Phosphoproteomic analysis of signaling pathways in head and neck squamous cell carcinoma patient samples

Translational Regulation by eIFs and RNA Modifications in Cancer

Translation is a fundamental process in all living organisms that involves the decoding of genetic information in mRNA by ribosomes and translation factors. The dysregulation of mRNA translation is a common feature of tumorigenesis. Protein expression reflects the total outcome of multiple regulatory mechanisms that change the metabolism of mRNA pathways from synthesis to degradation. Accumulated evidence has clarified the role of an increasing amount of mRNA modifications at each phase of the pathway, resulting in translational output. Translation machinery is directly affected by mRNA modifications, influencing translation initiation, elongation, and termination or altering mRNA abundance and subcellular localization. In this review, we focus on the translation initiation factors associated with cancer as well as several important RNA modifications, for which we describe their association with cancer.

Analyzing tyrosine kinase activity in head and neck cancer by functional kinomics: Identification of hyperactivated Src family kinases as prognostic markers and potential targets

Signal transduction via protein kinases is of central importance in cancer biology and treatment. However, the clinical success of kinase inhibitors is often hampered by a lack of robust predictive biomarkers, which is also caused by the discrepancy between kinase expression and activity. Therefore, there is a need for functional tests to identify aberrantly activated kinases in individual patients. Here we present a systematic analysis of the tyrosine kinases in head and neck cancer using such a test-functional kinome profiling. We detected increased tyrosine kinase activity in tumors compared with their corresponding normal tissue. Moreover, we identified members of the family of Src kinases (Src family kinases [SFK]) to be aberrantly activated in the majority of the tumors, which was confirmed by additional methods. We could also show that SFK hyperphosphorylation is associated with poor prognosis, while inhibition of SFK impaired cell proliferation, especially in cells with hyperactive SFK. In summary, functional kinome profiling identified SFK to be frequently hyperactivated in head and neck squamous cell carcinoma. SFK may therefore be potential therapeutic targets. These results furthermore demonstrate how functional tests help to increase our understanding of cancer biology and support the expansion of precision oncology.

Cotargeting CHK1 and PI3K Synergistically Suppresses Tumor Growth of Oral Cavity Squamous Cell Carcinoma in Patient-Derived Xenografts

Oral cavity squamous cell carcinomas (OSCCs) are aggressive tumors, and their recurrence leads to poor prognosis and reduced survival rates. This study aimed to identify therapeutic targets and to evaluate the efficacy of targeted inhibitors in OSCC patient-derived xenograft (PDX) models. Herein, we reported that OSCC PDXs recapitulated the genomic signatures of their paired primary tumors and the expression of CHEK1, PIK3CA, and PIK3CD was significantly upregulated in OSCC. The antitumor efficacy of CHK1 inhibitors (PF477736, AZD7762, LY2606368) and PI3K inhibitors (BYL719, GDC0941, GSK1059615) was investigated in OSCC cell lines and PDX models. Targeting either CHK1 or PI3K effectively inhibited cell proliferation and colony formation by inducing cell cycle arrest and apoptosis in in vitro cell-based assays. Cisplatin-based chemotherapy combined with CHK1 inhibitor treatment synergistically inhibited cell proliferation by suppressing CHK1 phosphorylation and inducing PARP cleavage. Furthermore, compared with monotherapy, cotreatment with CHK1 and PI3K inhibitors exerted synergistic anticancer effects by suppressing CHK1, AKT, and 4E-BP1 phosphorylation. In summary, our study identified CHK1 and PI3K as promising targets, especially in a dual treatment strategy combining a CHK1 inhibitor with cisplatin or a PI3K inhibitor as a novel therapeutic approach for OSCC patients with aberrant cell cycle regulation and PI3K signaling activation.

Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors

Background

Breast cancer tumors are known to be highly heterogeneous and differences in their metabolic phenotypes, especially at protein level, are less well-understood. Profiling of metabolism-related proteins harbors the potential to establish new patient stratification regimes and biomarkers promoting individualized therapy. In our study, we aimed to examine the relationship between metabolism-associated protein expression profiles and clinicopathological characteristics in a large cohort of breast cancer patients.

Methods

Breast cancer specimens from 801 consecutive patients, diagnosed between 2009 and 2011, were investigated using reverse phase protein arrays (RPPA). Patients were treated in accordance with national guidelines in five certified German breast centers. To obtain quantitative expression data, 37 antibodies detecting proteins relevant to cancer metabolism, were applied. Hierarchical cluster analysis and individual target characterization were performed. Clustering results and individual protein expression patterns were associated with clinical data. The Kaplan-Meier method was used to estimate survival functions. Univariate and multivariate Cox regression models were applied to assess the impact of protein expression and other clinicopathological features on survival.

