Antitumor activity of AZD0754, a dnTGFßRII-armored, STEAP2-targeted CAR-T cell therapy, in prostate cancer.

Prostate cancer is generally considered an immunologically "cold" tumor type that is insensitive to immunotherapy. Targeting surface antigens on tumors through cellular therapy can induce a potent antitumor immune response to "heat up" the tumor microenvironment. However, many antigens expressed on prostate tumor cells are also found on normal tissues, potentially causing on-target, off-tumor toxicities and a suboptimal therapeutic index. Our studies revealed that six-transmembrane epithelial antigen of prostate-2 (STEAP2) was a prevalent prostate cancer antigen that displayed high, homogeneous cell surface expression across all stages of disease with limited distal normal tissue expression, making it ideal for therapeutic targeting. A multifaceted lead generation approach enabled development of an armored STEAP2 chimeric antigen receptor T cell (CAR-T) therapeutic candidate, AZD0754. This CAR-T product was armored with a dominant-negative TGF-ß type II receptor, bolstering its activity in the TGF-ß-rich immunosuppressive environment of prostate cancer. AZD0754 demonstrated potent and specific cytotoxicity against antigen-expressing cells in vitro despite TGF-ß-rich conditions. Further, AZD0754 enforced robust, dose-dependent in vivo efficacy in STEAP2-expressing cancer cell line-derived and patient-derived xenograft mouse models, and exhibited encouraging preclinical safety. Together, these data underscore the therapeutic tractability of STEAP2 in prostate cancer as well as build confidence in the specificity, potency, and tolerability of this potentially first-in-class CAR-T therapy.

Mass spectrometry quantifies target engagement for a KRASG12C inhibitor in FFPE tumor tissue.

BACKGROUND: Quantification of drug-target binding is critical for confirming that drugs reach their intended protein targets, understanding the mechanism of action, and interpreting dose-response relationships. For covalent inhibitors, target engagement can be inferred by free target levels before and after treatment. Targeted mass spectrometry assays offer precise protein quantification in complex biological samples and have been routinely applied in pre-clinical studies to quantify target engagement in frozen tumor tissues for oncology drug development. However, frozen tissues are often not available from clinical trials so it is critical that assays are applicable to formalin-fixed, paraffin-embedded (FFPE) tissues in order to extend mass spectrometry-based target engagement studies into clinical settings. METHODS: Wild-type RAS and RASG12C was quantified in FFPE tissues by a highly optimized targeted mass spectrometry assay that couples high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) with internal standards. In a subset of samples, technical reproducibility was evaluated by analyzing consecutive tissue sections from the same tumor block and biological variation was accessed among adjacent tumor regions in the same tissue section. RESULTS: Wild-type RAS protein was measured in 32 clinical non-small cell lung cancer tumors (622-2525 amol/µg) as measured by FAIMS-PRM mass spectrometry. Tumors with a known KRASG12C mutation (n = 17) expressed a wide range of RASG12C mutant protein (127-2012 amol/µg). The variation in wild-type RAS and RASG12C measurements ranged 0-18% CV across consecutive tissue sections and 5-20% CV among adjacent tissue regions. Quantitative target engagement was then demonstrated in FFPE tissues from 2 xenograft models (MIA PaCa-2 and NCI-H2122) treated with a RASG12C inhibitor (AZD4625). CONCLUSIONS: This work illustrates the potential to expand mass spectrometry-based proteomics in preclinical and clinical oncology drug development through analysis of FFPE tumor biopsies.

The addition of FAIMS increases targeted proteomics sensitivity from FFPE tumor biopsies.

Mass spectrometry-based targeted proteomics allows objective protein quantitation of clinical biomarkers from a single section of formalin-fixed, paraffin-embedded (FFPE) tumor tissue biopsies. We combined high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) to increase assay sensitivity. The modular nature of the FAIMS source allowed direct comparison of the performance of FAIMS-PRM to PRM. Limits of quantitation were determined by spiking synthetic peptides into a human spleen matrix. In addition, 20 clinical samples were analyzed using FAIMS-PRM and the quantitation of HER2 was compared with that obtained with the Ventana immunohistochemistry assay. FAIMS-PRM improved the overall signal-to-noise ratio over that from PRM and increased assay sensitivity in FFPE tissue analysis for four (HER2, EGFR, cMET, and KRAS) of five proteins of clinical interest. FAIMS-PRM enabled sensitive quantitation of basal HER2 expression in breast cancer samples classified as HER2 negative by immunohistochemistry. Furthermore, we determined the degree of FAIMS-dependent background reduction and showed that this correlated with an improved lower limit of quantitation with FAIMS. FAIMS-PRM is anticipated to benefit clinical trials in which multiple biomarker questions must be addressed and the availability of tumor biopsy samples is limited.

