Quantification of beta-catenin signaling components in colon cancer cell lines, tissue sections, and microdissected tumor cells using reaction monitoring mass spectrometry

Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

Targeted mass spectrometry-based assays enable multiplex quantification of receptor tyrosine kinase, MAP Kinase, and AKT signaling

SUMMARY

A primary goal of the US National Cancer Institute's Ras initiative at the Frederick National Laboratory for Cancer Research is to develop methods to quantify RAS signaling to facilitate development of novel cancer therapeutics. We use targeted proteomics technologies to develop a community resource consisting of 256 validated multiple reaction monitoring (MRM)-based, multiplexed assays for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. As proof of concept, we quantify the response of melanoma (A375 and SK-MEL-2) and colorectal cancer (HCT-116 and HT-29) cell lines to BRAF inhibition by PLX-4720. These assays replace over 60 Western blots with quantitative mass spectrometry-based assays of high molecular specificity and quantitative precision, showing the value of these methods for pharmacodynamic measurements and mechanism of action studies. Methods, fit-for-purpose validation, and results are publicly available as a resource for the community at assays.cancer.gov.

MOTIVATION

A lack of quantitative, multiplexable assays for phosphosignaling limits comprehensive investigation of aberrant signaling in cancer and evaluation of novel treatments. To alleviate this limitation, we sought to develop assays using targeted mass spectrometry for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. The resulting assays provide a resource for replacing over 60 Western blots in examining cancer signaling and tumor biology with high molecular specificity and quantitative rigor.

Circulating Wnt Ligands Activate the Wnt Signaling Pathway in Mature Erythrocytes

[Figure: see text].

MicroRNA Expression and Correlation with mRNA Levels of Colorectal Cancer-Related Genes

INTRODUCTION

MicroRNAs (miRNAs), as a family of non-coding RNAs, have opened a new window in cancer biology and transcriptome. It has been revealed that miRNAs post-transcriptionally regulate the gene expression and involve in colorectal cancer (CRC) development and progression. Our aim was to examine the differential expression of miRNAs in a CRC and to correlate their expression levels with mRNA levels of CRC-related genes (K-ras, APC, p53).

MATERIALS AND METHODS

Seventy-two colorectal tumor tissues from patients with newly diagnosed CRC and 72 matched normal adjacent tissues were analyzed. Relative expression of seven CRC-related miRNAs (miR-21, miR-31, miR-20a, miR-133b, and miR-145, miR-135b and let-7g) and three CRC-related genes (K-ras, APC, p53) was detected using the SYBR Green quantitative real-time PCR technique. The correlation between gene expression levels and clinicopathological features was evaluated.

RESULTS

Our results showed a significant difference between the two groups for the expression level of miR-21, miR-31, miR-145, and miR-20a (P < 0.001). Also, a significant difference between the two groups for the expression level of K-ras was found (P < 0.001). Further analysis revealed an inverse significant correlation between miR-145 and K-ras (R² = 0.662, P < 0.001), while a positive correlation was observed between miR-21 and K-ras (R² = 0.732, P < 0.001).

CONCLUSION

Dysregulation of miRNAs and correlation with molecular signaling pathways designated a biological role for miRNAs in various cellular mechanisms underlying CRC. On the other hand, the pattern of miRNAs expression and its correlation with transcriptional status are helpful to discovery biomarkers and design therapeutics for CRC.

Computer-aided drug repurposing for cancer therapy: Approaches and opportunities to challenge anticancer targets

Despite huge efforts made in academic and pharmaceutical worldwide research, current anticancer therapies achieve effective treatment in a limited number of neoplasia cases only. Oncology terms such as big killers - to identify tumours with yet a high mortality rate - or undruggable cancer targets, and chemoresistance, represent the current therapeutic debacle of cancer treatments. In addition, metastases, tumour microenvironments, tumour heterogeneity, metabolic adaptations, and immunotherapy resistance are essential features controlling tumour response to therapies, but still, lack effective therapeutics or modulators. In this scenario, where the pharmaceutical productivity and drug efficacy in oncology seem to have reached a plateau, the so-called drug repurposing - i.e. the use of old drugs, already in clinical use, for a different therapeutic indication - is an appealing strategy to improve cancer therapy. Opportunities for drug repurposing are often based on occasional observations or on time-consuming pre-clinical drug screenings that are often not hypothesis-driven. In contrast, in-silico drug repurposing is an emerging, hypothesis-driven approach that takes advantage of the use of big-data. Indeed, the extensive use of -omics technologies, improved data storage, data meaning, machine learning algorithms, and computational modeling all offer unprecedented knowledge of the biological mechanisms of cancers and drugs' modes of action, providing extensive availability for both disease-related data and drugs-related data. This offers the opportunity to generate, with time and cost-effective approaches, computational drug networks to predict, in-silico, the efficacy of approved drugs against relevant cancer targets, as well as to select better responder patients or disease' biomarkers. Here, we will review selected disease-related data together with computational tools to be exploited for the in-silico repurposing of drugs against validated targets in cancer therapies, focusing on the oncogenic signaling pathways activation in cancer. We will discuss how in-silico drug repurposing has the promise to shortly improve our arsenal of anticancer drugs and, likely, overcome certain limitations of modern cancer therapies against old and new therapeutic targets in oncology.

