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Mol Oncol. 2010 December; 4(6): 482–495.
Published online 2010 September 26. doi:  10.1016/j.molonc.2010.09.004
PMCID: PMC3030978

Phosphoproteomics in cancer

Monitoring Editor: Julio Celis and José Moreira


Reversible protein phosphorylation serves as a basis for regulating a number of cellular processes. Aberrant activation of kinase signaling pathways is commonly associated with several cancers. Recent developments in phosphoprotein/phosphopeptide enrichment strategies and quantitative mass spectrometry have resulted in robust pipelines for high‐throughput characterization of phosphorylation in a global fashion. Today, it is possible to profile site‐specific phosphorylation events on thousands of proteins in a single experiment. The potential of this approach is already being realized to characterize signaling pathways that govern oncogenesis. In addition, chemical proteomic strategies have been used to unravel targets of kinase inhibitors, which are otherwise difficult to characterize. This review summarizes various approaches used for analysis of the phosphoproteome in general, and protein kinases in particular, highlighting key cancer phosphoproteomic studies.

Keywords: SILAC, Protein microarrays, Phosphorylation, Signal transduction

1. Introduction

Phosphorylation is one of the commonest post‐translational modifications involved in regulating biological processes in a cell. Dysregulation of kinase signaling pathways is commonly associated with various cancers (Hanahan and Weinberg, 2000). Aberrations in kinases have been reported in several cancers including gastrointestinal stromal tumors (Corless et al., 2004), lung cancer (Sharma et al., 2007), haematologic malignancies (Ferrajoli et al., 2006), breast cancer (Hynes and MacDonald, 2009), pancreatic cancer (Harsha et al., 2008a) and prostate cancer (Lee et al., 2008). This aberrant regulation may result from overexpression of kinases, mutations or defects in negative regulatory mechanisms, among others. Activated kinases can be specifically targeted using small molecule inhibitors. Examples of such targeted therapeutic approach employing small molecule kinase inhibitors have been previously reported in various cancers including chronic myelogenous leukemia (CML) (Druker et al., 1996; Golas et al., 2003), gastrointestinal stromal tumors (Braconi et al., 2008), small cell lung cancer (Krystal et al., 2000), breast cancer (Rabindran et al., 2004; Xia et al., 2002), non‐small cell lung cancer (Lynch et al., 2004) and melanomas (Karasarides et al., 2004). Personalized medicine in the context of cancer therapy is illustrated by the use of imatinib in CML and erlotinib in non‐small cell lung cancer through blockade of Abl and epidermal growth factor receptor kinase, respectively.

A number of proteomic approaches have been developed over the years to identify aberrantly activated kinases and their downstream substrates. Most often, phosphorylation is used as a surrogate for monitoring kinase activity in cells. In the past, kinases and their activities were generally studied on an individual basis using biochemical approaches. However, technological advances in the recent past have led to development of several high‐throughput strategies to study the phosphoproteome. High‐throughput technologies for monitoring phosphorylation events include array‐based technologies such as peptide arrays (Amanchy et al., 2008; Diks et al., 2004; Houseman et al., 2002; Versele et al., 2009), reverse‐phase protein arrays (Gulmann et al., 2009), antibody arrays (Gembitsky et al., 2004; Zhong et al., 2008) and mass spectrometry (Chen and Yates, 2007, 2009, 2008, 2008, 2005, 2007, 2009, 2007). Quantitative phosphoproteomic profiling allows researchers to investigate aberrantly activated signaling pathways and therapeutic targets in cancers (Figure 1). Finally, phosphoproteomic approaches can not only assist in determining the appropriate therapeutic targets but also elucidate mechanisms such as off‐target effects resulting from binding of inhibitors to unintended kinases/non‐kinase proteins. Here, we will discuss some of the popular approaches to characterize the kinome and the phosphoproteome along with illustrative examples where such approaches have been employed for global analysis of cancer.

Figure 1

Applications of quantitative phosphoproteomics in cancer. Quantitative phosphoproteomics can lead to discovery of aberrantly activated signaling pathways and therapeutic targets in cancers. It can also reveal downstream effectors of mutant kinases, thereby ...

2. Kinases and cancer

The human kinome comprises more than 500 distinct genes encoding serine/threonine and tyrosine kinases (Manning et al., 2002). Over the years, kinases have been firmly established as an important class of proteins involved in plethora of cellular functions including cell growth, proliferation and differentiation. Dysregulation of these otherwise tightly regulated processes has been described to contribute to oncogenesis. Direct involvement of protein kinases in cancers came from the discovery of v‐SRC oncogene (Spector et al., 1978; Stehelin et al., 1976). The corresponding oncoprotein was later purified and found to be a protein kinase that undergoes phosphorylation (Brugge and Erikson, 1977; Levinson et al., 1978). Subsequent biochemical studies revealed Src was a tyrosine kinase (Hunter and Sefton, 1980; Sefton et al., 1980). In fact, the transforming proteins of a number of avian and mammalian retroviruses were later found to possess tyrosine kinase activity (Hunter and Cooper, 1985; Sefton, 1986). Tyrosine phosphorylation of host cellular proteins by viral kinases and their apparent involvement in cellular transformation was established using Rous sarcoma and Abelson murine leukemia viruses (Sefton et al., 1981; Witte et al., 1980). To date, mutations in kinases have been studied in a large variety of cancers (Barber et al., 2004; Blume‐Jensen and Hunter, 2001; Parsons et al., 2005; Stephens et al., 2005) and, correspondingly, kinase inhibitors have emerged a major class of anti‐cancer drugs that are either in clinical use or in various phases of clinical trials (Knight et al., 2010). In recent years, advances in selective enrichment of phosphoproteome have led to systematic characterization of aberrantly activated kinase signaling pathways in several cancers.

3. Strategies for selective enrichment and analysis of phosphoproteome

Cellular proteins in humans are predominantly phosphorylated on serine/threonine residues with a smaller extent of phosphorylation occurring on tyrosine residues. However, the overall low abundance of phosphoproteins complicates identification and characterization of this sub‐proteome using standard analytical methods for protein characterization. This has spurred the development of molecular tools to preferentially enrich the phosphoproteome (Figure 2). The majority of these early tools were anti‐phosphotyrosine antibodies that were developed using a variety of immunogens (Frackelton et al., 1991; Kamps, 1991; Wang, 1988). The success of anti‐phosphotyrosine antibodies in characterizing tyrosine phosphoproteome in cancers is exemplified by various mass spectrometry‐based studies published in the recent past (Harsha et al., 2008a; Rikova et al., 2007; Rush et al., 2005). However, application of antibodies directed against phosphoserine and phosphothreonine residues for enrichment purposes is more recent (Gronborg et al., 2002; Kane et al., 2002).

Figure 2

Fractionation and enrichment strategies for phosphoproteomics. Phosphoproteome is a minor fraction of any cellular proteome. The complexity of the cellular proteome hinders the analysis of phosphoproteins. Prior to phosphoproteomic analysis by mass spectrometry, ...

High affinity of phosphoserine towards ferric ions was studied decades ago (Osterberg, 1957). This feature of ferric ions was later exploited by biochemists to isolate phosphoproteins and phosphopeptides using immobilized metal affinity chromatography (IMAC) (Andersson and Porath, 1986; Muszynska et al., 1992). Analogous to ferric ions, gallium (III) has also been shown to display affinity and selectivity to phosphopeptides (Posewitz and Tempst, 1999). These enrichment strategies followed by mass spectrometry can reveal the identity of the proteins and the sites of modification (Betts et al., 1997; Liao et al., 1994; Ma et al., 2001; Stensballe et al., 2001; Yip and Hutchens, 1992). Alternative strategies based on chemical modification of phosphopeptides to enable enrichment have also been described (Oda et al., 2001; Zhou et al., 2001). One of the other advances that particularly enhanced the ability to enrich serine/threonine phosphopeptides is the use of titanium dioxide (TiO2) for selective enrichment of phosphorylated peptides (Larsen et al., 2005; Molina et al., 2007; Olsen et al., 2006; Pinkse et al., 2004; Sano and Nakamura, 2004). Other strategies that are promising for phosphopeptide enrichment include hydrophilic interaction chromatography (HILIC) coupled to IMAC (McNulty and Annan, 2008). Analysis of phosphopeptides without prior enrichment can be carried out by applying precursor ion scanning for loss of PO3 ions in the negative ion mode on a mass spectrometer (Carr et al., 1996; Old et al., 2009). Old et al. further developed this method for a global analysis of the phosphoproteome in which they examined targets of B‐Raf/MKK/ERK signaling pathway, a pathway that is constitutively active in melanoma owing to oncogenic genomic mutations in B‐Raf (Carr et al., 1996; Old et al., 2009).