Global Extraction from Parallel Reaction Monitoring to Quantify Background Peptides for Improved Normalization and Quality Control in Targeted Proteomics.

Mass spectrometry-based targeted proteomics employs heavy isotope-labeled proteins or peptides as standards to improve accuracy and precision. The input sample amount is often determined by the total quantity of endogenous proteins or peptides, as defined by spectrophotometric assays, before the heavy-isotope standards are spiked into the samples. Errors in spectrophotometric measurements, which may be due to low sensitivity or chemical or biological interference, have a direct impact on the quantitative mass spectrometry results. Currently used targeted proteomics workflows cannot identify or correct deviations that arise from differences in the input sample amount. We have developed a workflow, global extraction from parallel reaction monitoring (PRM), to identify and quantify thousands of background peptides that are inherently acquired by PRM experiments. These background peptides were used to identify differences in the input sample amount and to reduce this variance by intensity-based, post-acquisition normalization. This approach was then applied to a xenograft study to improve the quantification of human proteins in the presence of mouse tissue contamination. In addition, these background peptides also provided a direct source of quality control metrics related to sample handling and preparation.

High throughput profiling of undifferentiated pleomorphic sarcomas identifies two main subgroups with distinct immune profile, clinical outcome and sensitivity to targeted therapies.

BACKGROUND: Undifferentiated pleomorphic sarcoma (UPS) is the most frequent, aggressive and less-characterized sarcoma subtype. This study aims to assess UPS molecular characteristics and identify specific therapeutic targets. METHODS: High-throughput technologies encompassing immunohistochemistry, RNA-sequencing, whole exome-sequencing, mass spectrometry, as well as radiomics were used to characterize three independent cohorts of 110, 25 and 41 UPS selected after histological review performed by an expert pathologist. Correlations were made with clinical outcome. Cell lines and xenografts were derived from human samples for functional experiments. FINDINGS: CD8 positive cell density was independently associated with metastatic behavior and prognosis. RNA-sequencing identified two main groups: the group A, enriched in genes involved in development and stemness, including FGFR2, and the group B, strongly enriched in genes involved in immunity. Immune infiltrate patterns on tumor samples were highly predictive of gene expression classification, leading to call the group B 'immune-high' and the group A 'immune-low'. This molecular classification and its prognostic impact were confirmed on an independent cohort of UPS from TCGA. Copy numbers alterations were significantly more frequent in immune-low UPS. Proteomic analysis identified two main proteomic groups that highly correlated with the two main transcriptomic groups. A set of nine radiomic features from conventional MRI sequences provided the basis for a radiomics signature that could select immune-high UPS on their pre-therapeutic imaging. Finally, in vitro and in vivo anti-tumor activity of FGFR inhibitor JNJ-42756493 was selectively shown in cell lines and patient-derived xenograft models derived from immune-low UPS. INTERPRETATION: Two main disease entities of UPS, with distinct immune phenotypes, prognosis, molecular features and MRI textures, as well as differential sensitivity to specific anticancer agents were identified. Immune-high UPS may be the best candidates for immune checkpoint inhibitors, whereas this study provides rational for assessing FGFR inhibition in immune-low UPS. FUNDING: This work was partly founded by a grant from La Ligue.

Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection.

Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients' survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening.

Data-Independent Acquisition Mass Spectrometry To Quantify Protein Levels in FFPE Tumor Biopsies for Molecular Diagnostics.