Results

We identified three metabolic clusters of breast cancer, which do not reflect the receptor-defined subtypes, but are significantly correlated with overall survival (OS, p ≤ 0.03) and recurrence-free survival (RFS, p ≤ 0.01). Furthermore, univariate and multivariate analysis of individual protein expression profiles demonstrated the central role of serine hydroxymethyltransferase 2 (SHMT2) and amino acid transporter ASCT2 (SLC1A5) as independent prognostic factors in breast cancer patients. High SHMT2 protein expression was significantly correlated with poor OS (hazard ratio (HR) = 1.53, 95% confidence interval (CI) = 1.10–2.12, p ≤ 0.01) and RFS (HR = 1.54, 95% CI = 1.16–2.04, p ≤ 0.01). High protein expression of ASCT2 was significantly correlated with poor RFS (HR = 1.31, 95% CI = 1.01–1.71, p ≤ 0.05).

Conclusions

Our data confirm the heterogeneity of breast tumors at a functional proteomic level and dissects the relationship between metabolism-related proteins, pathological features and patient survival. These observations highlight the importance of SHMT2 and ASCT2 as valuable individual prognostic markers and potential targets for personalized breast cancer therapy.

Trial registration

ClinicalTrials.gov, NCT01592825. Registered on 3 May 2012.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0905-7) contains supplementary material, which is available to authorized users.

Eukaryotic translation initiation factors and cancer

Recent technological advancements have shown tremendous mechanistic accomplishments in our understanding of the mechanism of messenger RNA translation in eukaryotic cells. Eukaryotic messenger RNA translation is very complex process that includes four phases (initiation, elongation, termination, and ribosome recycling) and diverse mechanisms involving protein and non-protein molecules. Translation regulation is principally achieved during initiation step of translation, which is organized by multiple eukaryotic translation initiation factors. Eukaryotic translation initiation factor proteins help in stabilizing the formation of the functional ribosome around the start codon and provide regulatory mechanisms in translation initiation. Dysregulated messenger RNA translation is a common feature of tumorigenesis. Various oncogenic and tumor suppressive genes affect/are affected by the translation machinery, making the components of the translation apparatus promising therapeutic targets for the novel anticancer drug. This review provides details on the role of eukaryotic translation initiation factors in messenger RNA translation initiation, their contribution to onset and progression of tumor, and how dysregulated eukaryotic translation initiation factors can be used as a target to treat carcinogenesis.

Combining Chk1/2 Inhibition with Cetuximab and Radiation Enhances In Vitro and In Vivo Cytotoxicity in Head and Neck Squamous Cell Carcinoma

EGFR inhibition and radiotherapy are potent inducers of DNA damage. Checkpoint kinases 1 and 2 (Chk1/2) are critical regulators of the DNA-damage response, controlling cell-cycle checkpoints that may permit recovery from therapy-associated genomic stress. We hypothesized that Chk1/2 inhibition (CHKi) with prexasertib may enhance cytotoxicity from EGFR inhibition plus radiotherapy in head and neck squamous cell carcinoma (HNSCC). In this study, we found that the addition of CHKi to the EGFR inhibitor cetuximab with and without radiotherapy significantly decreased cell proliferation and survival fraction in human papillomavirus virus (HPV)-positive and HPV-negative HNSCC cell lines. Reduced proliferation was accompanied by decreased checkpoint activation, induced S-phase accumulation, persistent DNA damage, and increased caspase cleavage and apoptosis. Importantly, a significant tumor growth delay was observed in vivo in both HPV-positive and HPV-negative cell line xenografts receiving triple combination therapy with CHKi, cetuximab, and radiotherapy without a concomitant increase in toxicity as assessed by mouse body weight. Taken together, the combination of CHKi with cetuximab plus irradiation displayed significant antitumor effects in HNSCCs both in vitro and in vivo, suggesting that this combination therapy may increase clinical benefit. A clinical trial to test this treatment for patients with head and neck cancer is currently ongoing (NCT02555644).

Novel biomarkers of nasopharyngeal carcinoma metastasis risk identified by reverse phase protein array based tumor profiling with consideration of plasma Epstein-Barr virus DNA load

PURPOSE

In patients with Epstein-Barr virus (EBV) associated nasopharyngeal carcinoma (NPC), intertumor heterogeneity causes interpatient heterogeneity in the risk of distant metastasis. We aimed to identify novel biomarkers of metastasis risk using reverse phase protein array (RPPA) profiling of NPC patients at risk for metastasis and considering plasma EBV DNA load.

EXPERIMENTAL DESIGN

A total of 98 patients with NPC with and without metastasis after treatment, matched with respect to clinical parameters, are enrolled. Total protein expression is measured by RPPA, and protein functions are analyzed by pathway bioinformatics.