3.1. Alternatives to mass spectrometry for high‐throughput phosphoproteome analysis

Approaches that do not rely on mass spectrometry to analyze the phosphoproteome include peptide microarrays, protein microarrays and antibody arrays. Global identification of substrates of kinases can be done by generating protein microarrays or peptide microarrays followed by in vitro kinase assays using purified kinases or cell/tissue lysates to determine the potential substrates (Amanchy et al., 2008; Diks et al., 2004; Ptacek et al., 2005). Using this methodology, once in vitro kinase substrate specificity is established, it can be extended to cancer phosphoproteomic studies to identify hyperactivated kinases or kinase driven signaling pathways. Alternatively, reverse‐phase protein microarrays can be generated either using purified proteins (Hudson et al., 2007; Ptacek et al., 2005) or using lysates derived from total cancer tissue lysate or microdissected epithelium from cancer tissues and probed with phosphospecific antibodies to determine activation status of key signaling molecules (Paweletz et al., 2001; Sheehan et al., 2005; Wulfkuhle et al., 2003). Antibody arrays also serve as an attractive option to carry out phosphoproteomic profiling in cancers (Gembitsky et al., 2004; Kingsmore, 2006). Here, unlike protein or peptide microarrays, antibodies against specific proteins are arrayed and used to detect the target proteins from cancer cell/tissue lysate. Phospho‐specific antibody arrays are commercially available that facilitate investigation of specific activated pathways in cancers (Zhong et al., 2008, 2009). While protein/peptide microarrays provide the necessary throughput to carry out large scale studies, they require extensive biochemical optimization experiments to carry out context dependent phosphoproteomic profiling studies. Table 1 provides most commonly used selective enrichment/monitoring strategies along with pros and cons of respective methodologies.

Table 1

Most commonly used phosphoprotein/peptide enrichment strategies along with their pros and cons.

4. Mass spectrometry‐based quantitative phosphoproteomic profiling

Development of various labeling methods coupled with the availability of sensitive mass spectrometers has offered researchers with an opportunity to carry out quantitative phosphoproteomic studies to monitor phosphorylation dynamics across various conditions. The most common labeling strategies used to achieve this include stable isotope labeling by amino acids in cell culture (SILAC; (Amanchy et al., 2005, 2005, 2008, 2008) and isobaric tags for relative and absolute quantitation (iTRAQ) (Ross et al., 2004). In particular, SILAC has been extensively used to study the temporal dynamics of phosphoproteins across various signaling pathways (Kruger et al., 2008; Olsen et al., 2006). Although serum starvation is not necessarily part of all SILAC experiments, phosphoproteomic studies to investigate signaling pathways generally involve serum starvation. Serum starvation induced gene expression changes have been well studied in various contexts (Levin et al., 2010; Shin et al., 2008; Zander and Bemark, 2008). It is necessary to consider these caveats of long term serum starvation before carrying out SILAC based phosphoproteomic studies. Several studies have been carried out in receptor or non‐receptor kinase activated systems to identify downstream signaling intermediates. This includes EphB (Jorgensen et al., 2009; Zhang and Neubert, 2009; Zhang et al., 2006), Her2/Neu (Bose et al., 2006), insulin (Kruger et al., 2008), FGF (Cunningham et al., 2010), T cell receptor (Nguyen et al., 2009), ATM/ATR (Stokes et al., 2007) and SYK (Larive et al., 2009) signaling pathways.

4.1. Phosphopeptide mapping of the human proteome

The capability to selectively enrich and perform site‐specific phosphopeptide analysis has led to an explosive growth of phosphoproteomic data in the past decade (Figure 3). Because of this, we already have a catalog of thousands of phosphorylation sites on cellular proteins. One of the earliest studies to employ mass spectrometry‐based site specific investigation of multiple tyrosine phosphorylation sites from human whole cell lysates used a combined approach involving immunoprecipitation of phosphotyrosine proteins followed by IMAC to enrich for phosphopeptides (Salomon et al., 2003). These studies were carried out to explore tyrosine phosphorylation patterns under activation of human T cells or inhibition of oncogenic BCR‐ABL fusion product in chronic myelogenous leukemia cells by treating them with the inhibitor Gleevec. These studies yielded 64 unique tyrosine phosphorylation sites on 32 different proteins. In the following year, the same group improvised the enrichment strategy and reported three times greater number of tyrosine phosphosites than their earlier report (Brill et al., 2004). Around the same time, Amanchy et al. carried out immunoaffinity‐based enrichment of tyrosine phosphoproteins from HeLa cell lysates prior to LC‐MS/MS and reported 42 in vivo tyrosine phosphorylation sites (Amanchy et al., 2005a). Major breakthrough in tyrosine phosphopeptide enrichment came when Rush et al. reported immunoaffinity‐based tyrosine phosphopeptide enrichment and revealed more than 300 distinct tyrosine phosphorylation sites by analyzing protein extracts from three human cancer cell lines – Jurkat (leukemic T cell line), Karpas 299 and SU‐DHL‐1 (cell lines derived from anaplastic large cell lymphomas) (Rush et al., 2005). This was achieved by employing an anti‐phosphotyrosine antibody to enrich tyrosine phosphopeptides prior to mass spectrometry. Since then, a number of groups have employed this strategy to study the tyrosine phosphoproteome in various contexts.

Figure 3

Key milestones in the global analysis of protein kinases and phosphoproteome using mass spectrometry. The past decade has witnessed rapid development of methodologies for global analysis of phosphoproteome. In less than ten years since the initial global ...

One of the most widely studied kinase signaling pathways using site specific phosphoproteomic analysis is EGFR signaling. Considering that this receptor tyrosine kinase is implicated in several cancers, these studies have immensely contributed to our understanding of molecular events downstream of EGFR signaling. By employing immunoaffinity‐based phosphopeptide enrichment coupled with iTRAQ based quantitative mass spectrometry, Zhang et al. characterized temporal regulation of 78 tyrosine phosphorylation sites on 58 proteins in a single analysis (Zhang et al., 2005). The study was carried out using human mammary epithelial cells treated with EGF for four different time points. Olsen et al. employed TiO2‐based phosphopeptide enrichment using SILAC to study temporal dynamics of EGFR signaling in HeLa cells. This study looked at five different time points after EGF stimulation and reported identification of 6600 phosphorylation sites on 2244 proteins (Olsen et al., 2006). By utilizing electron transfer dissociation (ETD) technique for peptide fragmentation along with classically used collision induced dissociation (CID), Molina et al. reported identification of 1435 phosphorylation sites in TiO2 enriched phosphopeptides from human embryonic kidney 293T cells (Molina et al., 2007). A proof of principle study using HILIC/IMAC identified >1000 unique phosphorylation sites from as little as 300 μg of HeLa cell lysate (McNulty and Annan, 2008).

Cataloging of phosphorylation sites has been carried out in other contexts as well. For instance, it is well known that upon DNA damage, serine/threonine kinases, ataxia telangiectasia‐mutated (ATM) and ATM and Rad3‐related (ATR), activate several downstream substrates by phosphorylating SQ/TQ motifs. Using immunoaffinity‐based enrichment strategy in conjunction with SILAC, Matsuoka et al. and Stokes et al. reported comprehensive site specific phosphoproteomic analysis of infrared and UV‐induced ATM/ATR signaling pathways (Matsuoka et al., 2007; Stokes et al., 2007). While Matsuoka et al. identified >900 regulated phosphorylation sites encompassing >700 proteins, Stokes et al. reported 570 phosphorylation sites on 464 proteins. Interestingly, although the studies were carried out using two different cell lines (293T embryonic kidney cells and MO59K glioblastoma cells, respectively) with two different challenges (IR and UV), there was considerable coherence in the signaling modules that were found to be activated upon DNA damage along with notable differences in phosphorylation of specific substrates that were unique to these forms of radiation.

Recently, alternative strategies are being employed to enrich phosphopeptides. One of the approaches involves precipitating phosphopeptides using calcium phosphate (Zhang et al., 2007) while the other involves precipitation of phosphopeptides by Ba2+/acetone (Ruse et al., 2008). By employing calcium phosphate precipitation strategy to enrich phosphopeptides, Xia et al. reported identification of 466 phosphorylation sites on 185 proteins from postmortem alzheimer disease brain (Xia et al., 2008). Ba2+/acetone precipitation method led to identification of 1037 phosphopeptides from 250 μg of total protein (Ruse et al., 2008). Selective monitoring of desired phosphopeptides can also be carried out in specific scenarios to identify and quantitate phosphorylation sites across multiple conditions (Unwin et al., 2005; Wolf‐Yadlin et al., 2007). Methods such as KAYAK (kinase activity assay for kinome profiling) that rely on mass spectrometry as a readout permit monitoring of kinase activities from multiple signaling pathways simultaneously (Kubota et al., 2009).