Mass spectrometry-based protein quantitation is currently used to measure therapeutically relevant protein biomarkers in CAP/CLIA setting to predict likely responses of known therapies. Selected reaction monitoring (SRM) is the method of choice due to its outstanding analytical performance. However, data-independent acquisition (DIA) is now emerging as a proteome-scale clinical assay. We evaluated the ability of DIA to profile the patient-specific proteomes of sample-limited tumor biopsies and to quantify proteins of interest in a targeted fashion using formalin-fixed, paraffin-embedded (FFPE) tumor biopsies ( n = 12) selected from our clinical laboratory. DIA analysis on the tumor biopsies provided 3713 quantifiable proteins including actionable biomarkers currently in clinical use, successfully separated two gastric cancers from colorectal cancer specimen solely on the basis of global proteomic profiles, and identified subtype-specific proteins with prognostic or diagnostic value. We demonstrate the potential use of DIA-based quantitation to inform therapeutic decision-making using TUBB3, for which clinical cutoff expression levels have been established by SRM. Comparative analysis of DIA-based proteomic profiles and mRNA expression levels found positively and negatively correlated protein-gene pairs, a finding consistent with previously reported results from fresh-frozen tumor tissues.

A new ALK isoform transported by extracellular vesicles confers drug resistance to melanoma cells.

BACKGROUND: Drug resistance remains an unsolved clinical issue in oncology. Despite promising initial responses obtained with BRAF and MEK kinase inhibitors, resistance to treatment develops within months in virtually all melanoma patients. METHODS: Microarray analyses were performed in BRAF inhibitor-sensitive and resistant cell lines to identify changes in the transcriptome that might play a role in resistance. siRNA approaches and kinase inhibitors were used to assess the involvement of the identified Anaplastic Lymphoma Kinase (ALK) in drug resistance. The capability of extracellular vesicles (EVs) to transfer drug resistant properties was investigated in co-culture assays. RESULTS: Here, we report a new mechanism of acquired drug resistance involving the activation of a novel truncated form of ALK. Knock down or inhibition of ALK re-sensitised resistant cells to BRAF inhibition and induced apoptosis. Interestingly, truncated ALK was also secreted into EVs and we show that EVs were the vehicle for transferring drug resistance. CONCLUSIONS: To our knowledge, this is the first report demonstrating the functional involvement of EVs in melanoma drug resistance by transporting a truncated but functional form of ALK, able to activate the MAPK signalling pathway in target cells. Combined inhibition of ALK and BRAF dramatically reduced tumour growth in vivo. These findings make ALK a promising clinical target in melanoma patients.

Identification of beta-arrestin-1 as a diagnostic biomarker in lung cancer.

BACKGROUND: Distinguishing lung adenocarcinoma (ADC) from squamous cell carcinoma (SCC) has a tremendous therapeutic implication. Sometimes, the commonly used immunohistochemistry (IHC) markers fail to discriminate between them, urging for the identification of new diagnostic biomarkers. METHODS: We performed IHC on tissue microarrays from two cohorts of lung cancer patients to analyse the expression of beta-arrestin-1, beta-arrestin-2 and clinically used diagnostic markers in ADC and SCC samples. Logistic regression models were applied for tumour subtype prediction. Parallel reaction monitoring (PRM)-based mass spectrometry was used to quantify beta-arrestin-1 in plasma from cancer patients and healthy donors. RESULTS: Beta-arrestin-1 expression was significantly higher in ADC versus SCC samples. Beta-arrestin-1 displayed high sensitivity, specificity and negative predictive value. Its usefulness in an IHC panel was also shown. Plasma beta-arrestin-1 levels were considerably higher in lung cancer patients than in healthy donors and were higher in patients who later experienced a progressive disease than in patients showing complete/partial response following EGFR inhibitor therapy. CONCLUSIONS: Our data identify beta-arrestin-1 as a diagnostic marker to differentiate ADC from SCC and indicate its potential as a plasma biomarker for non-invasive diagnosis of lung cancer. Its utility to predict response to EGFR inhibitors is yet to be confirmed.

Targeted data-independent acquisition for mass spectrometric detection of RAS mutations in formalin-fixed, paraffin-embedded tumor biopsies.

