Proteomic Analysis of Apoptotic Pathways Reveals Prognostic Factors in Follicular Lymphoma

Integrative microRNA and proteomic approaches identify novel osteoarthritis genes and their collaborative metabolic and inflammatory networks

BACKGROUND

Osteoarthritis is a multifactorial disease characterized by destruction of the articular cartilage due to genetic, mechanical and environmental components affecting more than 100 million individuals all over the world. Despite the high prevalence of the disease, the absence of large-scale molecular studies limits our ability to understand the molecular pathobiology of osteoathritis and identify targets for drug development.

METHODOLOGY/PRINCIPAL FINDINGS

In this study we integrated genetic, bioinformatic and proteomic approaches in order to identify new genes and their collaborative networks involved in osteoarthritis pathogenesis. MicroRNA profiling of patient-derived osteoarthritic cartilage in comparison to normal cartilage, revealed a 16 microRNA osteoarthritis gene signature. Using reverse-phase protein arrays in the same tissues we detected 76 differentially expressed proteins between osteoarthritic and normal chondrocytes. Proteins such as SOX11, FGF23, KLF6, WWOX and GDF15 not implicated previously in the genesis of osteoarthritis were identified. Integration of microRNA and proteomic data with microRNA gene-target prediction algorithms, generated a potential "interactome" network consisting of 11 microRNAs and 58 proteins linked by 414 potential functional associations. Comparison of the molecular and clinical data, revealed specific microRNAs (miR-22, miR-103) and proteins (PPARA, BMP7, IL1B) to be highly correlated with Body Mass Index (BMI). Experimental validation revealed that miR-22 regulated PPARA and BMP7 expression and its inhibition blocked inflammatory and catabolic changes in osteoarthritic chondrocytes.

CONCLUSIONS/SIGNIFICANCE

Our findings indicate that obesity and inflammation are related to osteoarthritis, a metabolic disease affected by microRNA deregulation. Gene network approaches provide new insights for elucidating the complexity of diseases such as osteoarthritis. The integration of microRNA, proteomic and clinical data provides a detailed picture of how a network state is correlated with disease and furthermore leads to the development of new treatments. This strategy will help to improve the understanding of the pathogenesis of multifactorial diseases such as osteoarthritis and provide possible novel therapeutic targets.

Laser capture microdissection and protein microarray analysis of human non-small cell lung cancer: differential epidermal growth factor receptor (EGPR) phosphorylation events associated with mutated EGFR compared with wild type

Little is known about lung carcinoma epidermal growth factor (EGF) kinase pathway signaling within the context of the tissue microenvironment. We quantitatively profiled the phosphorylation and abundance of signal pathway proteins relevant to the EGF receptor within laser capture microdissected untreated, human non-small cell lung cancer (NSCLC) (n = 25) of known epidermal growth factor receptor (EGFR) tyrosine kinase domain mutation status. We measured six phosphorylation sites on EGFR to evaluate whether EGFR mutation status in vivo was associated with the coordinated phosphorylation of specific multiple phosphorylation sites on the EGFR and downstream proteins. Reverse phase protein array quantitation of NSCLC revealed simultaneous increased phosphorylation of EGFR residues Tyr-1148 (p < 0.044) and Tyr-1068 (p < 0.026) and decreased phosphorylation of EGFR Tyr-1045 (p < 0.002), HER2 Tyr-1248 (p < 0.015), IRS-1 Ser-612 (p < 0.001), and SMAD Ser-465/467 (p < 0.011) across all classes of mutated EGFR patient samples compared with wild type. To explore which subset of correlations was influenced by ligand induction versus an intrinsic phenotype of the EGFR mutants, we profiled the time course of 115 cellular signal proteins for EGF ligand-stimulated (three dosages) NSCLC mutant and wild type cultured cell lines. EGFR mutant cell lines (H1975 L858R) displayed a pattern of EGFR Tyr-1045 and HER2 Tyr-1248 phosphorylation similar to that found in tissue. Persistence of phosphorylation for AKT Ser-473 following ligand stimulation was found for the mutant. These data suggest that a higher proportion of the EGFR mutant carcinoma cells may exhibit activation of the phosphatidylinositol 3-kinase/protein kinase B (AKT)/mammalian target of rapamycin (MTOR) pathway through Tyr-1148 and Tyr-1068 and suppression of IRS-1 Ser-612, altered heterodimerization with ERBB2, reduced response to transforming growth factor beta suppression, and reduced ubiquitination/degradation of the EGFR through EGFR Tyr-1045, thus providing a survival advantage. This is the first comparison of multiple, site-specific phosphoproteins with the EGFR tyrosine kinase domain mutation status in vivo.

