展,新的SRM实验策略以及分析方法、计算工具也应运而生.结合更优化的实验策略、方法,采用更精准的生物信息学算法和工具,SRM在未来蛋白质组学的发展中将发挥更加重要的作用.     

An assessment of current bioinformatic solutions for analyzing LC-MS data acquired by selected reaction monitoring technology

Selected reaction monitoring (SRM) is an accurate quantitative technique, typically used for small-molecule mass spectrometry (MS). SRM has emerged as an important technique for targeted and hypothesis-driven proteomic research, and is becoming the reference method for protein quantification in complex biological samples. SRM offers high selectivity, a lower limit of detection and improved reproducibility, compared to conventional shot-gun-based tandem MS (LC-MS/MS) methods. Unlike LC-MS/MS, which requires computationally intensive informatic postanalysis, SRM requires preacquisition bioinformatic analysis to determine proteotypic peptides and optimal transitions to uniquely identify and to accurately quantitate proteins of interest. Extensive arrays of bioinformatics software tools, both web-based and stand-alone, have been published to assist researchers to determine optimal peptides and transition sets. The transitions are oftentimes selected based on preferred precursor charge state, peptide molecular weight, hydrophobicity, fragmentation pattern at a given collision energy (CE), and instrumentation chosen. Validation of the selected transitions for each peptide is critical since peptide performance varies depending on the mass spectrometer used. In this review, we provide an overview of open source and commercial bioinformatic tools for analyzing LC-MS data acquired by SRM.     

利用基因组学和MALDI-TOF MS技术鉴定放线菌纲细菌的核糖体蛋白质标志物

【目的】基质辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)法基于微生物的特征蛋白指纹图谱鉴定菌种,本研究利用基因组学和MALDI-TOFMS技术鉴定放线菌纲细菌的核糖体蛋白质标志物。【方法】从MALDI-TOF MS图谱数据库选取放线菌纲代表菌种,在基因组数据库检索目标菌种,获取目标菌株或其参比菌株的核糖体蛋白质序列,计算获得分子质量理论值,用于注释目标菌株MALDI-TOFMS指纹图谱中的核糖体蛋白质信号。【结果】从8目,24科,53属,114种,142株放线菌的MALDI-TOFMS图谱中总共注释出31种核糖体蛋白质。各菌株的指纹图谱中核糖体蛋白质信号数量差异显著。各种核糖体蛋白质信号的注释次数差异显著。总共15种核糖体蛋白质在超过半数图谱中得到注释,注释次数最高的是核糖体大亚基蛋白质L36。【结论】本研究找到了放线菌纲细菌MALDI-TOF MS图谱中常见的15种核糖体蛋白质信号,可为通过识别核糖体蛋白质的质谱特征峰鉴定放线菌的方法建立提供依据。     

The association of a distinct plasma proteomic profile with the cervical high-grade squamous intraepithelial lesion of Uyghur women: a 2D liquid-phase chromatography/mass spectrometry study

Objective: To identify plasma protein biomarkers of cervical high-grade squamous intraepithelial lesion (HSIL) of Uyghur women by proteomics approach.

Methods: Plasma protein samples of Uyghur women with HSIL and chronic cervicitis were analyzed with 2D HPLC followed by detection of target proteins with Linear Trap Quadrupole Mass Spectrometer (LTQ MS/MS).

Results: We detected three upregulated and one downregulated protein peaks representing protein constituents distinguishing HSIL from controls by 2D HPLC, identified 31 target proteins by LTQ MS/MS. Further confirmed analysis with online software IPA^® 8.7 and ELISA assay showed APOA1 and mTOR as potential biomarkers.

Conclusions: A distinct plasma proteomic profile may be associated with HSIL of Uyghur women.     

Interfering with protein-protein interactions: Potential for cancer therapy

Genotype-specific cancer therapy promises to engender the era of personalised medicines in which rapid identification of tumour specific gene mutations coupled to rapid methods for efficacious drug identification will be applied. Aberrant signal transduction via protein-protein interactions is generally difficult to target with small molecules. However, macromolecules (macrodrugs) can be developed that interfere with protein-protein interactions by binding with high affinity and specificity to contact surfaces. Inhibitors of mutant RAS and its effector protein interactions affect cancer by attenuating aberrant RAS-dependent signal transduction and would be effective against mutant RAS in dividing cells of overt tumours and in putative cancer stem cells when they move into cell-cycle. Results with an antibody fragment blocking effector binding to RAS, illustrates that this is sufficient to prevent cancer. While macrodrugs have inherent problems of bio-distribution and delivery to target cells in patients, their efficacy suggests that efforts to achieve the goal of clinical use should be pursued.     