The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics"

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

The promise of targeted proteomics for quantitative network biology

Proteomics is a powerful tool for obtaining information on a large number of proteins with regard to their expression levels, interactions with other molecules, and posttranslational modifications. Whereas nontargeted, discovery proteomics uncovers differences in the proteomic landscape under different conditions, targeted proteomics has been developed to overcome the limitations of this approach with regard to quantitation. In addition to technical advances in instruments and informatics tools, the advent of the synthetic proteome composed of synthetic peptides or recombinant proteins has advanced the adoption of targeted proteomics across a wide range of research fields. Targeted proteomics can now be applied to measurement of the dynamics of any proteins of interest under a variety of conditions as well as to estimation of the absolute abundance or stoichiometry of proteins in a given network. Multiplexed targeted proteomics assays of high reproducibility and accuracy can provide insight at the quantitative level into entire networks that govern biological phenomena or diseases. Such assays will establish a new paradigm for data-driven science.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Quantification of Breast Cancer Protein Biomarkers at Different Expression Levels in Human Tumors

Liquid chromatography-selected reaction monitoring (LC-SRM) mass spectrometry has developed into a versatile tool for quantification of proteins with a wide range of applications in basic science, translational research, and clinical patient assessment. This strategy uniquely complements traditional pathology approaches, like hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC). The multiplexing capabilities offered by mass spectrometry are currently unmatched by other techniques. However, quantification of biomarkers in tissue specimens without the other data obtained from H&E-stained slides or IHC, including tumor cellularity or percentage of positively stained cells inter alia, may not provide as much information that is needed to fully understand tumor biology or properly assess the patient. Therefore, additional characterization of the tissue proteome is needed, which in turn requires the ability to assess protein markers across a wide range of expression levels from a single sample. This protocol provides an example of multiplexed analysis in breast tumor tissue quantifying specific biomarkers, specifically estrogen receptor, progesterone receptor, and the HER2 receptor tyrosine kinase, in combination with other proteins that can report on tissue content and other aspects of tumor biology.

Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer

Recent developments in instrumentation and bioinformatics have led to new quantitative mass spectrometry platforms including LC-MS/MS with data-independent acquisition (DIA) and targeted analysis using parallel reaction monitoring mass spectrometry (LC-PRM), which provide alternatives to well-established methods, such as LC-MS/MS with data-dependent acquisition (DDA) and targeted analysis using multiple reaction monitoring mass spectrometry (LC-MRM). These tools have been used to identify signaling perturbations in lung cancers and other malignancies, supporting the development of effective kinase inhibitors and, more recently, providing insights into therapeutic resistance mechanisms and drug repurposing opportunities. However, detection of kinases in biological matrices can be challenging; therefore, activity-based protein profiling enrichment of ATP-utilizing proteins was selected as a test case for exploring the limits of detection of low-abundance analytes in complex biological samples. To examine the impact of different MS acquisition platforms, quantification of kinase ATP uptake following kinase inhibitor treatment was analyzed by four different methods: LC-MS/MS with DDA and DIA, LC-MRM, and LC-PRM. For discovery data sets, DIA increased the number of identified kinases by 21% and reduced missingness when compared with DDA. In this context, MRM and PRM were most effective at identifying global kinome responses to inhibitor treatment, highlighting the value of a priori target identification and manual evaluation of quantitative proteomics data sets. We compare results for a selected set of desthiobiotinylated peptides from PRM, MRM, and DIA and identify considerations for selecting a quantification method and postprocessing steps that should be used for each data acquisition strategy.

Quantitative proteomics of breast tumors: Tissue quality assessment to clinical biomarkers

Liquid chromatography-selected reaction monitoring mass spectrometry (LC-SRM) is not only a proven tool for clinical chemistry, but also a versatile method to enhance the capability to quantify biomarkers for tumor biology research. As the treatment of cancer continues to evolve, the ability to assess multiple biomarkers to assign cancer phenotypes based on the genetic background and the signaling of the individual tumor becomes paramount to our ability to treat the patient. In breast cancer, the American Society of Clinical Oncology has defined biomarkers for patient assessment to guide selection of therapy: estrogen receptor, progesterone receptor, and the HER2/Neu receptor tyrosine kinase; therefore, these proteins were selected for LC-SRM assay development. Detailed molecular characterization of these proteins is necessary for patient treatment, so expression and phosphorylation assays have been developed and applied. In addition, other LC-SRM assays were developed to further evaluate tumor biology (e.g. Ki-67 for proliferation and vimentin for tumor aggressiveness related to the epithelial-to-mesenchymal transition). These measurements combined with biomarkers for tissue quality and histological content are implemented in a three-tier multiplexed assay platform, which is translated from cell line models into frozen tumor tissues banked from breast cancer patients.