IL-4 protein expression and basal activation of Erk in vivo in follicular lymphoma

Follicular lymphoma (FL) is characterized by constitutive expression of Bcl-2 as a consequence of t(14;18). Evidence suggests factors in the lymph node microenvironment, related to intratumoral T cells, macrophages, and dendritic cells, play a role in the disease process. We generated proteomic cytokine profiles of FL (N = 50) and follicular hyperplasia (FH; N = 23). A total of 10 cytokines were assayed using ultrasensitive multiplex enzyme-linked immunosorbent assays: IL-1beta, IL-2, IL-4, IL-5, IL-8, IL-10, IL-13, IL-12p70, tumor necrosis factor-alpha, and interferon-gamma. Each cytokine showed overall lower protein concentrations in FL, with the exception of IL-4, which was nearly 5 times higher in FL than FH (P = .005). Using reverse-phase protein microarrays (RPMAs), we evaluated the activation state of several intracellular signaling proteins downstream of cytokine receptors. Basal Erk phosphorylation was approximately 4 times greater in FL than FH (P < .001), with similar findings for Mek; Stat-6 showed weak basal phosphorylation that was approximately twice as high in FL than in FH (P = .012). In conclusion, the FL microenvironment contains increased levels of IL-4, with prominent tumor basal phosphorylation of Erk. These findings suggest IL-4, Erk, and possibly Stat-6 may play a role in the biology of FL and may serve as targets for future therapies.

A portrait of tissue phosphoprotein stability in the clinical tissue procurement process

Little is known about the preanalytical fluctuations of phosphoproteins during tissue procurement for molecular profiling. This information is crucial to establish guidelines for the reliable measurement of these analytes. To develop phosphoprotein profiles of tissue subjected to the trauma of excision, we measured the fidelity of 53 signal pathway phosphoproteins over time in tissue specimens procured in a community clinical practice. This information provides strategies for potential surrogate markers of stability and the design of phosphoprotein preservative/fixation solutions. Eleven different specimen collection time course experiments revealed augmentation (+/-20% from the time 0 sample) of signal pathway phosphoprotein levels as well as decreases over time independent of tissue type, post-translational modification, and protein subcellular location (tissues included breast, colon, lung, ovary, and uterus (endometrium/myometrium) and metastatic melanoma). Comparison across tissue specimens showed an >20% decrease of protein kinase B (AKT) Ser-473 (p < 0.002) and myristoylated alanine-rich C-kinase substrate protein Ser-152/156 (p < 0.0001) within the first 90-min postexcision. Proteins in apoptotic (cleaved caspase-3 Asp-175 (p < 0.001)), proliferation/survival/hypoxia (IRS-1 Ser-612 (p < 0.0003), AMP-activated protein kinase beta Ser-108 (p < 0.005), ERK Thr-202/Tyr-204 (p < 0.003), and GSK3alphabeta Ser-21/9 (p < 0.01)), and transcription factor pathways (STAT1 Tyr-701 (p < 0.005) and cAMP response element-binding protein Ser-133 (p < 0.01)) showed >20% increases within 90-min postprocurement. Endothelial nitric-oxide synthase Ser-1177 did not change over the time period evaluated with breast or leiomyoma tissue. Treatment with phosphatase or kinase inhibitors alone revealed that tissue kinase pathways are active ex vivo. Combinations of kinase and phosphatase inhibitors appeared to stabilize proteins that exhibited increases in the presence of phosphatase inhibitors alone (ATF-2 Thr-71, SAPK/JNK Thr-183/Tyr-185, STAT1 Tyr-701, JAK1 Tyr-1022/1023, and PAK1/PAK2 Ser-199/204/192/197). This time course study 1) establishes the dynamic nature of specific phosphoproteins in excised tissue, 2) demonstrates augmented phosphorylation in the presence of phosphatase inhibitors, 3) shows that kinase inhibitors block the upsurge in phosphorylation of phosphoproteins, 4) provides a rational strategy for room temperature preservation of proteins, and 5) constitutes a foundation for developing evidence-based tissue procurement guidelines.