Genomic testing for KRAS and NRAS mutations in clinical biopsies of various cancers is routinely performed to predict futility of anti-epidermal growth factor receptor (anti-EGFR) therapies. We hypothesized that RAS mutations could be detected and quantified at the protein level for diagnostic purposes using data-independent acquisition (DIA)-based mass spectrometry in formalin-fixed, paraffin-embedded (FFPE) tumor samples. We developed a targeted DIA assay that surveys the specific mass range of all possible peptides harboring activating mutations in KRAS exon 2. When the assay was applied to tumor samples with known KRAS or NRAS mutations (G12A, G12D, G12V, and G13D), RAS-mutant and wild-type peptides were successfully detected in 11 of 13 biopsy samples. Mutation statuses obtained by DIA were concordant with those obtained by DNA sequencing, and yields of mutant peptide (mutant peptide/[mutant + wild-type peptides]) exhibited linear correlation with yields of RAS-mutant mRNA. When applied to biopsy samples with failed DNA testing results, the DIA assay identified an additional RAS-mutated sample. SIGNIFICANCE: Proteomic detection of RAS mutations by DIA in tumor biopsies can provide solid evidence of mutant RAS protein regardless of the mutation types and sites in exon 2. This robust method could rescue samples that fail genomic testing due to insufficient tumor tissue or lack of sequenceable DNA. It can be used to explore the relationship between protein expression level of mutant RAS and therapeutic outcome.

Cell-free DNA and next-generation sequencing in the service of personalized medicine for lung cancer.

Personalized medicine has emerged as the future of cancer care to ensure that patients receive individualized treatment specific to their needs. In order to provide such care, molecular techniques that enable oncologists to diagnose, treat, and monitor tumors are necessary. In the field of lung cancer, cell free DNA (cfDNA) shows great potential as a less invasive liquid biopsy technique, and next-generation sequencing (NGS) is a promising tool for analysis of tumor mutations. In this review, we outline the evolution of cfDNA and NGS and discuss the progress of using them in a clinical setting for patients with lung cancer. We also present an analysis of the role of cfDNA as a liquid biopsy technique and NGS as an analytical tool in studying EGFR and MET, two frequently mutated genes in lung cancer. Ultimately, we hope that using cfDNA and NGS for cancer diagnosis and treatment will become standard for patients with lung cancer and across the field of oncology.

Biotechnology Based Process for Production of a Disulfide-Bridged Peptide.

A disulfide-bridged peptide drug development candidate contained two oligopeptide chains with 11 and 12 natural amino acids joined by a disulfide bond at the N-terminal end. An efficient biotechnology based process for the production of the disulfide-bridged peptide was developed. Initially, the two individual oligopeptide chains were prepared separately by designing different fusion proteins and expressing them in recombinant E. coli. Enzymatic or chemical cleavage of the two fusion proteins provided the two individual oligopeptide chains which could be conjugated via disulfide bond by conventional chemical reaction to the disulfide-bridged peptide. A novel heterodimeric system to bring the two oligopeptide chains closer and induce disulfide bond formation was designed by taking advantage of the self-assembly of a leucine zipper system. The heterodimeric approach involved designing fusion proteins with the acidic and basic components of the leucine zipper, additional amino acids to optimize interaction between the individual chains, specific cleavage sites, specific tag to ensure separation, and two individual oligopeptide chains. Computer modeling was used to identify the nature and number of amino acid residue to be inserted between the leucine zipper and oligopeptides for optimum interaction. Cloning and expression in rec E. coli, fermentation, followed by cell disruption resulted in the formation of heterodimeric protein with the interchain disulfide bond. Separation of the desired heterodimeric protein, followed by specific cleavage at methionine by cyanogen bromide provided the disulfide-bridged peptide.

Quantification of SAA1 and SAA2 in lung cancer plasma using the isotype-specific PRM assays.