Quantitative Mass Spectrometry Analysis of PD-L1 Protein Expression, N-glycosylation and Expression Stoichiometry with PD-1 and PD-L2 in Human Melanoma

Quantitative assessment of key proteins that control the tumor-immune interface is one of the most formidable analytical challenges in immunotherapeutics. We developed a targeted MS platform to quantify programmed cell death-1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2) at fmol/microgram protein levels in formalin fixed, paraffin-embedded sections from 22 human melanomas. PD-L1 abundance ranged 50-fold, from ∼0.03 to 1.5 fmol/microgram protein and the parallel reaction monitoring (PRM) data were largely concordant with total PD-L1-positive cell content, as analyzed by immunohistochemistry (IHC) with the E1L3N antibody. PD-1 was measured at levels up to 20-fold lower than PD-L1, but the abundances were not significantly correlated (r² = 0.062, p = 0.264). PD-1 abundance was weakly correlated (r² = 0.3057, p = 0.009) with the fraction of lymphocytes and histiocytes in sections. PD-L2 was measured from 0.03 to 1.90 fmol/microgram protein and the ratio of PD-L2 to PD-L1 abundance ranged from 0.03 to 2.58. In 10 samples, PD-L2 was present at more than half the level of PD-L1, which suggests that PD-L2, a higher affinity PD-1 ligand, is sufficiently abundant to contribute to T-cell downregulation. We also identified five branched mannose and N-acetylglucosamine glycans at PD-L1 position N192 in all 22 samples. Extent of PD-L1 glycan modification varied by ∼10-fold and the melanoma with the highest PD-L1 protein abundance and most abundant glycan modification yielded a very low PD-L1 IHC estimate, thus suggesting that N-glycosylation may affect IHC measurement and PD-L1 function. Additional PRM analyses quantified immune checkpoint/co-regulator proteins LAG3, IDO1, TIM-3, VISTA, and CD40, which all displayed distinct expression independent of PD-1, PD-L1, and PD-L2. Targeted MS can provide a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics.

Determination of Rate-Limiting Factor for Formation of Beta-Catenin Destruction Complexes Using Absolute Protein Quantification

Wnt/β-catenin signaling plays important roles in both ontogenesis and development. In the absence of a Wnt stimulus, β-catenin is degraded by a multiprotein "destruction complex" that includes Axin, APC, GSK3B, and FBXW11. Although the key molecules required for transducing Wnt signals have been identified, a quantitative understanding of this pathway has been lacking. Here, we calculated the absolute number of β-catenin destruction complexes by absolute protein quantification using LC-MS/MS. Similar amounts of destruction complex-constituting proteins and β-catenin interacted, and the number of destruction complexes was calculated to be about 1468 molecules/cell. We demonstrated that the calculated number of destruction complexes was valid for control of the β-catenin destruction rate under steady-state conditions. Interestingly, APC had the minimum expression level among the destruction complex components at about 2233 molecules/cell, and this number approximately corresponded to the calculated number of destruction complexes. Decreased APC expression by siRNA transfection decreased the number of destruction complexes, resulting in β-catenin accumulation and stimulation of the transcriptional activity of T-cell factor. Taken together, our results suggest that the amount of APC expression is the rate-limiting factor for the constitution of β-catenin destruction complexes.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Oncogenic KRAS and BRAF Drive Metabolic Reprogramming in Colorectal Cancer

Metabolic reprogramming, in which altered utilization of glucose and glutamine supports rapid growth, is a hallmark of most cancers. Mutations in the oncogenes KRAS and BRAF drive metabolic reprogramming through enhanced glucose uptake, but the broader impact of these mutations on pathways of carbon metabolism is unknown. Global shotgun proteomic analysis of isogenic DLD-1 and RKO colon cancer cell lines expressing mutant and wild type KRAS or BRAF, respectively, failed to identify significant differences (at least 2-fold) in metabolic protein abundance. However, a multiplexed parallel reaction monitoring (PRM) strategy targeting 73 metabolic proteins identified significant protein abundance increases of 1.25-twofold in glycolysis, the nonoxidative pentose phosphate pathway, glutamine metabolism, and the phosphoserine biosynthetic pathway in cells with KRAS G13D mutations or BRAF V600E mutations. These alterations corresponded to mutant KRAS and BRAF-dependent increases in glucose uptake and lactate production. Metabolic reprogramming and glucose conversion to lactate in RKO cells were proportional to levels of BRAF V600E protein. In DLD-1 cells, these effects were independent of the ratio of KRAS G13D to KRAS wild type protein. A study of 8 KRAS wild type and 8 KRAS mutant human colon tumors confirmed the association of increased expression of glycolytic and glutamine metabolic proteins with KRAS mutant status. Metabolic reprogramming is driven largely by modest (<2-fold) alterations in protein expression, which are not readily detected by the global profiling methods most commonly employed in proteomic studies. The results indicate the superiority of more precise, multiplexed, pathway-targeted analyses to study functional proteome systems. Data are available through MassIVE Accession MSV000079486 at ftp://MSV000079486@massive.ucsd.edu.