RESULTS

The RPPA analysis revealed a profile of 70 proteins that are differentially expressed in metastatic and nonmetastatic tumors. Plasma EBV DNA load after treatment correlated with protein expression level better than plasma EBV DNA load before treatment did. The biomarkers of NPC metastasis identified by proteomics regulate signaling pathways involved in cell cycle progression, apoptosis, and epithelial-mesenchymal transition. The authors identified 26 biomarkers associated with 5-year distant failure-free survival in univariate analysis; five biomarkers remained significant in multivariate analysis.

CONCLUSIONS AND CLINICAL RELEVANCE

A comprehensive RPPA profiling study is warranted to identify novel metastasis-related biomarkers and further examine the activation state of signaling proteins to improve estimation of metastasis risk for patients with EBV-associated NPC.

Models for predicting stage in head and neck squamous cell carcinoma using proteomic data

Head and neck squamous cell carcinoma (HNSCC) that is detected at an advanced stage is associated with much worse patient outcomes than if detected at early stages. This study uses reverse phase protein array (RPPA) data to build predictive models that discriminate between early and advanced stage HNSCC. Individual and ensemble binary classifiers, using filter-based and wrapper-based feature selection, are used to build several models which achieve moderate MCC and AUC values. This study identifies informative protein feature sets which may contribute to an increased understanding of the molecular basis of HNSCC.

Comprehensive molecular tumor profiling in radiation oncology: How it could be used for precision medicine

New technologies enabling the analysis of various molecules, including DNA, RNA, proteins and small metabolites, can aid in understanding the complex molecular processes in cancer cells. In particular, for the use of novel targeted therapeutics, elucidation of the mechanisms leading to cell death or survival is crucial to eliminate tumor resistance and optimize therapeutic efficacy. While some techniques, such as genomic analysis for identifying specific gene mutations or epigenetic testing of promoter methylation, are already in clinical use, other "omics-based" assays are still evolving. Here, we provide an overview of the current status of molecular profiling methods, including promising research strategies, as well as possible challenges, and their emerging role in radiation oncology.

Clinical utility of reverse phase protein array for molecular classification of breast cancer

Reverse Phase Protein Array (RPPA) represents a sensitive and high-throughput technique allowing simultaneous quantitation of protein expression levels in biological samples. This study aimed to confirm the ability of RPPA to classify archival formalin-fixed paraffin-embedded (FFPE) breast cancer tissues into molecular classes used in the Nottingham prognostic index plus (NPI+) determined by immunohistochemistry (IHC). Proteins were extracted from FFPE breast cancer tissues using three extraction protocols: the Q-proteome FFPE Tissue Kit (Qiagen, Hilden, Germany) and two in-house methods using Laemmli buffer with either incubation for 20 min or 2 h at 105 °C. Two preparation methods, full-face sections and macrodissection, were used to assess the yield and quality of protein extracts. Ten biomarkers used for the NPI+ (ER, PgR, HER2, Cytokeratins 5/6 and 7/8, EGFR, HER3, HER4, p53 and Mucin 1) were quantified using RPPA and compared to results determined by IHC. The Q-proteome FFPE Tissue Kit produced significantly higher protein concentration and signal intensities. The intra- and inter-array reproducibility assessment indicated that RPPA using FFPE lysates was a highly reproducible and robust technique. Expression of the biomarkers individually and in combination using RPPA was highly consistent with IHC results. Macrodissection of the invasive tumour component gave more reliable results with the majority of biomarkers determined by IHC, (80 % concordance) compared with full-face sections (60 % concordance). Our results provide evidence for the technical feasibility of RPPA for high-throughput protein expression profiling of FFPE breast cancer tissues. The sensitivity of the technique is related to the quality of extracted protein and purity of tumour tissue. RPPA could provide a quantitative technique alternative to IHC for the biomarkers used in the NPI+.

Models for Predicting Stage in Head and Neck Squamous Cell Carcinoma Using Proteomic and Transcriptomic Data

Late diagnosis is one of the reasons that head and neck squamous cell carcinoma (HNSCC) patients experience relative five-year survival rates ranging from 40%-66%. The molecular-level differences between early and advanced stage HNSCC may provide insight into therapeutic targets and strategies. Previous bioinformatics studies have shown mixed or limited results in identifying gene and protein markers and in developing models for discriminating between early and advanced stage HNSCC. Thus, we have investigated models for HNSCC stage prediction using RNAseq and reverse phase protein array data from The Cancer Genome Atlas and The Cancer Proteome Atlas. We systematically assessed individual and ensemble binary classifiers, using filter and wrapper feature selection methods, to develop several well-performing models. In particular, integrated models harnessing both data types consistently resulted in better performance. This study identifies informative protein and gene feature sets which may increase understanding of HNSCC progression.

Assessment of a panel of tumor markers for the differential diagnosis of benign and malignant effusions by well-based reverse phase protein array

Background

The differential diagnosis of benign and malignant effusion is often hampered by low cell content or insufficiently preserved tumor cells. In this study, we evaluated the combined diagnostic value of six tumor markers measured by well-based reverse-phase protein array (RPPA) for diagnosis of malignant effusion.