Enhanced Sensitivity for Selected Reaction Monitoring Mass Spectrometry-based Targeted Proteomics Using a Dual Stage Electrodynamic Ion Funnel Interface

Selected reaction monitoring mass spectrometry (SRM-MS) is playing an increasing role in quantitative proteomics and biomarker discovery studies as a method for high throughput candidate quantification and verification. Although SRM-MS offers advantages in sensitivity and quantification compared with other MS-based techniques, current SRM technologies are still challenged by detection and quantification of low abundance proteins (e.g. present at ∼10 ng/ml or lower levels in blood plasma). Here we report enhanced detection sensitivity and reproducibility for SRM-based targeted proteomics by coupling a nanospray ionization multicapillary inlet/dual electrodynamic ion funnel interface to a commercial triple quadrupole mass spectrometer. Because of the increased efficiency in ion transmission, significant enhancements in overall signal intensities and improved limits of detection were observed with the new interface compared with the original interface for SRM measurements of tryptic peptides from proteins spiked into non-depleted mouse plasma over a range of concentrations. Overall, average SRM peak intensities were increased by ∼70-fold. The average level of detection for peptides also improved by ∼10-fold with notably improved reproducibility of peptide measurements as indicated by the reduced coefficients of variance. The ability to detect proteins ranging from 40 to 80 ng/ml within mouse plasma was demonstrated for all spiked proteins without the application of front-end immunoaffinity depletion and fractionation. This significant improvement in detection sensitivity for low abundance proteins in complex matrices is expected to enhance a broad range of SRM-MS applications including targeted protein and metabolite validation.Although mass spectrometry (MS)-based proteomics is a promising high throughput technology for biomarker discovery and validation (1–5), only a handful of cancer biomarkers have been approved by the United States Food and Drug Administration for clinical use in the last decade (6, 7). Assuming that low abundance biomarkers do exist in the biofluids to be studied, the success of biomarker discovery efforts primarily depends on the sensitivity, accuracy, and robustness of the measurement technologies; the quality and size of patient cohorts and clinical samples and execution within the context of an overall difficult and expensive path to clinical application that encompasses discovery, verification, and validation stages (1, 5, 8–10). A multiplexed assay platform increasingly considered for biomarker verification is selected reaction monitoring (SRM)¹ by tandem mass spectrometry using e.g. a triple quadrupole (QqQ) mass spectrometer to attain high throughput quantitative measurements of targeted proteins in complex matrices (1, 11, 12).SRM utilizes two stages of mass filtering by selecting a specific analyte ion of interest (precursor ion) in the first stage followed by a specific fragment ion derived from the precursor (fragment ion) filter in the second stage after collision-activated dissociation. Typically, several transitions (precursor/fragment ion pairs) are monitored for greater selectivity and confidence in a targeted peptide assay, and large numbers of peptides can be monitored during a single LC-MS/MS analysis. The two-stage mass selection by individual quadrupoles enables more rapid and continuous monitoring of specific ions derived from analytes of interest such as peptides and leads to significantly enhanced detection sensitivity and quantitative accuracy compared with broad (i.e. non-targeted) LC-MS or LC-MS/MS measurements (11, 12). Both the sensitivity and selectivity of SRM-MS make this technique well suited for the targeted detection and quantification of low abundance proteins in highly complex biofluids (13–16). The precision and reproducibility of SRM-based measurements of proteins in plasma across different laboratories have recently been assessed (17).Despite its promise, present SRM measurements still do not provide sufficient sensitivity for reliable detection and quantification of low abundance proteins in biofluids (e.g. present in plasma at ∼10 ng/ml or lower levels) primarily because of factors related to high sample complexity and the large dynamic range of relative protein abundances (7, 18, 19). Given sufficient selectivity, the sensitivity achievable is generally related to the peptide MS and MS/MS signal intensities obtained. One of the key factors limiting peptide MS intensities is the significant ion losses encountered between the electrospray ionization (ESI) source and the interface to the mass spectrometer. In typical LC-ESI-MS interfaces, the mass spectrometer inlet (e.g. heated capillary followed by a skimmer) presently provides total ion utilization and ion transmission efficiencies on the order of ∼1% (20) due to a combination of limited ion sampling from the atmospheric pressure ion source into the inlet and inefficient transmission of ions entering the first reduced pressure stage of the mass spectrometer.The electrodynamic ion funnel (21), which has been developed to efficiently capture, focus, and transmit ions to the high vacuum region of the mass spectrometer, is expected to provide a large benefit to SRM analyses. The original ion funnel interfaces, which operated at a maximum of ∼5 torr, were able to enhance signal intensities for a variety of MS analyzers (22–24) by replacing the inefficient skimmer interface. Although achieving near lossless ion transmission to high vacuum, losses at the atmospheric pressure interface went unmitigated. More recently, a high pressure ion funnel interface capable of operating at a pressure of ∼30 torr was introduced (25). The higher operating pressures accommodated greater gas loads and enabled more efficient ion sampling from atmospheric pressure through a multicapillary inlet. With a dual ion funnel interface comprising a high pressure ion funnel with a heated multicapillary inlet followed by a standard ion funnel operated at 1–2 torrs, highly efficient ion sampling from atmospheric pressure to high vacuum is readily achieved.In this study, we report the enhanced sensitivity and reproducibility of SRM-based targeted proteomics measurements achieved by implementing a dual stage electrodynamic ion funnel interface that incorporates a multicapillary inlet with a triple quadrupole mass spectrometer. A series of LC-SRM-MS measurements were made using mouse plasma samples spiked with various concentrations of tryptic peptides from five standard proteins to evaluate the improvements in detection sensitivity and reproducibility attained by this modified interface relative to a standard Thermo (single capillary inlet/skimmer) interface. A ∼10-fold improvement in the limit of detection (LOD) as well as improved measurement reproducibility was achieved.     