Analysis of laser capture microdissected cells by 2-dimensional gel electrophoresis

Laser capture microdissection (LCM) is a powerful tool for procuring near-pure populations of targeted cell types from specific microscopic regions of tissue sections, by overcoming problems due to tissue heterogeneity and minimizing intermixture and contamination by other cell types. The combination of LCM with various proteomic technologies has enabled high-throughput molecular analysis of human tumors, and provided critical tools in the search for novel disease markers and therapeutic targets. As an example, we describe the application of LCM in dissecting the tumor cells in breast cancer for macromolecular extraction and subsequent protein separation by 2-dimensional gel electrophoresis (2-D GE). The protocols and the key issues involved in preparing ethanol-fixed paraffin-embedded tissue blocks and microscopic sections, microdissecting the cells of interest using the PixCell II LCM system, extracting and separating the cellular proteins by 2-D GE, and preparing selective proteins for peptide mass analysis by mass spectrometry, are discussed. The aim is to provide a practical guide in performing high-throughput microdissection of target cells and gel-based proteomics, which can be adapted to research in cancer formation and growth.

Porous silicon surfaces: a candidate substrate for reverse protein arrays in cancer biomarker detection

This paper introduces a new substrate for reverse-phase protein microarray applications based on macroporous silicon. A key feature of the microarray substrate is the vastly surface enlarging properties of the porous silicon, which simultaneously offers highly confined microarray spots. The proof of principle of the reverse array concept was demonstrated in the detection of different levels of cyclin E, a possible cancer biomarker candidate which regulates G1-S transition and correlates with poor prognosis in different types of human cancers. The substrate properties were studied performing analysis of total cyclin E expression in human colon cancer cell lines Hct116 and SW480. The absence of unspecific binding and good microarray quality was demonstrated. In order to verify the performance of the 3-D textured macroporous surface for complex biological samples, lysates of the human tissue spiked to different levels with cell extract overproducing cyclin E (Hct116) were arrayed on the chip surface. The samples were spotted in a noncontact mode in 100 pL droplets with spots sizes ranged between 50 and 70 mum and spot-to-spot center distances 100 mum, allowing microarray spot densities up to 14 000 spots per cm(2). The different sample types of increasing complexities did not have any impact on the spot intensities recorded and the protein spots showed good homogeneity and reproducibility over the recorded microarrays. The data demonstrate the potential use of macroporous silicon as a substrate for quantitative determination of a cancer biomarker cyclin E in tissue lysates.

Multiplexed cell signaling analysis of human breast cancer applications for personalized therapy

Phosphoprotein driven cellular signaling events represent most of the new molecular targets for cancer treatment. Application of reverse-phase protein microarray technology for the study of ongoing signaling activity within breast tumor specimens holds great potential for elucidating and profiling signaling activity in real-time for patient-tailored therapy. Analysis of laser capture microdissection primary human breast tumors and metastatic lesions reveals pathway specific profiles and a new way to classify cancer based on functional signaling portraits. Moreover, the data demonstrate the requirement of laser capture microdissection for analysis and reveal the metastasis-specific changes that occur within a new microenvironment. Analysis of biopsy material from clinical trials for targeted therapeutics demonstrates the feasibility and utility of comprehensive signal pathway activation profiling for molecular analysis.