Using IMAC‐based phosphopeptide enrichment strategy coupled with MS‐based proteomics employing ETD and CAD for peptide fragmentation, Swaney et al. reported 10,844 phosphorylation sites from human embryonic stem cells (Swaney et al., 2009). Phosphoproteomic profiling of human embryonic stem cells (hESCs) and their differentiated derivatives has revealed complex interplay of kinase signaling pathways in maintenance and differentiation of hESCs. By carrying out phosphoproteomic analysis of hESCs, Brill et al. reported 2546 phosphorylation sites on 1602 phosphoproteins (Brill et al., 2009). Using SILAC based quantitative phosphoproteomic strategy, Hoof et al. quantified phosphorylation dynamics during early differentiation of hESCs using 3067 phosphosites on 1399 phosphoproteins (Van Hoof et al., 2009). They report approximately 50% of the identified sites were regulated within 1h of inducing differentiation by bone morphogenetic protein (BMP).

In a short time, mass spectrometry‐based phosphoproteomic profiling has transformed cancer research by providing novel insights into molecular mechanisms that govern cancers and facilitating drug discovery. Below, we summarize various studies that have employed phosphoproteomics to study kinase signaling modules operating in cancers.

4.2. Characterizing activated signaling pathways using cell culture models

Cell culture models have been extensively used to understand molecular mechanisms that drive cancers. For example, Walters et al. investigated mechanisms underlying constitutive phosphorylation of STAT5 in acute myeloid leukemia (AML) cell lines by employing a phosphoproteomic approach (Walters et al., 2006a). In order to identify upstream kinases responsible for STAT5 phosphorylation in AML cell lines, HEL, HT‐93 and KBM‐3, in the absence of FLT3 or KIT activating mutations, they carried out tyrosine phosphopeptide enrichment and LC‐MS/MS. After observing phosphorylated forms of TEL and ARG in HT‐93 cell line and BCR and ABL in KNM‐3 cell lines, the authors went on to verify and conclude the existence of TEL‐ARG fusion protein in HT‐93 and BCR‐ABL fusion protein in KNM‐3 as upstream enzymes of STAT5. In HEL cell line, the authors identified phosphorylation of JAK proteins and established JAK2 as the upstream kinase responsible for STAT5 phosphorylation. Sequencing of JAK2 gene in HEL revealed activating mutations in JH2 pseudokinase domain. The group employed the same strategy to identify activating mutations in constitutively phosphorylated JAK3 in acute megakaryoblastic leukemia cell line CMK (Walters et al., 2006b).

Metabolic labeling strategies such as SILAC and in vitro chemical tagging approach like isobaric tags for relative and absolute quantitation (iTRAQ) are especially useful in dissecting molecular mechanisms using quantitative phosphoproteomics. Our group has utilized SILAC‐based approaches in the past to identify aberrantly activated tyrosine kinase signaling pathways in pancreatic cancer (Harsha et al., 2008a). Comparing tyrosine phosphoproteins derived from a non‐neoplastic human pancreatic ductal epithelial cell line (HPDE) with those derived from a low passage pancreatic cancer cell line, we identified epidermal growth factor receptor (EGFR) pathway to be aberrantly activated. Using a mouse xenograft system, we established activated EGFR as a potential drug target in a subset of pancreatic cancers. Importantly, in this study, EGFR was not overexpressed in the cancer cell line that was investigated but was hyperactivated. Similarly, we have employed this strategy to identify differentially regulated tyrosine phosphoproteins in cells expressing lung cancer‐specific alleles of EGFR and KRAS (Guha et al., 2008). The study was carried out using isogenic human bronchial epithelial cells and human lung adenocarcinoma cell lines expressing either of the two mutant alleles of EGFR (L858R and Del E746‐A750) or a mutant KRAS allele, which are commonly observed in human lung adenocarcinomas. This study showed hyperphosphorylation of signaling molecules in HBECs expressing mutant alleles of EGFR as compared to cells expressing wild type EGFR or mutant RAS. Li et al. have employed phosphoproteomic profiling to identify tyrosine phosphoproteins associated with metastasis in hepatocellular carcinoma (Li et al., 2009). In this study, tyrosine phosphoproteome of a non‐metastatic hepatocellular carcinoma cell line Hep3B was compared to a metastatic cell line MHCC97H. They identified FER, a non‐receptor tyrosine kinase as an important candidate that plays a critical role in invasion and metastasis of hepatocellular carcinoma. Large‐scale characterization of tyrosine kinase signaling in non‐small cell lung carcinoma has been carried out using both cell lines and surgically resected tumor tissue (Rikova et al., 2007).

Chemoresistance is one of the important properties of cancer cells that limits our ability of therapeutic intervention to treat cancers. Phosphoproteomic profiling studies prove useful in determining the signaling pathways/cellular networks associated with inhibitor sensitive and inhibitor resistant cancer cells. Guo et al. carried out phosphoproteomic profiling to compare tyrosine kinase signaling networks operative in EGFR inhibitor sensitive and resistant non‐small cell lung cancer cell lines (Guo et al., 2008). Similarly, Huang et al. performed iTRAQ based quantitative analysis of phosphorylation‐mediated EGFRvIII cellular signaling networks in glioblastoma cell lines expressing different levels of EGFRvIII (Huang et al., 2007). EGFRvIII is a truncated mutant of EGF receptor that lacks the extracellular ligand binding domain. It is known to be associated with poor outcome and chemoresistance. This phosphoproteomic study revealed that phosphorylation of activation site on c‐Met was enhanced as a function of EGFRvIII expression level. The authors showed that a combined treatment strategy targeting both EGFR and c‐Met could overcome the observed chemoresistance. As a follow up, the same group carried out quantitative phosphoproteomic profiling using phosphoserine/phosphothreonine specific antibodies revealing a previously undetermined role of several kinases downstream of EGFR signaling (Joughin et al., 2009).

Targeted studies to characterize the phosphoproteome induced by oncogenic non‐receptor tyrosine kinases have also been carried out using quantitative proteomic strategy. By using Src‐transformed and nontransformed mouse fibroblasts, our group has reported several Src substrates and the corresponding tyrosine phosphorylation sites that are regulated by oncogenic Src (Luo et al., 2008). By using an integrated proteomics strategy that included cell culture, mass spectrometry and peptide microarrays, we were able to identify a number of novel substrates of c‐Src (Amanchy et al., 2008). In a follow up work employing SILAC based quantitative phosphoproteomic strategy, c‐Src tyrosine kinase substrates in platelet‐derived growth factor receptor signaling were determined (Amanchy et al., 2009). This is of importance as oncogenic Src is associated with progression of many human cancers. Leroy et al. employed SILAC based quantitative proteomic strategy to reveal a Src induced tyrosine kinase network that promotes invasive activity in colorectal cancer cell line SW620 (Leroy et al., 2009). While cell culture systems have served as excellent models for characterizing signaling pathways in cancers, parallel efforts have been undertaken by different groups to study pathways in surgically resected tumor tissues.

4.3. Characterizing activated signaling pathways using tumor tissues

Surgically resected tumors are an ideal sample to investigate the phosphorylation status of proteins in their native environment. Large scale characterization of phosphoproteins in both cell lines and surgically resected tumor tissue has been undertaken in non‐small cell lung carcinoma. By employing tyrosine phosphopeptide enrichment strategy coupled with LC‐MS/MS analysis, Rikova et al. characterized tyrosine kinase signaling in 150 non‐small cell lung cancer samples along with 41 cell lines (Rikova et al., 2007). This study revealed phosphorylation of more than 50 different tyrosine kinases and roughly 2500 different substrates in non‐small cell lung cancer. Phosphoproteomic profiling has also been reported in melanoma where Zanivan et al. identified ~5600 phosphorylation sites on 2250 proteins (Zanivan et al., 2008). The melanoma tissue used in this study was derived from three albino TG3 mutant mice of different ages. Although this was not a quantitative experiment, it showed the feasibility of tissue phosphoproteomics. Cancer tissue samples are generally archived in hospitals after formalin fixation and paraffin‐embedding (FFPE). These samples have long been considered to be unsuitable for mass spectrometry‐based analysis as the proteins are cross‐linked. Recently, Ostasiewicz et al. carried out both qualitative and quantitative analysis using tissue derived from SILAC mouse to determine the feasibility of FFPE samples for phosphoproteomics(Ostasiewicz et al., 2010). This study identified ~5000 phosphorylation sites from FFPE mouse liver samples revealing that phosphoproteome is preserved in these samples and is suitable for quantitative profiling. This has immense implications for cancer research as it will encourage efforts on analysis of archived tissue samples from a broad range of clinical scenarios. While one aspect of cancer phosphoproteomics is to characterize aberrantly activated signaling pathways in cancers, there are now several efforts focusing on identifying and characterizing cellular targets of kinase inhibitors.