A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer

Proteomics discovery of novel cancer serum biomarkers is hindered by the great complexity of serum, patient-to-patient variability, and triggering by the tumor of an acute-phase inflammatory reaction. This host response alters many serum protein levels in cancer patients, but these changes have low specificity as they can be triggered by diverse causes. We addressed these hurdles by utilizing a xenograft mouse model coupled with an in-depth 4-D protein profiling method to identify human proteins in the mouse serum. This strategy ensures that identified putative biomarkers are shed by the tumor, and detection of low-abundance proteins shed by the tumor is enhanced because the mouse blood volume is more than a thousand times smaller than that of a human. Using TOV-112D ovarian tumors, more than 200 human proteins were identified in the mouse serum, including novel candidate biomarkers and proteins previously reported to be elevated in either ovarian tumors or the blood of ovarian cancer patients. Subsequent quantitation of selected putative biomarkers in human sera using label-free multiple reaction monitoring (MRM) mass spectrometry (MS) showed that chloride intracellular channel 1, the mature form of cathepsin D, and peroxiredoxin 6 were elevated significantly in sera from ovarian carcinoma patients.     

Mass spectrometry-based N-glycoproteomics for cancer biomarker discovery

Glycosylation is estimated to be found in over 50% of human proteins. Aberrant protein glycosylation and alteration of glycans are closely related to many diseases. More than half of the cancer biomarkers are glycosylated-proteins, and specific glycoforms of glycosylated-proteins may serve as biomarkers for either the early detection of disease or the evaluation of therapeutic efficacy for treatment of diseases. Glycoproteomics, therefore, becomes an emerging field that can make unique contributions to the discovery of biomarkers of cancers. The recent advances in mass spectrometry (MS)-based glycoproteomics, which can analyze thousands of glycosylated-proteins in a single experiment, have shown great promise for this purpose. Herein, we described the MS-based strategies that are available for glycoproteomics, and discussed the sensitivity and high throughput in both qualitative and quantitative manners. The discovery of glycosylated-proteins as biomarkers in some representative diseases by employing glycoproteomics was also summarized.     

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.     