Methods

A total of 114 patients (46 with malignant effusions, 32 with probable malignant effusions, and 36 with benign effusions) were enrolled. Expressional levels of MUC1, EMA, Pan-CK, HSP90, TGF-β and CA125 were determined by well-based RPPA.

Results

Median relative expression of MUC1, Pan-CK and EMA were significantly higher in malignant effusion than those in probable malignant or benign (p < 0.001, p = 0.003, p < 0.001, respectively), whereas the level of TGF-β in malignant effusions were significantly lower than that in the other groups (p = 0.005). For predicting malignancy, EMA presented the best areas under the curve of 0.728 followed by MUC1 of 0.701. The sensitivity of 52.0% for MUC1 and 48.0% for EMA were not better than cytology. However, sensitivity, negative predictive value, and accuracy of the tumor marker panel were better than cytology by 14.7%, 7.5%, and 6.1%, respectively.

Conclusions

Tumor marker panel measured by well-based RPPA showed values in the differential diagnosis between benign and malignant effusions. Further large scale studies need to be performed to evaluate the utility of this panel of markers.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1433424467160224

Electronic supplementary material

The online version of this article (doi:10.1186/s13000-015-0290-4) contains supplementary material, which is available to authorized users.

Copy number gains of FGFR1 and 3q chromosome in squamous cell carcinoma of the lung

Squamous cell carcinoma of the lung (SQCCL) remains a leading cause of cancer-related death. Unlike non-smoker adenocarcinoma of the lung, where highly efficient tyrosine kinase inhibitors are available for treating mutant EGFR or ALK-rearranged, no targetable biomarkers are available for SQCCL. The frequent and focal amplification of FGFR1 has generated great expectations in offering new therapeutical options in case of 16-22% of SQCCL patients. Broad 3q chromosome amplification is widely recognized as the most common chromosomal aberration found in SQCCL, where PIK3CA, SOX2, ACK1, PRKCI, TP63, PLD1, ECT2, and others genes are located. Although SOX2 has been postulated as a key regulator of basal stem cells transformation and tumor progression, it seems to confer a good prognosis in SQCCL. It is known that each patient might carry a different length of 3q chromosome amplicon. Thus, we suggest that the number and the biological importance of the genes spanned along each patient's 3q amplicon might help to explain inter-individual outcome variations of the disease and its potential predictive value, especially when relevant oncogenes such as those mentioned above are implicated. Currently, there is no clinical predictive data available from clinical trials. In this review, we have focused on the potential role of FGFR1 in SQCCL prognosis. Additionally, we have explored recently available public data on the comprehensive genomic characterization of SQCCL, in relation to the protein-coding genes that have a strong gene copy number - mRNA correlation in 3q chromosome, that were previously described as potential driver oncogenes or its modifiers in SQCCL.

Predicting clinical response to anticancer drugs using an ex vivo platform that captures tumour heterogeneity

Predicting clinical response to anticancer drugs remains a major challenge in cancer treatment. Emerging reports indicate that the tumour microenvironment and heterogeneity can limit the predictive power of current biomarker-guided strategies for chemotherapy. Here we report the engineering of personalized tumour ecosystems that contextually conserve the tumour heterogeneity, and phenocopy the tumour microenvironment using tumour explants maintained in defined tumour grade-matched matrix support and autologous patient serum. The functional response of tumour ecosystems, engineered from 109 patients, to anticancer drugs, together with the corresponding clinical outcomes, is used to train a machine learning algorithm; the learned model is then applied to predict the clinical response in an independent validation group of 55 patients, where we achieve 100% sensitivity in predictions while keeping specificity in a desired high range. The tumour ecosystem and algorithm, together termed the CANScript technology, can emerge as a powerful platform for enabling personalized medicine.

Detection of phosphorylated insulin receptor in colorectal adenoma and adenocarcinoma: implications for prognosis and clinical outcome

Colorectal carcinoma remains among the most frequent causes of cancer death. Besides the well-known genetic predisposition, a key role in colorectal adenoma and adenocarcinoma etio-pathogenesis, mainly in sporadic cases, is played by definite risk factors, such as obesity, type 2 diabetes, insulin resistance, hyper-insulinemia, and insulin therapy. These epidemiological data motivated us to determine, by means of immunohistochemistry, the amount of activated (phosphorylated) insulin receptor in archival samples from 22 colorectal adenoma and 117 adenocarcinoma patients, with the objective to estimate the role of this factor in colorectal epithelium transformation and cancer progression. Statistical analysis of the results clearly showed that positive staining for phosphorylated insulin receptor was significantly more frequent in adenomas than adenocarcinomas (P < 0.0001) and, within the adenocarcinoma cohort, it was more frequent in low-grade tumors (P = 0.005). In adenomas, staining was exclusively cytoplasmic, while in adenocarcinomas it was cytoplasmic and/or nuclear (P < 0.0001). Interestingly, disease-free survival in colorectal adenocarcinoma patients pointed out a significantly better prognosis for those bearing a positive staining for phosphorylated insulin receptor (P = 0.02). From these data, we can argue that activated insulin receptor plays a fundamental role at the early stages of tumorigenesis, where late stages could be characterized by a shift toward more active oncogenic drivers. Determining the amount of phosphorylated insulin receptor could thus represent a novel prognostic/predictive tool in colorectal adenocarcinoma patients.