The quantification of plasma proteins using the high resolution and accurate mass (HR/AM)-based parallel reaction monitoring (PRM) method provides an immediate benefit over the conventional SRM-based method in terms of selectivity. In this study, multiplexed PRM assays were developed to analyze isotypes of serum amyloid A (SAA) proteins in human plasma with a focus on SAA1 and SAA2. Elevated plasma levels of these proteins in patients diagnosed with lung cancer have been reported in previous studies. Since SAA1 and SAA2 are highly homologous, the available immunoassays tend to overestimate their concentrations due to cross-reactivity. On the other hand, when mass spectrometry (MS)-based assays are used, the presence of the several allelic variants may result in a problem of underestimation. In the present study, eight peptides that represent the target proteins at three different levels: isotype-specific (SAA1α,  SAA 1ß,  SAA1γ,  SAA2α,  SAA2ß), protein-specific (SAA1 or SAA2), and pan SAA (SAA1 and SAA2) were chosen to differentiate SAAs in lung cancer plasma samples using a panel of PRM assays. The measurement of specific isotypes, leveraging the analytical performance of PRM, allowed to quantify the allelic variants of both target proteins. The isotypes detected were corroborated with the genetic information obtained from the same samples. The combination of SAA2α and SAA2ß assays representing the total SAA2 concentration demonstrated a superior analytical outcome than the previously used assay on the common peptide when applied to the detection of lung cancer.

Exosomes released by chronic lymphocytic leukemia cells induce the transition of stromal cells into cancer-associated fibroblasts.

Exosomes derived from solid tumor cells are involved in immune suppression, angiogenesis, and metastasis, but the role of leukemia-derived exosomes has been less investigated. The pathogenesis of chronic lymphocytic leukemia (CLL) is stringently associated with a tumor-supportive microenvironment and a dysfunctional immune system. Here, we explore the role of CLL-derived exosomes in the cellular and molecular mechanisms by which malignant cells create this favorable surrounding. We show that CLL-derived exosomes are actively incorporated by endothelial and mesenchymal stem cells ex vivo and in vivo and that the transfer of exosomal protein and microRNA induces an inflammatory phenotype in the target cells, which resembles the phenotype of cancer-associated fibroblasts (CAFs). As a result, stromal cells show enhanced proliferation, migration, and secretion of inflammatory cytokines, contributing to a tumor-supportive microenvironment. Exosome uptake by endothelial cells increased angiogenesis ex vivo and in vivo, and coinjection of CLL-derived exosomes and CLL cells promoted tumor growth in immunodeficient mice. Finally, we detected α-smooth actin-positive stromal cells in lymph nodes of CLL patients. These findings demonstrate that CLL-derived exosomes actively promote disease progression by modulating several functions of surrounding stromal cells that acquire features of cancer-associated fibroblasts.

Screening protein isoforms predictive for cancer using immunoaffinity capture and fast LC-MS in PRM mode.

PURPOSE: We report an immunocapture strategy to extract proteins known to harbor driver mutations for a defined cancer type before the simultaneous assessment of their mutational status by MS. Such a method bypasses the sensitivity and selectivity issues encountered during the analysis of unfractionated complex biological samples. EXPERIMENTAL DESIGN: Fast LC separations using short nanobore columns hyphenated with a high-resolution quadrupole-orbitrap mass spectrometer have been devised to take advantage of fast MS cycle times in conjunction with sharp chromatographic peak widths to accelerate the sample analysis throughput. Such an analytical platform is well suited to analyze simple protein mixtures obtained after immunoaffinity enrichment. RESULTS: After establishing the technical performance of the platform, the method was applied to the quantitative profiling of cellular Ras and EGFR protein isoforms, as well as serum amyloid A isoforms in plasma. CONCLUSIONS AND CLINICAL RELEVANCE: Immunoaffinity purification combined with fast LC-MS detection for the detection of driver mutations in tissue and tumor biomarkers in plasma samples can assist clinicians to select an optimal therapeutic intervention for patients.

Verification of the biomarker candidates for non-small-cell lung cancer using a targeted proteomics approach.

Lung cancer, with its high metastatic potential and high mortality rate, is the worldwide leading cause of cancer-related deaths. High-throughput "omics"-based platforms have accelerated the discovery of biomarkers for lung cancer, and the resulting candidates are to be evaluated for their diagnostic potential as noninvasive biomarkers. The evaluation of the biomarker candidates involves the quantitative measurement of large numbers of proteins in bodily fluids using advanced mass spectrometric techniques. In this study, a robust pipeline based on targeted proteomics was developed for biomarker verification in plasma samples and applied to verifying lung cancer biomarker candidates. Highly multiplexed liquid chromatrography-selected reaction monitoring (LC-SRM) assays for 95 potential tumor markers for non-small-cell lung cancer (NSCLC) were generated to screen plasma samples obtained from 72, early to late stage, patients. A total of 17 proteins were verified as potent tumor markers detectable in plasma and, where available, verified by enzyme-linked immunosorbent assays (ELISAs). A novel plasma-based biomarker, zyxin, fulfilled the criteria for a potential early diagnostic marker for NSCLC.