Inhibition of PI3K/Akt/mTOR signaling in PI3KR2-overexpressing colon cancer stem cells reduces tumor growth due to apoptosis

In sporadic colon cancer, colon cancer stem cells (CCSCs) initiate tumorigenesis and may contribute to late disease recurrences and metastases. We previously showed that aldehyde dehydrogenase (ALDH) activity (as indicated by the ALDEFLUOR^® assay) is an effective marker for highly enriching CCSCs for further evaluation. Here, we used comparative transcriptome and proteome approaches to identify signaling pathways overrepresented in the CCSC population. We found overexpression of several components of the phosphoinositide 3-kinase (PI3K)/Akt/mechanistic target of rapamycin (mTOR) signaling pathway, including PI3KR2, a regulatory subunit of PI3K. LY294002, a PI3K inhibitor, defined the contribution of the PI3K/Akt/mTOR signaling pathway in CCSCs. LY294002-treated CCSCs showed decreases in proliferation, sphere formation and self-renewal, in phosphorylation-dependent activation of Akt, and in expression of cyclin D1. Inhibition of PI3K in vivo reduced tumorigenicity, increased detection of cleaved caspase 3, an indicator of apoptosis, and elevated expression of the inflammatory chemokine, CXCL8. Collectively, these results indicate that PI3K/Akt/mTOR signaling controls CCSC proliferation and CCSC survival, and suggests that it would be useful to develop therapeutic agents that target this signaling pathway.

Comparison of commercial nanoliquid chromatography columns for fast, targeted mass spectrometry-based proteomics

AIM

We compared four commonly used, commercially available reverse phase nanoLC columns for identification/determination of Wnt/β-catenin-related pathway proteins.

MATERIALS & METHODS

The columns were: Chromolith® (silica monolith; Merke Millipore, MA, USA), PepMap™ (porous particles; Thermo Fisher Scientific, MA, USA), Accucore™ (solid core particles; Thermo Fisher Scientific) and PepSwift™ (organic monolith; Thermo Fisher Scientific).

RESULTS

The peak capacity of the columns varied from 100 (Pepswift) to 190 (Accucore) (for 30 min gradients). All columns enabled identification/detection of GSK3β and β-catenin in the complex samples. However, even the columns with higher peak capacities could not enable detection of the somewhat less abundant proteins AXIN2 and TNKS2. The monoliths were more prone to retention time instability when sample complexity increased.

CONCLUSION

We find that commercial nanoLC columns, although featuring different morphologies and peak capacities, provided surprisingly few practical differences for relatively fast, targeted determination of proteins.

Proteomics of ovarian cancer: functional insights and clinical applications

In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification of aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics' contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. We propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.

Quantitative Profiling of Protein Tyrosine Kinases in Human Cancer Cell Lines by Multiplexed Parallel Reaction Monitoring Assays

Protein tyrosine kinases (PTKs) play key roles in cellular signal transduction, cell cycle regulation, cell division, and cell differentiation. Dysregulation of PTK-activated pathways, often by receptor overexpression, gene amplification, or genetic mutation, is a causal factor underlying numerous cancers. In this study, we have developed a parallel reaction monitoring-based assay for quantitative profiling of 83 PTKs. The assay detects 308 proteotypic peptides from 54 receptor tyrosine kinases and 29 nonreceptor tyrosine kinases in a single run. Quantitative comparisons were based on the labeled reference peptide method. We implemented the assay in four cell models: 1) a comparison of proliferating versus epidermal growth factor-stimulated A431 cells, 2) a comparison of SW480Null (mutant APC) and SW480APC (APC restored) colon tumor cell lines, and 3) a comparison of 10 colorectal cancer cell lines with different genomic abnormalities, and 4) lung cancer cell lines with either susceptibility (11-18) or acquired resistance (11-18R) to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib. We observed distinct PTK expression changes that were induced by stimuli, genomic features or drug resistance, which were consistent with previous reports. However, most of the measured expression differences were novel observations. For example, acquired resistance to erlotinib in the 11-18 cell model was associated not only with previously reported up-regulation of MET, but also with up-regulation of FLK2 and down-regulation of LYN and PTK7. Immunoblot analyses and shotgun proteomics data were highly consistent with parallel reaction monitoring data. Multiplexed parallel reaction monitoring assays provide a targeted, systems-level profiling approach to evaluate cancer-related proteotypes and adaptations. Data are available through Proteome eXchange Accession PXD002706.