5. Quantitative proteomics to identify and characterize pharmacological targets

The clinical success of imatinib in chronic myelogenous leukemia underscored the utility of kinase inhibitors in treating cancers (Druker et al., 2001). A variety of small molecules are now being screened to identify cancer therapeutic agents that are directed against kinases and other key signaling molecules. Although anti‐cancer effects of some of the inhibitors are established, the proteins or pathways targeted by these inhibitors remain ill‐characterized. Even when the direct targets of these inhibitors are established, the cellular networks that are affected by these inhibitors remain unexplored. It becomes important to characterize these as the kinases themselves are known to mutate thus becoming resistant to the drugs. Quantitative phosphoproteomics is especially useful in characterizing targets of kinase inhibitors. It facilitates exploring the effect of kinase inhibitors on entire signal transduction network at the resolution of individual phosphorylation sites. Bose et al. utilized three state SILAC strategy to explore the effect of EGFR and Her2 selective inhibitor, PD168393 on Her2 overexpressing cells (Bose et al., 2006). Similar study has also been undertaken to characterize the effect of two widely used MAPK inhibitors, U0126 and SB202190 on cellular phosphoproteome (Pan et al., 2009). The same study also demonstrated nearly thousand phosphorylation events that were affected by dasatinib, a clinical drug against Gleevec‐resistant, point mutated versions of BCR‐Abl. While the effect of selective kinase inhibitors on cellular phosphoproteome is being studied using the above‐mentioned strategies, efforts are also on to characterize the total kinome complement of cells and their phosphorylation dynamics.

Small molecule kinase inhibitors often target conserved ATP binding sites on kinases. Because of high conservation of this site across kinases, most inhibitors are not so specific and target multiple kinases. The selectivity of such inhibitors is usually assessed by in vitro enzymatic assays using a set of recombinant protein kinases (Bain et al., 2003; Davies et al., 2000). However, these kinases are often expressed in non‐human systems and may not truly reflect the behaviour of native kinases both in terms of folding as well as activity. Further, inhibitor selectivity is often tested across only a subset of kinases leaving the large majority untested. This has prompted researchers to look for alternative approaches by which target selectivity can be established for kinase inhibitors. An approach that will reveal the true (and broad) specificity of kinase inhibitors in physiological context is preferred. Recent advances in chemical proteomics involving kinase inhibitor based affinity matrices have opened up avenues for better characterization of cellular targets (Bantscheff et al., 2007; Godl et al., 2003).

By using immobilized SB 203580 analogue, a widely used p38 inhibitor, as bait, Godl et al. identified previously unknown targets in HeLa protein lysates (Godl et al., 2003). Rip‐like interacting caspase‐like apoptosis‐regulatory protein was more potently inhibited by SB 203580 as compared to p38. By employing immobilized nonselective kinase inhibitors (kinobeads) coupled with iTRAQ based quantitative proteomic strategy, Bantscheff et al. profiled protein targets of widely used ABL kinase inhibitors imatinib, dasatinib and bosutinib in K562 cells. In addition to confirming known targets including ABL and SRC family kinases, this strategy identified receptor tyrosine kinase DDR1 and oxidoreductase NQO2, as additional targets of imatinib (Bantscheff et al., 2007). Mass spectrometric analysis of kinobead purifications from 14 human cell lines and tissues led to enrichment of 269 protein kinases, about 50% of all the kinases known in human. Interestingly, Rix et al. carried out a similar study employing three potent BCR‐ABL inhibitors, imatinib, dasatinib and nilotinib and probed for cellular targets in K562 and primary chronic myeloid leukemia cells. These studies also identified DDR1 and oxidoreductase NQO2 as potent targets of these kinase inhibitors (Rix et al., 2007). While off‐targets in the kinase family are understandable, the identification of non‐kinase target NQO2 by both the groups reveals unsuspected mechanisms through which some of the kinase inhibitors could be acting. These studies have established chemical proteomics using kinase enrichment matrices as useful strategies for identifying cellular targets of kinase inhibitors. This strategy is now increasingly employed to characterize several novel kinase inhibitors (Remsing Rix, 2009; Rix et al., 2010). Coupling kinase enrichment strategy with phosphoproteomics will not only identify cellular targets of kinase inhibitors, but will also reveal endogenous phosphorylation status of the enriched kinases that may reflect its activation status (Daub et al., 2008; Oppermann et al., 2009) (Figure 4). In another approach, Hahn et al. integrated immunoaffinity‐based tyrosine phosphoproteome profiling by mass spectrometry and RNAi based signature screening to identify candidate gefitinib targets for AML therapy (Hahn et al., 2009). This approach identified SYK as a candidate target for gefitinib, a widely used EGFR inhibitor.

Figure 4

Identification of cellular targets of kinase inhibitors. Immobilized kinase inhibitors can be used to identify their cellular targets. The target selectivity of such inhibitors can be determined by incubating lysates from cells labeled using the SILAC ...

6. Conclusions and outlook

Phosphoproteomics has played a significant role in our ability to understand molecular mechanisms that govern human cancers. Various technological platforms are now available for phosphoproteomic studies enabling us to address different aspects of tumor biology governed by phosphorylation‐mediated signaling pathways. These studies have clearly taken us beyond looking at mutations or other genetic variations commonly observed in cancers and are providing us insights into functional consequences of these changes in conferring survival advantages to cancer cells. Such studies are already being used as the basis for determining therapeutic options. With an ever increasing list of kinase inhibitors being developed by pharmaceutical companies, such strategies have become vital not only to determine the targets of these inhibitors but also to study their off‐target effects. We foresee phosphoproteomics emerging as a vital technique in clinical research to assist in diagnosis, prognosis and treatment of cancers. The major challenge ahead is to develop this technology further to make it amenable for use in the clinic with as few sample processing steps as possible.


We thank the Department of Biotechnology (DBT), Government of India for research support to the Institute of Bioinformatics, Bangalore. Harsha Gowda is a Wellcome Trust/DBT India Alliance Early Career Fellow. A.P. was supported by NIH Roadmap grant “Technology Center for Networks and Pathways” (U54 RR 020839) and a contract N01‐HV‐28180 from the National Heart Lung and Blood Institute.


Harsha H.C., Pandey Akhilesh, (2010), Phosphoproteomics in cancer, Molecular Oncology, 4, doi: 10.1016/j.molonc.2010.09.004.

Contributor Information

H.C. Harsha, gro.scitamrofnioibi@ahsrah.

Akhilesh Pandey, ude.imhj@yednap.