Constitution and quantity of lysis buffer alters outcome of reverse phase protein microarrays

Application of novel technology to clinical samples requires optimization of procedures. Reverse phase protein lysate arrays use femtomolar quantities of tissue lysate from clinical samples with which to profile biochemical events happening in the tumor. We analyzed the effects of different tissue solubilization buffers on frozen ovarian tumor samples in order to identify the system with the best signal intensity dynamic range, reproducibility, tissue solubility, and signal consistency. A modified RIPA-like buffer supplemented with DTT and SDS was deemed optimal.

Experimental validation for quantitative protein network models

Cellular responses are the consequence of complex reactions of protein networks. The complexity should ultimately be described by a set of formulas in a quantitative fashion, in which each formula defines the reactions in response to given types of input. However, testing these formulas has not been a simple task because of the lack of appropriate means for experimental validation. 'Reverse-phase' lysate microarrays have been proved to be powerful for such requirements and thus can be a good resource for providing an experimental reference point for the theoretical biology of protein networks.

Reverse-phase protein microarrays: application to biomarker discovery and translational medicine

Mapping of protein signaling networks within tumors can identify new targets for therapy and provide a means to stratify patients for individualized therapy. Kinases are important drug targets, as such kinase network information could become the basis for development of therapeutic strategies for improving treatment outcome. An urgent clinical goal is to identify functionally important molecular networks associated with subpopulations of patients that may not respond to conventional combination chemotherapy. Reverse-phase protein microarrays are a technology platform designed for quantitative, multiplexed analysis of specific phosphorylated, cleaved, or total (phosphorylated and nonphosphorylated) forms of cellular proteins from a limited amount of sample. This class of microarray can be used to interrogate cellular samples, serum or body fluids. This review focuses on the application of reverse-phase protein microarrays for translational research and therapeutic drug target discovery.

Laser capture microdissection technology

Deciphering the cellular and molecular interactions that drive disease within the tissue microenvironment holds promise for discovering drug targets of the future. In order to recapitulate the in vivo interactions through molecular analysis, one must be able to analyze specific cell populations within the context of their heterogeneous tissue microecology. Laser capture microdissection is a method to procure subpopulations of tissue cells under direct microscopic visualization. Laser capture microdissection technology can harvest the cells of interest directly or can isolate specific cells by cutting away unwanted cells to give histologically pure enriched cell populations. A variety of downstream applications exist: DNA genotyping and loss-of-heterozygosity analysis, RNA transcript profiling, cDNA library generation, mass spectrometry proteomics discovery and signal pathway profiling.

Laser-capture microdissection

Deciphering the cellular and molecular interactions that drive disease within the tissue microenvironment holds promise for discovering drug targets of the future. In order to recapitulate the in vivo interactions thorough molecular analysis, one must be able to analyze specific cell populations within the context of their heterogeneous tissue microecology. Laser-capture microdissection (LCM) is a method to procure subpopulations of tissue cells under direct microscopic visualization. LCM technology can harvest the cells of interest directly or can isolate specific cells by cutting away unwanted cells to give histologically pure enriched cell populations. A variety of downstream applications exist: DNA genotyping and loss-of-heterozygosity (LOH) analysis, RNA transcript profiling, cDNA library generation, proteomics discovery and signal-pathway profiling. Herein we provide a thorough description of LCM techniques, with an emphasis on tips and troubleshooting advice derived from LCM users. The total time required to carry out this protocol is typically 1-1.5 h.