Signaling pathway profiling by reverse-phase protein array for personalized cancer medicine

Deregulation of intracellular signaling through accumulation of genetic alterations is a hallmark of cancer. In the past few decades, concerted and systematic efforts have been made to identify key genetic alterations and to develop therapeutic agents targeting active signaling molecules. However, the efficacy of molecular therapeutics often varies among individuals, and precise mapping of active molecules in individual patients is now considered an essential for therapy optimization. Reverse-phase protein array or microarray (RPPA or RPPM) is an emerging antibody-based highly quantitative proteomic technology, especially suitable for profiling of expression and modification of signaling proteins in low abundance. Because the supply of clinical materials is often limited, RPPA technology is highly advantageous for clinical proteomics in view of its high sensitivity as well as accurate quantification. RPPA has now begun to be incorporated into various clinical trials employing molecular-targeted therapeutics. In this article we review and discuss the application of RPPA technology in the fields of basic, preclinical, and clinical research. The RPPA Global Workshop was recently launched to accelerate the exchange of rapidly expanding knowledge of this fascinating technology among academic laboratories and industries worldwide. This article is part of a Special Issue entitled: Medical Proteomics.

Protein Kinase C (PKC) Isozymes and Cancer

Protein kinase C (PKC) is a family of phospholipid-dependent serine/threonine kinases, which can be further classified into three PKC isozymes subfamilies: conventional or classic, novel or nonclassic, and atypical. PKC isozymes are known to be involved in cell proliferation, survival, invasion, migration, apoptosis, angiogenesis, and drug resistance. Because of their key roles in cell signaling, PKC isozymes also have the potential to be promising therapeutic targets for several diseases, such as cardiovascular diseases, immune and inflammatory diseases, neurological diseases, metabolic disorders, and multiple types of cancer. This review primarily focuses on the activation, mechanism, and function of PKC isozymes during cancer development and progression.

Association between phosphorylated AMP-activated protein kinase and acetyl-CoA carboxylase expression and outcome in patients with squamous cell carcinoma of the head and neck

Background

Epidemiological studies have indicated that impaired glucose metabolism may increase the risk of squamous cell carcinoma of the head and neck (SCCHN). AMP-activated protein kinase (AMPK) regulates glucose and lipid metabolism via the phosphorylation and subsequent inactivation of its downstream target acetyl-CoA carboxylase (ACC).Thus, we analyzed the expression of pAMPK and its downstream target phosphorylated acetyl-CoA carboxylase (pACC), as well as their impact on the survival of patients with resected SCCHN.

Methods

One hundred eighteen patients with surgically resected SCCHN were enrolled. Immunohistochemical (IHC) staining for pAMPK and pACC was performed using tissue microarrays of operative specimens of SCCHN. The expression was divided into two or three groups according to the IHC score [pAMPK: negative (0), positive (1–3); pACC: negative (0), low expression (1, 2), and high expression (3)]. Statistical analysis was performed to determine the association of pAMPK expression with clinicopathological features and pACC and pErk expression.

Results

The positive rates of pAMPK and pACC expression were 64.4% (76/118) and 68.6% (81/118), respectively. pAMPK was significantly higher in patients aged younger than 60 years (P = 0.024; χ²test) and those with early-stage (T1/T2; P = 0.02; χ² test) and oral cavity (P = 0.026; Fisher’s exact test) tumors. In multivariate analysis, pAMPK expression was not significantly correlated with overall survival (OS) (adjusted hazard ratio [HR]: 0.66; 95% confidence interval [CI]: 0.35–1.23), whereas high pACC expression was independently associated with worse OS in node-positive patients (adjusted HR: 17.58; 95% CI: 3.50–88.18).

Conclusions

Strong expression of pACC was found to be an independent prognostic marker for patients with node-positive SCCHN. Our results suggest that pACC may play a role in tumor progression of SCCHN and may help to identify patient subgroups at high risk for poor disease outcome.

HRAS mutations and resistance to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib in head and neck squamous cell carcinoma cells

BACKGROUND

The purpose of this study was to identify mechanisms of innate resistance to an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, erlotinib, in a panel of head and neck squamous cell carcinoma (HNSCC) cell lines. Specifically, we analyzed the role of HRAS mutations in erlotinib resistance.

METHODS

Erlotinib sensitivity was determined by methyl thiazolyl-tetrazolium (MTT) assays. Molecular signaling pathways and somatic mutations were examined. Changes in sensitivity after modulation of HRAS expression were evaluated.