  • Amanchy R., Kalume D.E., Iwahori A., Zhong J., Pandey A., 2005. Phosphoproteome analysis of HeLa cells using stable isotope labeling with amino acids in cell culture (SILAC). J. Proteome Res. 4, 1661–1671. [PubMed]
  • Amanchy R., Kalume D.E., Pandey A., 2005. Stable isotope labeling with amino acids in cell culture (SILAC) for studying dynamics of protein abundance and posttranslational modifications. Sci. STKE. l2 [PubMed]
  • Amanchy R., Zhong J., Hong R., Kim J.H., Gucek M., Cole R.N., Molina H., Pandey A., 2009. Identification of c-Src tyrosine kinase substrates in platelet-derived growth factor receptor signaling. Mol. Oncol. 3, 439–450. [PubMed]
  • Amanchy R., Zhong J., Molina H., Chaerkady R., Iwahori A., Kalume D.E., Gronborg M., Joore J., Cope L., Pandey A., 2008. Identification of c-Src tyrosine kinase substrates using mass spectrometry and peptide microarrays. J. Proteome Res. 7, 3900–3910. [PubMed]
  • Andersson L., Porath J., 1986. Isolation of phosphoproteins by immobilized metal (Fe3+) affinity chromatography. Anal. Biochem. 154, 250–254. [PubMed]
  • Bain J., McLauchlan H., Elliott M., Cohen P., 2003. The specificities of protein kinase inhibitors: an update. Biochem. J. 371, 199–204. [PubMed]
  • Bantscheff M., Eberhard D., Abraham Y., Bastuck S., Boesche M., Hobson S., Mathieson T., Perrin J., Raida M., Rau C., Reader V., Sweetman G., Bauer A., Bouwmeester T., Hopf C., Kruse U., Neubauer G., Ramsden N., Rick J., Kuster B., Drewes G., 2007. Quantitative chemical proteomics reveals mechanisms of action of clinical ABL kinase inhibitors. Nat. Biotechnol. 25, 1035–1044. [PubMed]
  • Barber T.D., Vogelstein B., Kinzler K.W., Velculescu V.E., 2004. Somatic mutations of EGFR in colorectal cancers and glioblastomas. N. Engl. J. Med. 351, 2883 [PubMed]
  • Betts J.C., Blackstock W.P., Ward M.A., Anderton B.H., 1997. Identification of phosphorylation sites on neurofilament proteins by nanoelectrospray mass spectrometry. J. Biol. Chem. 272, 12922–12927. [PubMed]
  • Blume-Jensen P., Hunter T., 2001. Oncogenic kinase signalling. Nature. 411, 355–365. [PubMed]
  • Bose R., Molina H., Patterson A.S., Bitok J.K., Periaswamy B., Bader J.S., Pandey A., Cole P.A., 2006. Phosphoproteomic analysis of Her2/neu signaling and inhibition. Proc. Natl. Acad. Sci. U S A. 103, 9773–9778. [PubMed]
  • Braconi C., Bracci R., Cellerino R., 2008. Molecular targets in gastrointestinal stromal tumors (GIST) therapy. Curr. Cancer Drug Targets. 8, 359–366. [PubMed]
  • Brill L.M., Salomon A.R., Ficarro S.B., Mukherji M., Stettler-Gill M., Peters E.C., 2004. Robust phosphoproteomic profiling of tyrosine phosphorylation sites from human T cells using immobilized metal affinity chromatography and tandem mass spectrometry. Anal. Chem. 76, 2763–2772. [PubMed]
  • Brill L.M., Xiong W., Lee K.B., Ficarro S.B., Crain A., Xu Y., Terskikh A., Snyder E.Y., Ding S., 2009. Phosphoproteomic analysis of human embryonic stem cells. Cell Stem Cell. 5, 204–213. [PubMed]
  • Brugge J.S., Erikson R.L., 1977. Identification of a transformation-specific antigen induced by an avian sarcoma virus. Nature. 269, 346–348. [PubMed]
  • Carr S.A., Huddleston M.J., Annan R.S., 1996. Selective detection and sequencing of phosphopeptides at the femtomole level by mass spectrometry. Anal. Biochem. 239, 180–192. [PubMed]
  • Chen E.I., Yates J.R., 2007. Cancer proteomics by quantitative shotgun proteomics. Mol. Oncol. 1, 144–159. [PubMed]
  • Choudhary C., Olsen J.V., Brandts C., Cox J., Reddy P.N., Bohmer F.D., Gerke V., Schmidt-Arras D.E., Berdel W.E., Muller-Tidow C., Mann M., Serve H., 2009. Mislocalized activation of oncogenic RTKs switches downstream signaling outcomes. Mol. Cell. 36, 326–339. [PubMed]
  • Corless C.L., Fletcher J.A., Heinrich M.C., 2004. Biology of gastrointestinal stromal tumors. J. Clin. Oncol. 22, 3813–3825. [PubMed]
  • Cunningham D.L., Sweet S.M., Cooper H.J., Heath J.K., 2010. Differential phosphoproteomics of fibroblast growth factor signaling: identification of Src family kinase-mediated phosphorylation events. J. Proteome Res. [PMC free article] [PubMed]
  • Daub H., Olsen J.V., Bairlein M., Gnad F., Oppermann F.S., Korner R., Greff Z., Keri G., Stemmann O., Mann M., 2008. Kinase-selective enrichment enables quantitative phosphoproteomics of the kinome across the cell cycle. Mol. Cell. 31, 438–448. [PubMed]
  • Davies S.P., Reddy H., Caivano M., Cohen P., 2000. Specificity and mechanism of action of some commonly used protein kinase inhibitors. Biochem. J. 351, 95–105. [PubMed]
  • Diks S.H., Kok K., O'Toole T., Hommes D.W., van Dijken P., Joore J., Peppelenbosch M.P., 2004. Kinome profiling for studying lipopolysaccharide signal transduction in human peripheral blood mononuclear cells. J. Biol. Chem. 279, 49206–49213. [PubMed]
  • Druker B.J., Talpaz M., Resta D.J., Peng B., Buchdunger E., Ford J.M., Lydon N.B., Kantarjian H., Capdeville R., Ohno-Jones S., Sawyers C.L., 2001. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N. Engl. J. Med. 344, 1031–1037. [PubMed]
  • Druker B.J., Tamura S., Buchdunger E., Ohno S., Segal G.M., Fanning S., Zimmermann J., Lydon N.B., 1996. Effects of a selective inhibitor of the Abl tyrosine kinase on the growth of Bcr-Abl positive cells. Nat. Med. 2, 561–566. [PubMed]
  • Ferrajoli A., Faderl S., Ravandi F., Estrov Z., 2006. The JAK-STAT pathway: a therapeutic target in hematological malignancies. Curr. Cancer Drug Targets. 6, 671–679. [PubMed]
  • Frackelton A.R., Posner M., Kannan B., Mermelstein F., 1991. Generation of monoclonal antibodies against phosphotyrosine and their use for affinity purification of phosphotyrosine-containing proteins. Methods Enzymol. 201, 79–92. [PubMed]
  • Gembitsky D.S., Lawlor K., Jacovina A., Yaneva M., Tempst P., 2004. A prototype antibody microarray platform to monitor changes in protein tyrosine phosphorylation. Mol. Cell Proteomics. 3, 1102–1118. [PubMed]
  • Godl K., Wissing J., Kurtenbach A., Habenberger P., Blencke S., Gutbrod H., Salassidis K., Stein-Gerlach M., Missio A., Cotten M., Daub H., 2003. An efficient proteomics method to identify the cellular targets of protein kinase inhibitors. Proc. Natl. Acad. Sci. U S A. 100, 15434–15439. [PubMed]
  • Golas J.M., Arndt K., Etienne C., Lucas J., Nardin D., Gibbons J., Frost P., Ye F., Boschelli D.H., Boschelli F., 2003. SKI-606, a 4-anilino-3-quinolinecarbonitrile dual inhibitor of Src and Abl kinases, is a potent antiproliferative agent against chronic myelogenous leukemia cells in culture and causes regression of K562 xenografts in nude mice. Cancer Res. 63, 375–381. [PubMed]
  • Gronborg M., Kristiansen T.Z., Stensballe A., Andersen J.S., Ohara O., Mann M., Jensen O.N., Pandey A., 2002. A mass spectrometry-based proteomic approach for identification of serine/threonine-phosphorylated proteins by enrichment with phospho-specific antibodies: identification of a novel protein, Frigg, as a protein kinase A substrate. Mol. Cell Proteomics. 1, 517–527. [PubMed]
  • Guha U., Chaerkady R., Marimuthu A., Patterson A.S., Kashyap M.K., Harsha H.C., Sato M., Bader J.S., Lash A.E., Minna J.D., Pandey A., Varmus H.E., 2008. Comparisons of tyrosine phosphorylated proteins in cells expressing lung cancer-specific alleles of EGFR and KRAS. Proc. Natl. Acad. Sci. U S A. 105, 14112–14117. [PubMed]
  • Gulmann C., Sheehan K.M., Conroy R.M., Wulfkuhle J.D., Espina V., Mullarkey M.J., Kay E.W., Liotta L.A., Petricoin E.F., 2009. Quantitative cell signalling analysis reveals down-regulation of MAPK pathway activation in colorectal cancer. J. Pathol. 218, 514–519. [PubMed]