Principles of laser microdissection and catapulting of histologic specimens and live cells

Rapid contact- and contamination-free procurement of specific samples of histologic material for proteomic and genomic analysis as well as separation and transport of living cells can be achieved by laser microdissection (LMD) of the sample of interest followed by a laser-induced forward transport process [laser pressure "catapulting," (LPC)] of the dissected material. We investigated the dynamics of LMD and LPC with focused and defocused laser pulses by means of time-resolved photography. The working mechanism of microdissection was found to be plasma-mediated ablation. Catapulting is driven by plasma formation, when tightly focused pulses are used, and by ablation at the bottom of the sample for moderate and strong defocusing. Driving pressures of several hundred megapascals accelerate the specimen to initial velocities of 100-300 m/s before it is rapidly slowed down by air friction. With strong defocusing, driving pressure and initial flight velocity decrease considerably. On the basis of a characterization of the thermal and optical properties of the histologic specimens and supporting materials used, we calculated the temporal evolution of the heat distribution in the sample. After laser microdissection and laser pressure catapulting (LMPC), the samples were inspected by scanning electron microscopy. Catapulting with tightly focused or strongly defocused pulses results in very little collateral damage, while slight defocusing involves significant heat and UV exposure of up to about 10% of the specimen volume, especially if samples are catapulted directly from a glass slide. Time-resolved photography of live-cell catapulting revealed that in defocused catapulting strong shear forces originate from the flow of the thin layer of culture medium covering the cells. By contrast, pulses focused at the periphery of the specimen cause a fast rotational movement that makes the specimen wind its way out of the culture medium, thereby undergoing much less shear stresses. Therefore, the recultivation rate of catapulted cells was much higher when focused pulses were used.

Protein microarray platforms for clinical proteomics

Proteomics for clinical applications is presently in a state of transition. It has become clear that the classical approaches based on 2-DE and/or MS need to be complemented by different kinds of technologies. The well-known problems include sample complexity, sensitivity, quantitation, reproducibility, and analysis time. We suggest that the new technologies for clinical proteomics can be supported by antibody-centric protein microarray platforms. These platforms presently include antibody microarrays and lysate, or reverse capture/reverse phase protein microarrays. Other forms of these arrays are in less mature developmental stages, including ORF and self assembling protein microarrays. Bioinformatic support for interpreting these arrays is becoming more available as the whole field of systems biology begins to mature. The present set of applications for these platforms is profoundly focused on certain common cancers, immunology, and cystic fibrosis. However, we predict that many more disease entities will become studied as knowledge of the power and availability of these platforms becomes more widely established. We anticipate that these platforms will eventually evolve to accommodate label-free detection technologies, human genome-scale numbers of analytes, and increases in analytic and bioinformatic speeds.

Proteomics analysis in lung cancer: challenges and opportunities

Recent technological developments in proteomic analysis are bringing us new insights into the molecular classification of tumours. Although proteomic analysis in cancer profiling is still under development both in terms of the instruments used and the data analytical tools, this method has great potential advantages for the analysis of biospecimens of many types. Direct measurement of abnormally expressed or modified proteins in the tumour tissue and/or patient blood may be an effective approach for discovering new biomarkers. Proteomics has the significant advantage of being able to discern not only changes in expression levels but also in post-translational modifications. Thus, the proteomics approach to protein profiling and biomarker discovery uncovers biomarkers from a different viewpoint than microarray analysis. This review summarizes the range of proteomics technologies employed for cancer profiling, and how they have been used to derive new classification models for human lung cancer.

4E-binding protein 1, a cell signaling hallmark in breast cancer that correlates with pathologic grade and prognosis

PURPOSE

Cell signaling pathways include a complex myriad of interconnected factors from the membrane to the nucleus, such as erbB family receptors and the phosphoinositide-3-kinase/Akt/mTOR and Ras-Raf-ERK cascades, which drive proliferative signals, promote survival, and regulate protein synthesis.

EXPERIMENTAL DESIGN

To find pivotal factors in these pathways, which provide prognostic information in malignancies, we studied 103 human breast tumors with an immunohistochemical profile, including total and phosphorylated (p) proteins: human epidermal growth factor receptor 2 (HER2), epidermal growth factor receptor, extracellular signal-regulated kinase 1/2, Akt, 4E-binding protein 1 (4EBP1), eukaryotic initiation factor 4E, phosphorylated ribosomal protein S6 kinase 1, phosphorylated ribosomal protein S6, and Ki67. Western blot and reverse lysate protein arrays were also done in a subset of tumors.