Targeted proteomics strategy applied to biomarker evaluation.

The evaluation of biomarker candidates, involving quantitative measurement of a large number of proteins in bodily fluids, remains the main obstruction in the development of a biomarker validation pipeline. Although immunoassays are commonly used, high-throughput and multiplex-capable methods are required for expediting the evaluation process. MS-based approaches employing targeted proteomic strategies provide not only a sensitive, but in addition a precise quantification tool, which is versatile, systematic, and scalable. Its capability of multiplexing hundreds of targets facilitate a cost-effective and rapid evaluation and is especially useful during the early stage of the process where a large list of candidate biomarkers must be triaged before entering validation studies. The robustness requirement for the methods also mandates a high degree of selectivity to analyze complex clinical samples. Improvement in the selectivity of LC-MS methods has been achieved by adopting high-resolution and high-accuracy mass analyzers to perform quantitative analyses with a novel method called parallel reaction monitoring. This article discusses the design and performance of biomarker evaluation studies using targeted proteomics strategies and the implementation of recent technology developments.

Mass spectrometry-based detection and quantification of plasma glycoproteins using selective reaction monitoring.

Mass spectrometry-based targeted proteomics is a rapidly expanding method for quantifying proteins in complex clinical samples such as plasma. In conjunction with the stable isotope dilution method, selected reaction monitoring (SRM) assays provide unparalleled sensitivity and selectivity for detection and quantification. A crucial factor for robust SRM assays is the reduction of interference by lowering the background. This can be achieved by the selective isolation of a subproteome, such as N-glycosylated proteins, from the original sample. The present protocol includes the development and optimization of SRM assays associated with each peptide of interest and the qualification of assays in the biological matrix to establish the limits of detection and quantification. The protocol also describes the enrichment of formerly N-glycosylated peptides relying on periodate oxidation of glycan moieties attached to the proteins, their immobilization on solid supports through hydrazide chemistry, proteolysis and enzymatic release of the formerly N-glycosylated peptides.

Structural mass spectrometry in protein therapeutics discovery.

The protein therapeutics market is one of the highest growing segments of the pharmaceutical industry with an estimated global market value of $77 billion by 2011 (Global Protein Therapeutics Market report by RNCOS: Delhi, India, 2009). This growth has been fueled by several advantages that protein drugs can offer such as higher specificity, reduced side effects, and faster development time compared to small molecule drugs. Major pharmaceutical companies are strategically shifting gears toward protein therapeutics and gradually increasing the biologics portion of their pipelines. Consequently, in the present pharmaceutical industry, there is a rapid growth in the number and types of protein structural mass spectrometry analyses, particularly during the discovery phase where an abundance of new drug candidates are being investigated. This perspective article discusses the role of protein structural mass spectrometry during the discovery of protein therapeutics with focus on recombinant protein production quality control and structural biology applications. The current challenges in technologies associated with this field and the analytical prospects for the future direction will be also discussed.

Reference map for liquid chromatography-mass spectrometry-based quantitative proteomics.

The accurate mass and time (AMT) tag strategy has been recognized as a powerful tool for high-throughput analysis in liquid chromatography-mass spectrometry (LC-MS)-based proteomics. Due to the complexity of the human proteome, this strategy requires highly accurate mass measurements for confident identifications. We have developed a method of building a reference map that allows relaxed criteria for mass errors yet delivers high confidence for peptide identifications. The samples used for generating the peptide database were produced by collecting cysteine-containing peptides from T47D cells and then fractionating the peptides using strong cationic exchange chromatography (SCX). LC-tandem mass spectrometry (MS/MS) data from the SCX fractions were combined to create a comprehensive reference map. After the reference map was built, it was possible to skip the SCX step in further proteomic analyses. We found that the reference-driven identification increases the overall throughput and proteomic coverage by identifying peptides with low intensity or complex interference. The use of the reference map also facilitates the quantitation process by allowing extraction of peptide intensities of interest and incorporating models of theoretical isotope distribution.