  • Guo A., Villen J., Kornhauser J., Lee K.A., Stokes M.P., Rikova K., Possemato A., Nardone J., Innocenti G., Wetzel R., Wang Y., MacNeill J., Mitchell J., Gygi S.P., Rush J., Polakiewicz R.D., Comb M.J., 2008. Signaling networks assembled by oncogenic EGFR and c-Met. Proc. Natl. Acad. Sci. U S A. 105, 692–697. [PubMed]
  • Hahn C.K., Berchuck J.E., Ross K.N., Kakoza R.M., Clauser K., Schinzel A.C., Ross L., Galinsky I., Davis T.N., Silver S.J., Root D.E., Stone R.M., DeAngelo D.J., Carroll M., Hahn W.C., Carr S.A., Golub T.R., Kung A.L., Stegmaier K., 2009. Proteomic and genetic approaches identify Syk as an AML target. Cancer Cell. 16, 281–294. [PubMed]
  • Hanahan D., Weinberg R.A., 2000. The hallmarks of cancer. Cell. 100, 57–70. [PubMed]
  • Harsha H.C., Jimeno A., Molina H., Mihalas A.B., Goggins M.G., Hruban R.H., Schulick R.D., Kamath U., Maitra A., Hidalgo M., Pandey A., 2008. Activated epidermal growth factor receptor as a novel target in pancreatic cancer therapy. J. Proteome Res. 7, 4651–4658. [PubMed]
  • Harsha H.C., Molina H., Pandey A., 2008. Quantitative proteomics using stable isotope labeling with amino acids in cell culture. Nat. Protoc. 3, 505–516. [PubMed]
  • Houseman B.T., Huh J.H., Kron S.J., Mrksich M., 2002. Peptide chips for the quantitative evaluation of protein kinase activity. Nat. Biotechnol. 20, 270–274. [PubMed]
  • Huang P.H., Mukasa A., Bonavia R., Flynn R.A., Brewer Z.E., Cavenee W.K., Furnari F.B., White F.M., 2007. Quantitative analysis of EGFRvIII cellular signaling networks reveals a combinatorial therapeutic strategy for glioblastoma. Proc. Natl. Acad. Sci. U S A. 104, 12867–12872. [PubMed]
  • Hudson M.E., Pozdnyakova I., Haines K., Mor G., Snyder M., 2007. Identification of differentially expressed proteins in ovarian cancer using high-density protein microarrays. Proc. Natl. Acad. Sci. U S A. 104, 17494–17499. [PubMed]
  • Hunter T., Cooper J.A., 1985. Protein-tyrosine kinases. Annu. Rev. Biochem. 54, 897–930. [PubMed]
  • Hunter T., Sefton B.M., 1980. Transforming gene product of Rous sarcoma virus phosphorylates tyrosine. Proc. Natl. Acad. Sci. U S A. 77, 1311–1315. [PubMed]
  • Hynes N.E., MacDonald G., 2009. ErbB receptors and signaling pathways in cancer. Curr. Opin. Cell Biol. 21, 177–184. [PubMed]
  • Jorgensen C., Sherman A., Chen G.I., Pasculescu A., Poliakov A., Hsiung M., Larsen B., Wilkinson D.G., Linding R., Pawson T., 2009. Cell-specific information processing in segregating populations of Eph receptor ephrin-expressing cells. Science. 326, 1502–1509. [PubMed]
  • Joughin B.A., Naegle K.M., Huang P.H., Yaffe M.B., Lauffenburger D.A., White F.M., 2009. An integrated comparative phosphoproteomic and bioinformatic approach reveals a novel class of MPM-2 motifs upregulated in EGFRvIII-expressing glioblastoma cells. Mol. Biosyst. 5, 59–67. [PubMed]
  • Kamps M.P., 1991. Generation and use of anti-phosphotyrosine antibodies for immunoblotting. Methods Enzymol. 201, 101–110. [PubMed]
  • Kane S., Sano H., Liu S.C., Asara J.M., Lane W.S., Garner C.C., Lienhard G.E., 2002. A method to identify serine kinase substrates. Akt phosphorylates a novel adipocyte protein with a Rab GTPase-activating protein (GAP) domain. J. Biol. Chem. 277, 22115–22118. [PubMed]
  • Karasarides M., Chiloeches A., Hayward R., Niculescu-Duvaz D., Scanlon I., Friedlos F., Ogilvie L., Hedley D., Martin J., Marshall C.J., Springer C.J., Marais R., 2004. B-RAF is a therapeutic target in melanoma. Oncogene. 23, 6292–6298. [PubMed]
  • Kingsmore S.F., 2006. Multiplexed protein measurement: technologies and applications of protein and antibody arrays. Nat. Rev. Drug Discov. 5, 310–320. [PubMed]
  • Knight Z.A., Lin H., Shokat K.M., 2010. Targeting the cancer kinome through polypharmacology. Nat. Rev. Cancer. 10, 130–137. [PubMed]
  • Kruger M., Kratchmarova I., Blagoev B., Tseng Y.H., Kahn C.R., Mann M., 2008. Dissection of the insulin signaling pathway via quantitative phosphoproteomics. Proc. Natl. Acad. Sci. U S A. 105, 2451–2456. [PubMed]
  • Krystal G.W., Honsawek S., Litz J., Buchdunger E., 2000. The selective tyrosine kinase inhibitor STI571 inhibits small cell lung cancer growth. Clin. Cancer Res. 6, 3319–3326. [PubMed]
  • Kubota K., Anjum R., Yu Y., Kunz R.C., Andersen J.N., Kraus M., Keilhack H., Nagashima K., Krauss S., Paweletz C., Hendrickson R.C., Feldman A.S., Wu C.L., Rush J., Villen J., Gygi S.P., 2009. Sensitive multiplexed analysis of kinase activities and activity-based kinase identification. Nat. Biotechnol. 27, 933–940. [PubMed]
  • Larive R.M., Urbach S., Poncet J., Jouin P., Mascre G., Sahuquet A., Mangeat P.H., Coopman P.J., Bettache N., 2009. Phosphoproteomic analysis of Syk kinase signaling in human cancer cells reveals its role in cell-cell adhesion. Oncogene. 28, 2337–2347. [PubMed]
  • Larsen M.R., Thingholm T.E., Jensen O.N., Roepstorff P., Jorgensen T.J., 2005. Highly selective enrichment of phosphorylated peptides from peptide mixtures using titanium dioxide microcolumns. Mol. Cell Proteomics. 4, 873–886. [PubMed]
  • Lee J.T., Lehmann B.D., Terrian D.M., Chappell W.H., Stivala F., Libra M., Martelli A.M., Steelman L.S., McCubrey J.A., 2008. Targeting prostate cancer based on signal transduction and cell cycle pathways. Cell Cycle. 7, 1745–1762. [PubMed]
  • Leroy C., Fialin C., Sirvent A., Simon V., Urbach S., Poncet J., Robert B., Jouin P., Roche S., 2009. Quantitative phosphoproteomics reveals a cluster of tyrosine kinases that mediates SRC invasive activity in advanced colon carcinoma cells. Cancer Res. 69, 2279–2286. [PubMed]
  • Levin V.A., Panchabhai S.C., Shen L., Kornblau S.M., Qiu Y., Baggerly K.A., 2010. Different changes in protein and phosphoprotein levels result from serum starvation of high-grade glioma and adenocarcinoma cell lines. J. Proteome Res. 9, 179–191. [PubMed]
  • Levinson A.D., Oppermann H., Levintow L., Varmus H.E., Bishop J.M., 1978. Evidence that the transforming gene of avian sarcoma virus encodes a protein kinase associated with a phosphoprotein. Cell. 15, 561–572. [PubMed]
  • Li H., Ren Z., Kang X., Zhang L., Li X., Wang Y., Xue T., Shen Y., Liu Y., 2009. Identification of tyrosine-phosphorylated proteins associated with metastasis and functional analysis of FER in human hepatocellular carcinoma cells. BMC Cancer. 9, 366 [PubMed]
  • Liao P.C., Leykam J., Andrews P.C., Gage D.A., Allison J., 1994. An approach to locate phosphorylation sites in a phosphoprotein: mass mapping by combining specific enzymatic degradation with matrix-assisted laser desorption/ionization mass spectrometry. Anal. Biochem. 219, 9–20. [PubMed]
  • Loyet K.M., Stults J.T., Arnott D., 2005. Mass spectrometric contributions to the practice of phosphorylation site mapping through 2003: a literature review. Mol. Cell Proteomics. 4, 235–245. [PubMed]
  • Luo W., Slebos R.J., Hill S., Li M., Brabek J., Amanchy R., Chaerkady R., Pandey A., Ham A.J., Hanks S.K., 2008. Global impact of oncogenic Src on a phosphotyrosine proteome. J. Proteome Res. 7, 3447–3460. [PubMed]
  • Lynch T.J., Bell D.W., Sordella R., Gurubhagavatula S., Okimoto R.A., Brannigan B.W., Harris P.L., Haserlat S.M., Supko J.G., Haluska F.G., Louis D.N., Christiani D.C., Settleman J., Haber D.A., 2004. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139. [PubMed]
  • Ma Y., Lu Y., Zeng H., Ron D., Mo W., Neubert T.A., 2001. Characterization of phosphopeptides from protein digests using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and nanoelectrospray quadrupole time-of-flight mass spectrometry. Rapid Commun. Mass Spectrom. 15, 1693–1700. [PubMed]
  • Manning G., Whyte D.B., Martinez R., Hunter T., Sudarsanam S., 2002. The protein kinase complement of the human genome. Science. 298, 1912–1934. [PubMed]