Targeted proteomics of solid cancers: from quantification of known biomarkers towards reading the digital proteome maps

The concept of personalized medicine includes novel protein biomarkers that are expected to improve the early detection, diagnosis and therapy monitoring of malignant diseases. Tissues, biofluids, cell lines and xenograft models are the common sources of biomarker candidates that require verification of clinical value in independent patient cohorts. Targeted proteomics - based on selected reaction monitoring, or data extraction from data-independent acquisition based digital maps - now represents a promising mass spectrometry alternative to immunochemical methods. To date, it has been successfully used in a high number of studies answering clinical questions on solid malignancies: breast, colorectal, prostate, ovarian, endometrial, pancreatic, hepatocellular, lung, bladder and others. It plays an important role in functional proteomic experiments that include studying the role of post-translational modifications in cancer progression. This review summarizes verified biomarker candidates successfully quantified by targeted proteomics in this field and directs the readers who plan to design their own hypothesis-driven experiments to appropriate sources of methods and knowledge.

Applications of targeted proteomics in systems biology and translational medicine

Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM-MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.

Evaluating kinase ATP uptake and tyrosine phosphorylation using multiplexed quantification of chemically labeled and post-translationally modified peptides

Cancer biologists and other healthcare researchers face an increasing challenge in addressing the molecular complexity of disease. Biomarker measurement tools and techniques now contribute to both basic science and translational research. In particular, liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) for multiplexed measurements of protein biomarkers has emerged as a versatile tool for systems biology. Assays can be developed for specific peptides that report on protein expression, mutation, or post-translational modification; discovery proteomics data rapidly translated into multiplexed quantitative approaches. Complementary advances in affinity purification enrich classes of enzymes or peptides representing post-translationally modified or chemically labeled substrates. Here, we illustrate the process for the relative quantification of hundreds of peptides in a single LC-MRM experiment. Desthiobiotinylated peptides produced by activity-based protein profiling (ABPP) using ATP probes and tyrosine-phosphorylated peptides are used as examples. These targeted quantification panels can be applied to further understand the biology of human disease.

Emerging proteomic technologies for elucidating context-dependent cellular signaling events: A big challenge of tiny proportions

Aberrant cell signaling events either drive or compensate for nearly all pathologies. A thorough description and quantification of maladaptive signaling flux in disease is a critical step in drug development, and complex proteomic approaches can provide valuable mechanistic insights. Traditional proteomics-based signaling analyses rely heavily on in vitro cellular monoculture. The characterization of these simplified systems generates a rich understanding of the basic components and complex interactions of many signaling networks, but they cannot capture the full complexity of the microenvironments in which pathologies are ultimately made manifest. Unfortunately, techniques that can directly interrogate signaling in situ often yield mass-limited starting materials that are incompatible with traditional proteomics workflows. This review provides an overview of established and emerging techniques that are applicable to context-dependent proteomics. Analytical approaches are illustrated through recent proteomics-based studies in which selective sample acquisition strategies preserve context-dependent information, and where the challenge of minimal starting material is met by optimized sensitivity and coverage. This review is organized into three major technological themes: (i) LC methods in line with MS; (ii) antibody-based approaches; (iii) MS imaging with a discussion of data integration and systems modeling. Finally, we conclude with future perspectives and implications of context-dependent proteomics.

Mathematical modelling suggests a differential impact of β-transducin repeat-containing protein paralogues on Wnt/β-catenin signalling dynamics

The Wnt/β-catenin signalling pathway is involved in the regulation of a multitude of cellular processes by controlling the concentration of the transcriptional regulator β-catenin. Proteasomal degradation of β-catenin is mediated by two β-transducin repeat-containing protein paralogues, homologous to Slimb protein (HOS) and F-box/WD repeat-containing protein 1A (FWD1), which are functionally interchangeable and thereby considered to function redundantly in the pathway. HOS and FWD1 are both regulated by Wnt/β-catenin signalling, albeit in opposite directions, thus establishing interlocked negative and positive feedback loops. The functional relevance of the opposite regulation of HOS and FWD1 by Wnt/β-catenin signalling in conjunction with their redundant activities in proteasomal degradation of β-catenin remains unresolved. Using a detailed ordinary differential equation model, we investigated the specific influence of each individual feedback mechanism and their combination on Wnt/β-catenin signal transduction under wild-type and cancerous conditions. We found that, under wild-type conditions, the signalling dynamics are predominantly affected by the HOS feedback as a result of a higher concentration of HOS than FWD1. Transcriptional up-regulation of FWD1 by other signalling pathways reduced the impact of the HOS feedback. The opposite regulation of HOS and FWD1 expression by Wnt/β-catenin signalling allows the FWD1 feedback to be employed as a compensation mechanism against aberrant pathway activation as a result of a reduced HOS concentration. By contrast, the FWD1 feedback provides no protection against aberrant activation in adenomatous polyposis coli protein mutant cancer cells.