RESULTS

All 7 cell lines were wild-type for EGFR and KRAS regardless of erlotinib sensitivity; however, 1 erlotinib-resistant cell line (HN31) harbored an HRAS G12D mutation. Downregulation of HRAS expression by small interfering RNA (siRNA) or short hairpin RNA (shRNA) in HN31 led to increased erlotinib sensitivity in vitro and in vivo. Transfection of activating HRAS-mutant (G12D and G12V) constructs into erlotinib-sensitive cell lines made them more resistant to erlotinib.

CONCLUSION

Activating HRAS mutations can confer erlotinib resistance in an HRAS mutant HNSCC cell line.

MicroRNA and protein profiling of brain metastasis competent cell-derived exosomes

Exosomes are small membrane vesicles released by most cell types including tumor cells. The intercellular exchange of proteins and genetic material via exosomes is a potentially effective approach for cell-to-cell communication and it may perform multiple functions aiding to tumor survival and metastasis. We investigated microRNA and protein profiles of brain metastatic (BM) versus non-brain metastatic (non-BM) cell-derived exosomes. We studied the cargo of exosomes isolated from brain-tropic 70W, MDA-MB-231BR, and circulating tumor cell brain metastasis-selected markers (CTC1BMSM) variants, and compared them with parental non-BM MeWo, MDA-MB-231P and CTC1P cells, respectively. By performing microRNA PCR array we identified one up-regulated (miR-210) and two down-regulated miRNAs (miR-19a and miR-29c) in BM versus non-BM exosomes. Second, we analyzed the proteomic content of cells and exosomes isolated from these six cell lines, and detected high expression of proteins implicated in cell communication, cell cycle, and in key cancer invasion and metastasis pathways. Third, we show that BM cell-derived exosomes can be internalized by non-BM cells and that they effectively transport their cargo into cells, resulting in increased cell adhesive and invasive potencies. These results provide a strong rationale for additional investigations of exosomal proteins and miRNAs towards more profound understandings of exosome roles in brain metastasis biogenesis, and for the discovery and application of non-invasive biomarkers for new therapies combating brain metastasis.

Antagonistic functional duality of cancer genes

Cancer evolution is a stochastic process both at the genome and gene levels. Most of tumors contain multiple genetic subclones, evolving in either succession or in parallel, either in a linear or branching manner, with heterogeneous genome and gene alterations, extensively rewired signaling networks, and addicted to multiple oncogenes easily switching with each other during cancer progression and medical intervention. Hundreds of discovered cancer genes are classified according to whether they function in a dominant (oncogenes) or recessive (tumor suppressor genes) manner in a cancer cell. However, there are many cancer "gene-chameleons", which behave distinctly in opposite way in the different experimental settings showing antagonistic duality. In contrast to the widely accepted view that mutant NADP(+)-dependent isocitrate dehydrogenases 1/2 (IDH1/2) and associated metabolite 2-hydroxyglutarate (R)-enantiomer are intrinsically "the drivers" of tumourigenesis, mutant IDH1/2 inhibited, promoted or had no effect on cell proliferation, growth and tumorigenicity in diverse experiments. Similar behavior was evidenced for dozens of cancer genes. Gene function is dependent on genetic network, which is defined by the genome context. The overall changes in karyotype can result in alterations of the role and function of the same genes and pathways. The diverse cell lines and tumor samples have been used in experiments for proving gene tumor promoting/suppressive activity. They all display heterogeneous individual karyotypes and disturbed signaling networks. Consequently, the effect and function of gene under investigation can be opposite and versatile in cells with different genomes that may explain antagonistic duality of cancer genes and the cell type- or the cellular genetic/context-dependent response to the same protein. Antagonistic duality of cancer genes might contribute to failure of chemotherapy. Instructive examples of unexpected activity of cancer genes and "paradoxical" effects of different anticancer drugs depending on the cellular genetic context/signaling network are discussed.

Signaling Networks of Activated Oncogenic and Altered Tumor Suppressor Genes in Head and Neck Cancer