  • Matsuoka S., Ballif B.A., Smogorzewska A., McDonald E.R., Hurov K.E., Luo J., Bakalarski C.E., Zhao Z., Solimini N., Lerenthal Y., Shiloh Y., Gygi S.P., Elledge S.J., 2007. ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage. Science. 316, 1160–1166. [PubMed]
  • McNulty D.E., Annan R.S., 2008. Hydrophilic interaction chromatography reduces the complexity of the phosphoproteome and improves global phosphopeptide isolation and detection. Mol. Cell Proteomics. 7, 971–980. [PubMed]
  • Molina H., Horn D.M., Tang N., Mathivanan S., Pandey A., 2007. Global proteomic profiling of phosphopeptides using electron transfer dissociation tandem mass spectrometry. Proc. Natl. Acad. Sci. U S A. 104, 2199–2204. [PubMed]
  • Muszynska G., Dobrowolska G., Medin A., Ekman P., Porath J.O., 1992. Model studies on iron(III) ion affinity chromatography. II. Interaction of immobilized iron(III) ions with phosphorylated amino acids, peptides and proteins. J. Chromatogr. 604, 19–28. [PubMed]
  • Nguyen V., Cao L., Lin J.T., Hung N., Ritz A., Yu K., Jianu R., Ulin S.P., Raphael B.J., Laidlaw D.H., Brossay L., Salomon A.R., 2009. A new approach for quantitative phosphoproteomic dissection of signaling pathways applied to T cell receptor activation. Mol. Cell Proteomics. 8, 2418–2431. [PubMed]
  • Oda Y., Nagasu T., Chait B.T., 2001. Enrichment analysis of phosphorylated proteins as a tool for probing the phosphoproteome. Nat. Biotechnol. 19, 379–382. [PubMed]
  • Old W.M., Shabb J.B., Houel S., Wang H., Couts K.L., Yen C.Y., Litman E.S., Croy C.H., Meyer-Arendt K., Miranda J.G., Brown R.A., Witze E.S., Schweppe R.E., Resing K.A., Ahn N.G., 2009. Functional proteomics identifies targets of phosphorylation by B-Raf signaling in melanoma. Mol. Cell. 34, 115–131. [PubMed]
  • Olsen J.V., Blagoev B., Gnad F., Macek B., Kumar C., Mortensen P., Mann M., 2006. Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. Cell. 127, 635–648. [PubMed]
  • Oppermann F.S., Gnad F., Olsen J.V., Hornberger R., Greff Z., Keri G., Mann M., Daub H., 2009. Large-scale proteomics analysis of the human kinome. Mol. Cell Proteomics. 8, 1751–1764. [PubMed]
  • Ostasiewicz P., Zielinska D.F., Mann M., Wisniewski J.R., 2010. Proteome, phosphoproteome, and N-glycoproteome are quantitatively preserved in formalin-fixed paraffin-embedded tissue and analyzable by high-resolution mass spectrometry. J. Proteome Res. 9, 3688–3700. [PubMed]
  • Osterberg R., 1957. Metal and hydrogen-ion binding properties of o-phosphoserine. Nature. 179, 476–477. [PubMed]
  • Pan C., Olsen J.V., Daub H., Mann M., 2009. Global effects of kinase inhibitors on signaling networks revealed by quantitative phosphoproteomics. Mol. Cell Proteomics. 8, 2796–2808. [PubMed]
  • Parsons D.W., Wang T.L., Samuels Y., Bardelli A., Cummins J.M., DeLong L., Silliman N., Ptak J., Szabo S., Willson J.K., Markowitz S., Kinzler K.W., Vogelstein B., Lengauer C., Velculescu V.E., 2005. Colorectal cancer: mutations in a signalling pathway. Nature. 436, 792 [PubMed]
  • Paweletz C.P., Charboneau L., Bichsel V.E., Simone N.L., Chen T., Gillespie J.W., Emmert-Buck M.R., Roth M.J., Petricoin I.E., Liotta L.A., 2001. Reverse phase protein microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front. Oncogene. 20, 1981–1989. [PubMed]
  • Pinkse M.W., Uitto P.M., Hilhorst M.J., Ooms B., Heck A.J., 2004. Selective isolation at the femtomole level of phosphopeptides from proteolytic digests using 2D-NanoLC-ESI-MS/MS and titanium oxide precolumns. Anal. Chem. 76, 3935–3943. [PubMed]
  • Posewitz M.C., Tempst P., 1999. Immobilized gallium(III) affinity chromatography of phosphopeptides. Anal. Chem. 71, 2883–2892. [PubMed]
  • Ptacek J., Devgan G., Michaud G., Zhu H., Zhu X., Fasolo J., Guo H., Jona G., Breitkreutz A., Sopko R., McCartney R.R., Schmidt M.C., Rachidi N., Lee S.J., Mah A.S., Meng L., Stark M.J., Stern D.F., De Virgilio C., Tyers M., Andrews B., Gerstein M., Schweitzer B., Predki P.F., Snyder M., 2005. Global analysis of protein phosphorylation in yeast. Nature. 438, 679–684. [PubMed]
  • Rabindran S.K., Discafani C.M., Rosfjord E.C., Baxter M., Floyd M.B., Golas J., Hallett W.A., Johnson B.D., Nilakantan R., Overbeek E., Reich M.F., Shen R., Shi X., Tsou H.R., Wang Y.F., Wissner A., 2004. Antitumor activity of HKI-272, an orally active, irreversible inhibitor of the HER-2 tyrosine kinase. Cancer Res. 64, 3958–3965. [PubMed]
  • Remsing Rix L.L., Rix U., Colinge J., Hantschel O., Bennett K.L., Stranzl T., Muller A., Baumgartner C., Valent P., Augustin M., Till J.H., Superti-Furga G., 2009. Global target profile of the kinase inhibitor bosutinib in primary chronic myeloid leukemia cells. Leukemia. 23, 477–485. [PubMed]
  • Rikova K., Guo A., Zeng Q., Possemato A., Yu J., Haack H., Nardone J., Lee K., Reeves C., Li Y., Hu Y., Tan Z., Stokes M., Sullivan L., Mitchell J., Wetzel R., Macneill J., Ren J.M., Yuan J., Bakalarski C.E., Villen J., Kornhauser J.M., Smith B., Li D., Zhou X., Gygi S.P., Gu T.L., Polakiewicz R.D., Rush J., Comb M.J., 2007. Global survey of phosphotyrosine signaling identifies oncogenic kinases in lung cancer. Cell. 131, 1190–1203. [PubMed]
  • Rix U., Hantschel O., Durnberger G., Remsing Rix L.L., Planyavsky M., Fernbach N.V., Kaupe I., Bennett K.L., Valent P., Colinge J., Kocher T., Superti-Furga G., 2007. Chemical proteomic profiles of the BCR-ABL inhibitors imatinib, nilotinib, and dasatinib reveal novel kinase and nonkinase targets. Blood. 110, 4055–4063. [PubMed]
  • Rix U., Remsing Rix L.L., Terker A.S., Fernbach N.V., Hantschel O., Planyavsky M., Breitwieser F.P., Herrmann H., Colinge J., Bennett K.L., Augustin M., Till J.H., Heinrich M.C., Valent P., Superti-Furga G., 2010. A comprehensive target selectivity survey of the BCR-ABL kinase inhibitor INNO-406 by kinase profiling and chemical proteomics in chronic myeloid leukemia cells. Leukemia. 24, 44–50. [PubMed]
  • Ross P.L., Huang Y.N., Marchese J.N., Williamson B., Parker K., Hattan S., Khainovski N., Pillai S., Dey S., Daniels S., Purkayastha S., Juhasz P., Martin S., Bartlet-Jones M., He F., Jacobson A., Pappin D.J., 2004. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell Proteomics. 3, 1154–1169. [PubMed]
  • Ruse C.I., McClatchy D.B., Lu B., Cociorva D., Motoyama A., Park S.K., Yates J.R., 2008. Motif-specific sampling of phosphoproteomes. J. Proteome Res. 7, 2140–2150. [PubMed]
  • Rush J., Moritz A., Lee K.A., Guo A., Goss V.L., Spek E.J., Zhang H., Zha X.M., Polakiewicz R.D., Comb M.J., 2005. Immunoaffinity profiling of tyrosine phosphorylation in cancer cells. Nat. Biotechnol. 23, 94–101. [PubMed]
  • Salomon A.R., Ficarro S.B., Brill L.M., Brinker A., Phung Q.T., Ericson C., Sauer K., Brock A., Horn D.M., Schultz P.G., Peters E.C., 2003. Profiling of tyrosine phosphorylation pathways in human cells using mass spectrometry. Proc. Natl. Acad. Sci. U S A. 100, 443–448. [PubMed]
  • Sano A., Nakamura H., 2004. Titania as a chemo-affinity support for the column-switching HPLC analysis of phosphopeptides: application to the characterization of phosphorylation sites in proteins by combination with protease digestion and electrospray ionization mass spectrometry. Anal. Sci. 20, 861–864. [PubMed]
  • Sefton B.M., 1986. The viral tyrosine protein kinases. Curr. Top. Microbiol. Immunol. 123, 39–72. [PubMed]
  • Sefton B.M., Hunter T., Beemon K., Eckhart W., 1980. Evidence that the phosphorylation of tyrosine is essential for cellular transformation by Rous sarcoma virus. Cell. 20, 807–816. [PubMed]
  • Sefton B.M., Hunter T., Raschke W.C., 1981. Evidence that the Abelson virus protein functions in vivo as a protein kinase that phosphorylates tyrosine. Proc. Natl. Acad. Sci. U S A. 78, 1552–1556. [PubMed]