Comparative LC-MS/MS analysis of optimal cutting temperature (OCT) compound removal for the study of mammalian proteomes

Primary tissue samples are valuable resources for investigators interested in understanding disease. In order to maximize the information content that can be gained from these precious samples, proper storage, handling, and preparation are essential. Some tissue preservation techniques utilize the cryopreservation medium, optimal cutting temperature (OCT) compound. While this medium provides benefits for traditional molecular studies, certain components can interfere with mass spectrometric analyses. Mass spectrometry based proteomics is a growing field with many applications for disease research. Our goal is to determine a reliable method for separating the proteins from the contaminating species in OCT embedded samples, thus making these samples compatible with mass spectrometric analyses. The novel applications of ether-methanol precipitation, filter-aided sample preparation (FASP), and SDS-PAGE provide researchers with protocols for removing OCT contaminating species from valuable samples. The results presented in this study show that all three methods reproducibly remove OCT; however, precipitation and FASP outperform SDS-PAGE by common proteomic metrics.

Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods.

Evaluating melanoma drug response and therapeutic escape with quantitative proteomics

The evolution of cancer therapy into complex regimens with multiple drugs requires novel approaches for the development and evaluation of companion biomarkers. Liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) is a versatile platform for biomarker measurement. In this study, we describe the development and use of the LC-MRM platform to study the adaptive signaling responses of melanoma cells to inhibitors of HSP90 (XL888) and MEK (AZD6244). XL888 had good anti-tumor activity against NRAS mutant melanoma cell lines as well as BRAF mutant cells with acquired resistance to BRAF inhibitors both in vitro and in vivo. LC-MRM analysis showed HSP90 inhibition to be associated with decreased expression of multiple receptor tyrosine kinases, modules in the PI3K/AKT/mammalian target of rapamycin pathway, and the MAPK/CDK4 signaling axis in NRAS mutant melanoma cell lines and the inhibition of PI3K/AKT signaling in BRAF mutant melanoma xenografts with acquired vemurafenib resistance. The LC-MRM approach targeting more than 80 cancer signaling proteins was highly sensitive and could be applied to fine needle aspirates from xenografts and clinical melanoma specimens (using 50 μg of total protein). We further showed MEK inhibition to be associated with signaling through the NFκB and WNT signaling pathways, as well as increased receptor tyrosine kinase expression and activation. Validation studies identified PDGF receptor β signaling as a potential escape mechanism from MEK inhibition, which could be overcome through combined use of AZD6244 and the PDGF receptor inhibitor, crenolanib. Together, our studies show LC-MRM to have unique value as a platform for the systems level understanding of the molecular mechanisms of drug response and therapeutic escape. This work provides the proof-of-principle for the future development of LC-MRM assays for monitoring drug responses in the clinic.

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.

Review of software tools for design and analysis of large scale MRM proteomic datasets

Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow.

Modeling Wnt/β-Catenin Target Gene Expression in APC and Wnt Gradients Under Wild Type and Mutant Conditions

The Wnt/β-catenin pathway is involved in the regulation of a multitude of physiological processes by controlling the differential expression of target genes. In certain tissues such as the adult liver, the Wnt/β-catenin pathway can attain different levels of activity due to gradients of Wnt ligands and/or intracellular pathway components like APC. How graded pathway activity is converted into regionally distinct patterns of Wnt/β-catenin target gene expression is largely unknown. Here, we apply a mathematical modeling approach to investigate the impact of different regulatory mechanisms on target gene expression within Wnt or APC concentration gradients. We develop a minimal model of Wnt/β-catenin signal transduction and combine it with various mechanisms of target gene regulation. In particular, the effects of activation, inhibition, and an incoherent feedforward loop (iFFL) are compared. To specify activation kinetics, we analyze experimental data that quantify the response of β-catenin/TCF reporter constructs to different Wnt concentrations, and demonstrate that the induction of these constructs occurs in a cooperative manner with Hill coefficients between 2 and 5. In summary, our study shows that the combination of specific gene regulatory mechanisms with a time-independent gradient of Wnt or APC is sufficient to generate distinct target gene expression patterns as have been experimentally observed in liver. We find that cooperative gene activation in combination with a TCF feedback can establish sharp borders of target gene expression in Wnt or APC gradients. In contrast, the iFFL renders gene expression independent of gradients of the upstream signaling components. Our subsequent analysis of carcinogenic pathway mutations reveals that their impact on gene expression is determined by the gene regulatory mechanism and the APC concentration of the cell in which the mutation occurs.

Quantitative multiple reaction monitoring of peptide abundance introduced via a capillary zone electrophoresis-electrospray interface

We demonstrate the use of capillary zone electrophoresis with an electrokinetic sheath-flow electrospray interface coupled to a triple-quadrupole mass spectrometer for the accurate and precise quantification of Leu-enkephalin in a complex mixture using multiple-reaction monitoring (MRM). Assay time is <6 min, with no re-equilibration required between runs. A standard curve of Leu-enkephalin was performed in the presence of a background tryptic digest of bovine albumin. We demonstrate reasonably reproducible peak heights (21% relative standard deviation), retention times (better than 1% relative standard deviation), and robust electrospray quality. Our limit of detection (3σ) was 60 pM, which corresponds to the injection of 335 zmol of peptide. This is a 10-20-fold improvement in mass sensitivity than we have obtained by nano HPLC/MRM and substantially better than reported for LC/MS/MS. Further quantification was performed in the presence of stable-isotope-labeled versions of the peptides; under these conditions, linearity was observed across nearly 4 orders of magnitude. The concentration detection limit was 240 pM for the stable-isotope-labeled quantification.

Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that is emerging in the field of proteomics as a complement to untargeted shotgun methods. SRM is particularly useful when predetermined sets of proteins, such as those constituting cellular networks or sets of candidate biomarkers, need to be measured across multiple samples in a consistent, reproducible and quantitatively precise manner. Here we describe how SRM is applied in proteomics, review recent advances, present selected applications and provide a perspective on the future of this powerful technology.

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.

Evaluation of protein quantification using standard peptides containing single conservative amino acid replacements

Structural analogs are evaluated as peptide internal standards for protein quantification with liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM); specifically, single conservative amino acid replacements (SCAR) are performed to create tagged standards that differ by the addition or subtraction of a single methylene group in one amino acid side chain. Because the performance of stable isotope-labeled standards (SIS) has been shown to be superior to structural analogs, differences in both development and quantitative performance between assays based on SIS and SCAR peptides are explored. To establish an assay using the structural analogs, analysis of endogenous, SCAR and SIS peptides was performed to examine their ion signal, fragmentation patterns and response in LC-MRM. Performance of SCAR and SIS peptides was compared for quantification of epidermal growth factor receptor from lung cancer cell lysates and immunoglobulin M in the serum of multiple myeloma patients.

Monitoring a nuclear factor-κB signature of drug resistance in multiple myeloma

The emergence of acquired drug resistance results from multiple compensatory mechanisms acting to prevent cell death. Simultaneous monitoring of proteins involved in drug resistance is a major challenge for both elucidation of the underlying biology and development of candidate biomarkers for assessment of personalized cancer therapy. Here, we have utilized an integrated analytical platform based on SDS-PAGE protein fractionation prior to liquid chromatography coupled to multiple reaction monitoring mass spectrometry, a versatile and powerful tool for targeted quantification of proteins in complex matrices, to evaluate a well-characterized model system of melphalan resistance in multiple myeloma (MM). Quantitative assays were developed to measure protein expression related to signaling events and biological processes relevant to melphalan resistance in multiple myeloma, specifically: nuclear factor-κB subunits, members of the Bcl-2 family of apoptosis-regulating proteins, and Fanconi Anemia DNA repair components. SDS-PAGE protein fractionation prior to liquid chromatography coupled to multiple reaction monitoring methods were developed for quantification of these selected target proteins in amounts of material compatible with direct translation to clinical specimens (i.e. less than 50,000 cells). As proof of principle, both relative and absolute quantification were performed on cell line models of MM to compare protein expression before and after drug treatment in naïve cells and in drug resistant cells; these liquid chromatography-multiple reaction monitoring results are compared with existing literature and Western blots. The initial stage of a systems biology platform for examining drug resistance in MM has been implemented in cell line models and has been translated to MM cells isolated from a patient. The ultimate application of this platform could assist in clinical decision-making for individualized patient treatment. Although these specific assays have been developed to monitor MM, these techniques are expected to have broad applicability in cancer and other types of disease.

A database of reaction monitoring mass spectrometry assays for elucidating therapeutic response in cancer

PURPOSE

The Quantitative Assay Database (QuAD), http://proteome.moffitt.org/QUAD/, facilitates widespread implementation of quantitative mass spectrometry in cancer biology and clinical research through sharing of methods and reagents for monitoring protein expression and modification.

EXPERIMENTAL DESIGN

Liquid chromatography coupled to multiple reaction monitoring (LC-MRM) mass spectrometry assays are developed using SDS-PAGE fractionated lysates from cancer cell lines. Pathway maps created using GeneGO Metacore provide the biological relationships between proteins and illustrate concepts for multiplexed analysis; each protein can be selected to examine assay development at the protein and peptide levels.

RESULTS

The coupling of SDS-PAGE and multiple reaction monitoring mass spectrometry screening has been used to detect 876 peptides from 218 cancer-related proteins in model systems including colon, lung, melanoma, leukemias, and myeloma, which has led to the development of 95 quantitative assays including stable-isotope-labeled peptide standards. Methods are published online and peptide standards are made available to the research community. Protein expression measurements for heat shock proteins, including a comparison with ELISA and monitoring response to the HSP90 inhibitor, 17-(dimethylaminoethylamino)-17-demethoxygeldanamycin (17-DMAG), are used to illustrate the components of the QuAD and its potential utility.

CONCLUSIONS AND CLINICAL RELEVANCE

This resource enables quantitative assessment of protein components of signaling pathways and biological processes and holds promise for systematic investigation of treatment responses in cancer.