Fusion Peptides from Oncogenic Chimeric Proteins as Putative Specific Biomarkers of Cancer

Chromosomal translocations encoding chimeric fusion proteins constitute one of the most common mechanisms underlying oncogenic transformation in human cancer. Fusion peptides resulting from such oncogenic chimeric fusions, though unique to specific cancer subtypes, are unexplored as cancer biomarkers. Here we show, using an approach termed fusion peptide multiple reaction monitoring mass spectrometry, the direct identification of different cancer-specific fusion peptides arising from protein chimeras that are generated from the juxtaposition of heterologous genes fused by recurrent chromosomal translocations. Using fusion peptide multiple reaction monitoring mass spectrometry in a clinically relevant scenario, we demonstrate the specific, sensitive, and unambiguous detection of a specific diagnostic fusion peptide in clinical samples of anaplastic large cell lymphoma, but not in a diverse array of benign lymph nodes or other forms of primary malignant lymphomas and cancer-derived cell lines. Our studies highlight the utility of fusion peptides as cancer biomarkers and carry broad implications for the use of protein biomarkers in cancer detection and monitoring.A cancer biomarker is generally an analyte that indicates the presence or extent of a specific form of cancer. A useful cancer biomarker should reliably distinguish between benign and malignant states and, ideally, distinguish one form of cancer from other, related differential diagnoses. Many human cancers contain recurrent chromosomal translocations and chimeric gene fusions that could be exploited as cancer-specific biomarkers (1, 2). Indeed, several structural aberrations are specific and pathognomonic for distinct types of cancer (3). Moreover, as new molecular therapies increasingly target oncogenic fusion proteins, the detection and quantitation of these proteins may also provide important, direct therapeutic guidance (4–6). Although genomic techniques targeting fusion partner genes are routinely used for diagnosing cancers, fusion peptides resulting from oncogenic chimeric fusions are unexplored as biomarker candidates for cancer detection. The specificity and qualitative/binary nature (i.e. present or absent) of fusion proteins in specific tumor types make these analytes attractive candidates for cancer detection.Advances in mass spectrometry permit the direct and unbiased interrogation of proteins and peptides in complex mixtures with unambiguous identification of specific proteins (7, 8). Multiple reaction monitoring (MRM)¹ via mass spectrometry is a powerful approach for the targeted detection of biomarker candidates in a complex background (9). MRM involves the focused interrogation of specific m/z windows for the precursor analyte, as well as selected fragment ions, following MS/MS analysis. By focusing only on specific m/z windows, one increases the sensitivity of detection dramatically, and within the context of a complex mixture there is the potential for a reproducible dynamic range spanning ≥4 orders of magnitude (10, 11).Despite their enormous potential as biomarkers, fusion peptides resulting from oncogenic chimeric fusions have not been exploited for the specific and sensitive detection of cancer. Here we demonstrate the detection of unique fusion peptides that are specific for various forms of cancer. To demonstrate applicability in a clinically relevant scenario, we show the utility of our MRM-based MS approach combined with an innovative double stable isotope strategy for the identification of nucleophosmin-anaplastic lymphoma kinase (NPM-ALK) fusion peptide arising from the corresponding chimeric fusion protein for the identification of NPM-ALK-positive anaplastic large cell lymphoma (ALCL). We show the exquisite specificity and sensitivity of this fusion peptide (FP) MRM approach and the extraordinary accuracy of its application with clinical biopsy material.     

Clinical Proteomics: From Biomarker Discovery and Cell Signaling Profiles to Individualized Personal Therapy

The discovery of new highly sensitive and specific biomarkers for early disease detection and risk stratification coupled with the development of personalized “designer” therapies holds the key to future treatment of complex diseases such as cancer. Mounting evidence confirms that the low molecular weight (LMW) range of the circulatory proteome contains a rich source of information that may be able to detect early stage disease and stratify risk. Current mass spectrometry (MS) platforms can generate a rapid and high resolution portrait of the LMW proteome. Emerging novel nanotechnology strategies to amplify and harvest these LMW biomarkers in vivo or ex vivo will greatly enhance our ability to discover and characterize molecules for early disease detection, subclassification and prognostic capability of current proteomics modalities. Ultimately genetic mutations giving rise to disease are played out and manifested on a protein level, involving derangements in protein function and information flow within diseased cells and the interconnected tissue microenvironment. Newly developed highly sensitive, specific and linearly dynamic reverse phase protein microarray systems are now able to generate circuit maps of information flow through phosphoprotein networks of pure populations of microdissected tumor cells obtained from patient biopsies. We postulate that this type of enabling technology will provide the foundation for the development of individualized combinatorial therapies of molecular inhibitors to target tumor-specific deranged pathways regulating key biologic processes including proliferation, differentiation, apoptosis, immunity and metastasis. Hence future therapies will be tailored to the specific deranged molecular circuitry of an individual patient’s disease. The successful transition of these groundbreaking proteomic technologies from research tools to integrated clinical diagnostic platforms will require ongoing continued development, and optimization with rigorous standardization development and quality control procedures.     