  • Sharma S.V., Bell D.W., Settleman J., Haber D.A., 2007. Epidermal growth factor receptor mutations in lung cancer. Nat. Rev. Cancer. 7, 169–181. [PubMed]
  • Sheehan K.M., Calvert V.S., Kay E.W., Lu Y., Fishman D., Espina V., Aquino J., Speer R., Araujo R., Mills G.B., Liotta L.A., Petricoin E.F., Wulfkuhle J.D., 2005. Use of reverse phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma. Mol. Cell Proteomics. 4, 346–355. [PubMed]
  • Shin J.S., Hong S.W., Lee S.L., Kim T.H., Park I.C., An S.K., Lee W.K., Lim J.S., Kim K.I., Yang Y., Lee S.S., Jin D.H., Lee M.S., 2008. Serum starvation induces G1 arrest through suppression of Skp2-CDK2 and CDK4 in SK-OV-3 cells. Int. J. Oncol. 32, 435–439. [PubMed]
  • Spector D.H., Varmus H.E., Bishop J.M., 1978. Nucleotide sequences related to the transforming gene of avian sarcoma virus are present in DNA of uninfected vertebrates. Proc. Natl. Acad. Sci. U S A. 75, 4102–4106. [PubMed]
  • Stehelin D., Guntaka R.V., Varmus H.E., Bishop J.M., 1976. Purification of DNA complementary to nucleotide sequences required for neoplastic transformation of fibroblasts by avian sarcoma viruses. J. Mol. Biol. 101, 349–365. [PubMed]
  • Stensballe A., Andersen S., Jensen O.N., 2001. Characterization of phosphoproteins from electrophoretic gels by nanoscale Fe(III) affinity chromatography with off-line mass spectrometry analysis. Proteomics. 1, 207–222. [PubMed]
  • Stephens P., Edkins S., Davies H., Greenman C., Cox C., Hunter C., Bignell G., Teague J., Smith R., Stevens C., O'Meara S., Parker A., Tarpey P., Avis T., Barthorpe A., Brackenbury L., Buck G., Butler A., Clements J., Cole J., Dicks E., Edwards K., Forbes S., Gorton M., Gray K., Halliday K., Harrison R., Hills K., Hinton J., Jones D., Kosmidou V., Laman R., Lugg R., Menzies A., Perry J., Petty R., Raine K., Shepherd R., Small A., Solomon H., Stephens Y., Tofts C., Varian J., Webb A., West S., Widaa S., Yates A., Brasseur F., Cooper C.S., Flanagan A.M., Green A., Knowles M., Leung S.Y., Looijenga L.H., Malkowicz B., Pierotti M.A., Teh B., Yuen S.T., Nicholson A.G., Lakhani S., Easton D.F., Weber B.L., Stratton M.R., Futreal P.A., Wooster R., 2005. A screen of the complete protein kinase gene family identifies diverse patterns of somatic mutations in human breast cancer. Nat. Genet. 37, 590–592. [PubMed]
  • Stokes M.P., Rush J., Macneill J., Ren J.M., Sprott K., Nardone J., Yang V., Beausoleil S.A., Gygi S.P., Livingstone M., Zhang H., Polakiewicz R.D., Comb M.J., 2007. Profiling of UV-induced ATM/ATR signaling pathways. Proc. Natl. Acad. Sci. U S A. 104, 19855–19860. [PubMed]
  • Swaney D.L., Wenger C.D., Thomson J.A., Coon J.J., 2009. Human embryonic stem cell phosphoproteome revealed by electron transfer dissociation tandem mass spectrometry. Proc. Natl. Acad. Sci. U S A. 106, 995–1000. [PubMed]
  • Unwin R.D., Griffiths J.R., Leverentz M.K., Grallert A., Hagan I.M., Whetton A.D., 2005. Multiple reaction monitoring to identify sites of protein phosphorylation with high sensitivity. Mol. Cell Proteomics. 4, 1134–1144. [PubMed]
  • Van Hoof D., Munoz J., Braam S.R., Pinkse M.W., Linding R., Heck A.J., Mummery C.L., Krijgsveld J., 2009. Phosphorylation dynamics during early differentiation of human embryonic stem cells. Cell Stem Cell. 5, 214–226. [PubMed]
  • Versele M., Talloen W., Rockx C., Geerts T., Janssen B., Lavrijssen T., King P., Gohlmann H.W., Page M., Perera T., 2009. Response prediction to a multitargeted kinase inhibitor in cancer cell lines and xenograft tumors using high-content tyrosine peptide arrays with a kinetic readout. Mol. Cancer Ther. 8, 1846–1855. [PubMed]
  • Walters D.K., Goss V.L., Stoffregen E.P., Gu T.L., Lee K., Nardone J., McGreevey L., Heinrich M.C., Deininger M.W., Polakiewicz R., Druker B.J., 2006. Phosphoproteomic analysis of AML cell lines identifies leukemic oncogenes. Leuk. Res. 30, 1097–1104. [PubMed]
  • Walters D.K., Mercher T., Gu T.L., O'Hare T., Tyner J.W., Loriaux M., Goss V.L., Lee K.A., Eide C.A., Wong M.J., Stoffregen E.P., McGreevey L., Nardone J., Moore S.A., Crispino J., Boggon T.J., Heinrich M.C., Deininger M.W., Polakiewicz R.D., Gilliland D.G., Druker B.J., 2006. Activating alleles of JAK3 in acute megakaryoblastic leukemia. Cancer Cell. 10, 65–75. [PubMed]
  • Wang J.Y., 1988. Antibodies for phosphotyrosine: analytical and preparative tool for tyrosyl-phosphorylated proteins. Anal. Biochem. 172, 1–7. [PubMed]
  • Witte O.N., Dasgupta A., Baltimore D., 1980. Abelson murine leukaemia virus protein is phosphorylated in vitro to form phosphotyrosine. Nature. 283, 826–831. [PubMed]
  • Wolf-Yadlin A., Hautaniemi S., Lauffenburger D.A., White F.M., 2007. Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks. Proc. Natl. Acad. Sci. U S A. 104, 5860–5865. [PubMed]
  • Wulfkuhle J.D., Aquino J.A., Calvert V.S., Fishman D.A., Coukos G., Liotta L.A., Petricoin E.F., 2003. Signal pathway profiling of ovarian cancer from human tissue specimens using reverse-phase protein microarrays. Proteomics. 3, 2085–2090. [PubMed]
  • Xia Q., Cheng D., Duong D.M., Gearing M., Lah J.J., Levey A.I., Peng J., 2008. Phosphoproteomic analysis of human brain by calcium phosphate precipitation and mass spectrometry. J. Proteome Res. 7, 2845–2851. [PubMed]
  • Xia W., Mullin R.J., Keith B.R., Liu L.H., Ma H., Rusnak D.W., Owens G., Alligood K.J., Spector N.L., 2002. Anti-tumor activity of GW572016: a dual tyrosine kinase inhibitor blocks EGF activation of EGFR/erbB2 and downstream Erk1/2 and AKT pathways. Oncogene. 21, 6255–6263. [PubMed]
  • Yip T.T., Hutchens T.W., 1992. Mapping and sequence-specific identification of phosphopeptides in unfractionated protein digest mixtures by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. FEBS Lett. 308, 149–153. [PubMed]
  • Zander L., Bemark M., 2008. Identification of genes deregulated during serum-free medium adaptation of a Burkitt's lymphoma cell line. Cell Prolif. 41, 136–155. [PubMed]
  • Zanivan S., Gnad F., Wickstrom S.A., Geiger T., Macek B., Cox J., Fassler R., Mann M., 2008. Solid tumor proteome and phosphoproteome analysis by high resolution mass spectrometry. J. Proteome Res. 7, 5314–5326. [PubMed]
  • Zhang G., Neubert T.A., 2009. Use of stable isotope labeling by amino acids in cell culture (SILAC) for phosphotyrosine protein identification and quantitation. Methods Mol. Biol. 527, 79–92. xi [PubMed]
  • Zhang G., Spellman D.S., Skolnik E.Y., Neubert T.A., 2006. Quantitative phosphotyrosine proteomics of EphB2 signaling by stable isotope labeling with amino acids in cell culture (SILAC). J. Proteome Res. 5, 581–588. [PubMed]
  • Zhang X., Ye J., Jensen O.N., Roepstorff P., 2007. Highly efficient phosphopeptide enrichment by calcium phosphate precipitation combined with Subsequent IMAC enrichment. Mol. Cell Proteomics. 6, 2032–2042. [PubMed]
  • Zhang Y., Wolf-Yadlin A., Ross P.L., Pappin D.J., Rush J., Lauffenburger D.A., White F.M., 2005. Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules. Mol. Cell Proteomics. 4, 1240–1250. [PubMed]
  • Zhong D., Liu X., Khuri F.R., Sun S.Y., Vertino P.M., Zhou W., 2008. LKB1 is necessary for Akt-mediated phosphorylation of proapoptotic proteins. Cancer Res. 68, 7270–7277. [PubMed]
  • Zhong D., Xiong L., Liu T., Liu X., Liu X., Chen J., Sun S.Y., Khuri F.R., Zong Y., Zhou Q., Zhou W., 2009. The glycolytic inhibitor 2-deoxyglucose activates multiple prosurvival pathways through IGF1R. J. Biol. Chem. 284, 23225–23233. [PubMed]
  • Zhou H., Watts J.D., Aebersold R., 2001. A systematic approach to the analysis of protein phosphorylation. Nat. Biotechnol. 19, 375–378. [PubMed]

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