Head and neck squamous cell carcinoma (HNSCC) arises from the upper aerodigestive tract and is the six most common cancers worldwide. HNSCC is associated with high morbidity and mortality, as standard surgery, radiation, and chemotherapy can cause significant disfigurement and only provide 5-year survival rates of ~50-60%. The heterogeneity of HNSCC subsets with different potentials for recurrence and metastasis challenges the traditional pathological classification system, thereby increasing demand for the development of new diagnostic, prognostic, and therapeutic tools based on global molecular signatures of HNSCC. Historically, using classical biological techniques, it has been extremely difficult and time-consuming to survey hundreds or thousands of genes in a given disease. However, the development of high throughput technologies and high-powered computation throughout the last two decades has enabled us to investigate hundreds or thousands of genes simultaneously. Using high throughput technologies, our laboratory has identified the gene signatures and protein networks, which significantly affect HNSCC malignant phenotypes, including TP53/p63/p73 family members, IL-1/TNF-β/NF-κB, PI3K/AKT/mTOR, IL-6/IL-6R/JAK/STAT3, EGFR/MAPK/AP1, HGF/cMET/EGR1, and TGFβ/TGFβR/TAK1/SMAD pathways. This review summarizes the results from high-throughput technological assays conducted on HNSCC samples, including microarray, DNA methylation, miRNA profiling, and protein array, using primarily experimental data and conclusions generated in our own laboratory. The use of bioinformatics and integrated analyses of data sets from different platforms, as well as meta-analysis of large datasets pulled from multiple publicly available studies, provided significantly higher statistical power to extract biologically relevant information. The data suggested that the heterogeneity of HNSCC genotype and phenotype are much more complex than we previously thought. Understanding of global molecular signatures and disease classification for specific subsets of HNSCC will be essential to provide accurate diagnoses for targeted therapy and personalized treatment, which is an important effort toward improving patient outcomes.

Chk1/2 inhibition overcomes the cisplatin resistance of head and neck cancer cells secondary to the loss of functional p53

Despite the use of multimodality therapy using cisplatin to treat patients with advanced stage squamous cell carcinoma of the head and neck (HNSCC), there is an unacceptably high rate of treatment failure. TP53 is the most commonly mutated gene in HNSCC, and the impact of p53 mutation on response to cisplatin treatment is poorly understood. Here, we show unambiguously that wild-type TP53 (wtp53) is associated with sensitivity of HNSCC cells to cisplatin treatment, whereas mutation or loss of TP53 is associated with cisplatin resistance. We also show that senescence is the major cellular response to cisplatin in wtp53 HNSCC cells and that cisplatin resistance in p53-null or -mutant TP53 cells is due to their lack of senescence. Given the dependence on checkpoint kinase (Chk)1/2 kinases to mediate the DNA damage response in p53-deficient cells, there is potential to exploit this to therapeutic advantage through targeted inhibition of the Chk1/2 kinases. Treatment of p53-deficient HNSCC cells with the Chk inhibitor AZD7762 sensitizes them to cisplatin through induction of mitotic cell death. This is the first report showing the ability of a Chk kinase inhibitor to sensitize TP53-deficient HNSCC to cisplatin in a synthetic lethal manner, which has significance given the frequency of TP53 mutations in this disease and because cisplatin has become part of standard therapy for aggressive HNSCC tumors. These preclinical data provide evidence that a personalized approach to the treatment of HNSCC based on Chk inhibition in p53-mutant tumors may be feasible.

Dynamic protein pathway activation mapping of adipose-derived stem cell differentiation implicates novel regulators of adipocyte differentiation

Next to embryonic stem cell research, adult stem cell research is providing a promising alternative for enhanced tissue regeneration and transplantation. The key biochemical networks controlling the differentiation processes regulating stem cell biology remain largely disputed and or undefined, contributing to a lack of knowledge of the principle phosphoregulatory events propagating signal transduction. To effectively monitor these events relative to adipocyte differentiation, this study utilized a high throughput reverse phase protein microarray platform and characterized adult adipose-derived stem cell (ASC) differentiation through the monitoring of ∼100 phosphospecific endpoints with 33 distinct time points examined across 14 days. This kinetic-based analysis showed time ordered signal transduction ultimately implicating pathways correlated with adipogenic differentiation. To further validate the causal significance of these network activations, pharmacological targeting was implemented to include the chemical inhibitors MAPK inhibitor PD169316, rapamycin, and HNMPA-(AM)3 yielding partial or complete disruption of adipocytic differentiation, as noted by a decrease or lack of lipid formation within the mature adipocytes. Based on this analysis, v-crk sarcoma virus CT10 oncogene homolog (CRKII) and c-abl oncogene 1, non-receptor tyrosine kinase (c-ABL) were implicated as novel key regulators of adipocyte differentiation, with v-akt murine thymoma viral oncogene (AKT), mammalian target of rapamycin (mTOR), and SMAD family member (SMAD) pathways being implicated as secondary regulators. This dynamic molecular profiling provides a novel insight into the signaling architecture of mesenchymal stem cell differentiation and may be useful in the development of therapeutic modulators for clinical applications; in addition to advancing the collective understanding of key cellular processes, ultimately contributing to more confident stem cell manipulation.