A serum glycomics approach to breast cancer biomarkers

Because the glycosylation of proteins is known to change in tumor cells during the development of breast cancer, a glycomics approach is used here to find relevant biomarkers of breast cancer. These glycosylation changes are known to correlate with increasing tumor burden and poor prognosis. Current antibody-based immunochemical tests for cancer biomarkers of ovarian (CA125), breast (CA27.29 or CA15-3), pancreatic, gastric, colonic, and carcinoma (CA19-9) target highly glycosylated mucin proteins. However, these tests lack the specificity and sensitivity for use in early detection. This glycomics approach to find glycan biomarkers of breast cancer involves chemically cleaving oligosaccharides (glycans) from glycosylated proteins that are shed or secreted by breast cancer tumor cell lines. The resulting free glycan species are analyzed by MALDI-FT-ICR MS. Further structural analysis of the glycans can be performed in FTMS through the use of tandem mass spectrometry with infrared multiphoton dissociation. Glycan profiles were generated for each cell line and compared. These methods were then used to analyze sera obtained from a mouse model of breast cancer and a small number of serum samples obtained from human patients diagnosed with breast cancer or patients with no known history of breast cancer. In addition to the glycosylation changes detected in mice as mouse mammary tumors developed, glycosylation profiles were found to be sufficiently different to distinguish patients with cancer from those without. Although the small number of patient samples analyzed so far is inadequate to make any legitimate claims at this time, these promising but very preliminary results suggest that glycan profiles may contain distinct glycan biomarkers that may correspond to glycan "signatures of cancer."     

A dominant activating mutation in the effector region of RAS abolishes IRA2 sensitivity.

Previously described mutations in RAS genes that cause a dominant activated phenotype affect the intrinsic biochemical properties of RAS proteins, either decreasing the intrinsic GTPase or reducing the affinity for guanine nucleotides. In this report, we describe a novel activating mutation in the RAS2 gene of Saccharomyces cerevisiae that does not alter intrinsic biochemical properties of the mutant RAS2 protein. Rather, this mutation, RAS2-P41S (proline 41 to serine), which lies in the effector region of RAS, is shown to abolish the ability of the IRA2 protein to stimulate the GTPase activity of the mutant RAS protein. This mutation also modestly reduced the ability of the mutant protein to stimulate the target adenylate cyclase in an in vitro assay, although in vivo the phenotypes it induced suggest that it retains potency in stimulation of adenylate cyclase. Our results demonstrate that although the effector region of RAS appears to be important for interaction with both target effector and negative regulators of RAS, it is possible to eliminate negative regulator responsiveness and retain potency in effector stimulation.     

A large-scale assay library for targeted protein quantification in renal cell carcinoma tissues

Renal cell carcinoma (RCC) represents 2.2% of all cancer incidences; however, prognostic or predictive RCC biomarkers at protein level are largely missing. To support proteomics research of localized and metastatic RCC, we introduce a new library of targeted mass spectrometry assays for accurate protein quantification in malignant and normal kidney tissue. Aliquots of 86 initially localized RCC, 75 metastatic RCC and 17 adjacent non-cancerous fresh frozen tissue lysates were trypsin digested, pooled, and fractionated using hydrophilic chromatography. The fractions were analyzed using LC-MS/MS on QExactive HF-X mass spectrometer in data-dependent acquisition (DDA) mode. A resulting spectral library contains 77,817 peptides representing 7960 protein groups (FDR = 1%). Further, we confirm applicability of this library on four RCC datasets measured in data-independent acquisition (DIA) mode, demonstrating a specific quantification of a substantially increased part of RCC proteome, depending on LC-MS/MS instrumentation. Impact of sample specificity of the library on the results of targeted DIA data extraction was demonstrated by parallel analyses of two datasets by two pan human libraries. The new RCC specific library has potential to contribute to better understanding the RCC development at molecular level, leading to new diagnostic and therapeutic targets.