Monitoring protein expression in whole-cell extracts by targeted label- and standard-free LC-MS/MS

Targeted quantification of proteins is a daily task in biological research but often relies on techniques such as western blotting that are only barely quantitative. Here we present a broadly applicable workflow for protein quantification from unpurified whole-cell extracts that can be completed in less than 3 d. Without prefractionation or affinity enrichment, a whole-cell extract is trypsin-digested in an acetonitrile-containing ammonium carbonate buffer and high-molecular-weight compounds are removed by filtration. A normalization strategy, which involves endogenous reference proteins, facilitates the determination of relative changes in protein expression without requiring isotope labeling or standard addition. On a triple-quadrupole mass spectrometer, we demonstrate standard-free quantification of yeast proteins present over five orders of magnitude and present at ≥500 copies per cell. Liquid chromatography/multiple reaction monitoring (LC-MRM)-based proteomics is therefore a next-generation alternative to western blotting, as it allows simultaneous and reliable quantification of multiple endogenous proteins without the need for enrichment, isotope labeling or use of antibodies.

PTEN loss confers BRAF inhibitor resistance to melanoma cells through the suppression of BIM expression

This study addresses the role of PTEN loss in intrinsic resistance to the BRAF inhibitor PLX4720. Immunohistochemical staining of a tissue array covering all stages of melanocytic neoplasia (n = 192) revealed PTEN expression to be lost in >10% of all melanoma cases. Although PTEN expression status did not predict for sensitivity to the growth inhibitory effects of PLX4720, it was predictive for apoptosis, with only limited cell death observed in melanomas lacking PTEN expression (PTEN-). Mechanistically, PLX4720 was found to stimulate AKT signaling in the PTEN- but not the PTEN+ cell lines. Liquid chromatography multiple reaction monitoring mass spectrometry (LC-MRM) was performed to identify differences in apoptosis signaling between the two cell line groups. PLX4720 treatment significantly increased BIM expression in the PTEN+ (>14-fold) compared with the PTEN- cell lines (four-fold). A role for PTEN in the regulation of PLX4720-mediated BIM expression was confirmed by siRNA knockdown of PTEN and through reintroduction of PTEN into cells that were PTEN-. Further studies showed that siRNA knockdown of BIM significantly blunted the apoptotic response in PTEN+ melanoma cells. Dual treatment of PTEN- cells with PLX4720 and a PI3K inhibitor enhanced BIM expression at both the mRNA and protein level and increased the level of apoptosis through a mechanism involving AKT3 and the activation of FOXO3a. In conclusion, we have shown for the first time that loss of PTEN contributes to intrinsic BRAF inhibitor resistance via the suppression of BIM-mediated apoptosis.

PTEN loss confers BRAF inhibitor resistance to melanoma cells through the suppression of BIM expression

This study addresses the role of PTEN loss in intrinsic resistance to the BRAF inhibitor PLX4720. Immunohistochemical staining of a tissue array covering all stages of melanocytic neoplasia (n = 192) revealed PTEN expression to be lost in >10% of all melanoma cases. Although PTEN expression status did not predict for sensitivity to the growth inhibitory effects of PLX4720, it was predictive for apoptosis, with only limited cell death observed in melanomas lacking PTEN expression (PTEN-). Mechanistically, PLX4720 was found to stimulate AKT signaling in the PTEN- but not the PTEN+ cell lines. Liquid chromatography multiple reaction monitoring mass spectrometry (LC-MRM) was performed to identify differences in apoptosis signaling between the two cell line groups. PLX4720 treatment significantly increased BIM expression in the PTEN+ (>14-fold) compared with the PTEN- cell lines (four-fold). A role for PTEN in the regulation of PLX4720-mediated BIM expression was confirmed by siRNA knockdown of PTEN and through reintroduction of PTEN into cells that were PTEN-. Further studies showed that siRNA knockdown of BIM significantly blunted the apoptotic response in PTEN+ melanoma cells. Dual treatment of PTEN- cells with PLX4720 and a PI3K inhibitor enhanced BIM expression at both the mRNA and protein level and increased the level of apoptosis through a mechanism involving AKT3 and the activation of FOXO3a. In conclusion, we have shown for the first time that loss of PTEN contributes to intrinsic BRAF inhibitor resistance via the suppression of BIM-mediated apoptosis.

Proteomic technologies for biomarker studies in psychiatry: advances and needs

In the postgenome era, proteomics has arisen as a promising tool for more complete comprehension of diseases and for biomarker discovery. Some of these objectives have already been partly achieved for illnesses such as cancer. In the case of psychiatric conditions, however, proteomic advances have had a less profound impact. Here, we outline the necessity of improving and applying proteomic methods for biomarker discovery and validation in the field of psychiatric disorders. While proteomic-based applications in neurosciences have increased in accuracy and sensitivity over the past 10 years, the development of orthogonal validation technologies has fallen behind. These issues are discussed along with the importance of integrating systems biology approaches and combining proteomics with other research approaches. The future development of such technologies may put proteomics closer to clinical applications in psychiatry.