Atypical protein kinase Cι is required for Wnt3a-dependent neurite outgrowth and binds to phosphorylated dishevelled 2

Previously we reported that Wnt3a-dependent neurite outgrowth in Ewing sarcoma family tumor cell lines was mediated by Frizzled3, Dishevelled (Dvl), and c-Jun N-terminal kinase (Endo, Y., Beauchamp, E., Woods, D., Taylor, W. G., Toretsky, J. A., Uren, A., and Rubin, J. S. (2008) Mol. Cell. Biol. 28, 2368-2379). Subsequently, we observed that Dvl2/3 phosphorylation correlated with neurite outgrowth and that casein kinase 1δ, one of the enzymes that mediate Wnt3a-dependent Dvl phosphorylation, was required for neurite extension (Greer, Y. E., and Rubin, J. S. (2011) J. Cell Biol. 192, 993-1004). However, the functional relevance of Dvl phosphorylation in neurite outgrowth was not established. Dvl1 has been shown by others to be important for axon specification in hippocampal neurons via an interaction with atypical PKCζ, but the role of Dvl phosphorylation was not evaluated. Here we report that Ewing sarcoma family tumor cells express PKCι but not PKCζ. Wnt3a stimulated PKCι activation and caused a punctate distribution of pPKCι in the neurites and cytoplasm, with a particularly intense signal at the centrosome. Knockdown of PKCι expression with siRNA reagents blocked neurite formation in response to Wnt3a. Aurothiomalate, a specific inhibitor of PKCι/Par6 binding, also suppressed neurite extension. Wnt3a enhanced the co-immunoprecipitation of endogenous PKCι and Dvl2. Although FLAG-tagged wild-type Dvl2 immunoprecipitated with PKCι, a phosphorylation-deficient Dvl2 derivative did not. This derivative also was unable to rescue neurite outgrowth when endogenous Dvl2/3 was suppressed by siRNA (González-Sancho, J. M., Greer, Y. E., Abrahams, C. L., Takigawa, Y., Baljinnyam, B., Lee, K. H., Lee, K. S., Rubin, J. S., and Brown, A. M. (2013) J. Biol. Chem. 288, 9428-9437). Taken together, these results suggest that site-specific Dvl2 phosphorylation is required for Dvl2 association with PKCι. This interaction is likely to be one of the mechanisms essential for Wnt3a-dependent neurite outgrowth.

Proteomic strategies to characterize signaling pathways

Cells respond to external stimuli by transducing signals through a series of intracellular molecules and eliciting an appropriate response. The cascade of events through which the signals are transduced include post-translational modifications such as phosphorylation and ubiquitylation in addition to formation of multi-protein complexes. Improvements in biological mass spectrometry and protein/peptide microarray technology have tremendously improved our ability to probe proteins, protein complexes, and signaling pathways in a high-throughput fashion. Today, a single mass spectrometry-based investigation of a signaling pathway has the potential to uncover the large majority of known signaling intermediates painstakingly characterized over decades in addition to discovering a number of novel ones. Here, we discuss various proteomic strategies to characterize signaling pathways and provide protocols for phosphoproteomic analysis.

Reverse phase protein microarrays and their utility in drug development

The majority of human diseases, including cancer, are characterized by abnormal protein function. Proteins regulate virtually every cellular process and exhibit multiple kinds of post-translational modification that modulate expression levels and activation states, such as phosphorylation by protein kinases. Additionally proteins interact with each other in complex regulatory networks and signal transduction pathways modulated by feedback mechanisms. These pathways are disrupted in disease and altered by therapeutic drugs. Reverse phase protein microarray (RPMA) technology allows simultaneous measurement of numerous phosphorylated, glycosylated, cleaved, or total cellular proteins from complex mixtures in many samples at once. Therefore, RPMAs can provide a portrait of a cell's signaling pathways in diseased states, before and after treatment with drugs, and allows comparison of changes in drug-resistant and sensitive cells. Furthermore, the technology offers a means of connecting genomic abnormalities in cancer to targetable alterations in protein signaling pathways, even for genetic events that seem otherwise undruggable. Consequently, the RPMA platform has great utility in many steps of drug development including target identification, validation of a pharmaceutical agent's efficacy, understanding mechanisms of action, and discovery of biomarkers that predict or guide therapeutic response. RPMAs have become a powerful tool for drug development and are now being integrated into human clinical cancer trials, where they are being used to personalize therapy.

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

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

Proteomics and biomarkers in clinical trials for drug development

Proteomics allows characterization of protein structure and function, protein-protein interactions, and peptide modifications. It has given us insight into the perturbations of signaling pathways within tumor cells and has improved the discovery of new therapeutic targets and possible indicators of response to and duration of therapy. The discovery, verification, and validation of novel biomarkers are critical in streamlining clinical development of targeted compounds, and directing rational treatments for patients whose tumors are dependent upon select signaling pathways. Studies are now underway in many diseases to examine the immune or inflammatory proteome, vascular proteome, cancer or disease proteome, and other subsets of the specific pathology microenvironment. Successful assay verification and biological validation of such biomarkers will speed development of potential agents to targetable dominant pathways and lead to selection of individuals most likely to benefit. Reconsideration of analytical and clinical trials methods for acquisition, examination, and translation of proteomics data must occur before we march further into future of drug development.