RESULTS

Significantly, activation of the phosphoinositide-3-kinase/Akt/mTOR cascade was detected in a high proportion of tumors (41.9%). Tumors with HER2 overexpression showed higher p-Akt as compared with negative tumors (P < 0.001). Levels of p-Akt correlated with the downstream molecules, p-4EBP1 (P = 0.001) and p-p70S6K (P = 0.05). Although 81.5% of tumors expressed p-4EBP1, in 16.3% of these tumors, concomitant activation of the upstream factors was not detected. Interestingly, p-4EBP1 was mainly expressed in poorly differentiated tumors (P < 0.001) and correlated with tumor size (P < 0.001), presence of lymph node metastasis (P = 0.002), and locoregional recurrences (P = 0.002). Coexpression of p-4EBP1 and p-eIF4G correlated with a high tumor proliferation rate (P = 0.012).

CONCLUSION

In this study, p-4EBP1 was the main factor in signaling pathways that associate with prognosis and grade of malignancy in breast tumors. Moreover, p-4EBP1 was detected in both HER2-positive and HER2-negative tumors. This factor seems to be a channeling point at which different upstream oncogenic alterations converge and transmit their proliferative signal, modulating protein translation.

Porous silicon protein microarray technology and ultra-/superhydrophobic states for improved bioanalytical readout

One attractive method for monitoring biomolecular interactions in a highly parallel fashion is the use of microarrays. Protein microarray technology is an emerging and promising tool for protein analysis, which ultimately may have a large impact in clinical diagnostics, drug discovery studies and basic protein research. This chapter is based upon several original papers presenting our effort in the development of new protein microarray chip technology. The work describes a novel 3D surface/platform for protein characterization based on porous silicon. The simple adjustment of pore morphology and geometry offers a convenient way to control wetting behavior of the microarray substrates. In this chapter, an interesting insight into the surface role in bioassays performance is made. The up-scaled fabrication of the novel porous chips is demonstrated and stability of the developed supports as well as the fluorescent bioassay reproducibility and data quality issues are addressed. We also describe the efforts made by our group to link protein microarrays to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), suggesting porous silicon as a convenient platform for fast on-surface protein digestion protocols linked to MS-readout. The fabrication of ultra- and superhydrophobic states on porous silicon is also described and the utilization of these water-repellent properties for a new microscaled approach to superhydrophobic MALDI-TOF MS target anchor chip is covered.

Physicochemically modified silicon as a substrate for protein microarrays

Reverse phase protein microarrays (RPMA) enable high throughput screening of posttranslational modifications of important signaling proteins within diseased cells. One limitation of protein-based molecular profiling is the lack of a PCR-like intrinsic amplification system for proteins. Enhancement of protein microarray sensitivities is an important goal, especially because many molecular targets within patient tissues are of low abundance. The ideal array substrate will have a high protein-binding affinity and low intrinsic signal. To date, nitrocellulose-coated glass has provided an effective substrate for protein binding in the microarray format when using chromogenic detection systems. As fluorescent systems, such as quantum dots, are explored as potential reporter agents, the intrinsic fluorescent properties of nitrocellulose-coated glass slides limit the ability to image microarrays for extended periods of time where increases in net sensitivity can be attained. Silicon, with low intrinsic autofluorescence, is being explored as a potential microarray surface. Native silicon has low binding potential. Through titrated reactive ion etching (RIE), varying surface areas have been created on silicon in order to enhance protein binding. Further, via chemical modification, reactive groups have been added to the surfaces for comparison of relative protein binding. Using this combinatorial method of surface roughening and surface coating, 3-aminopropyltriethoxysilane (APTES) and mercaptopropyltrimethoxysilane (MPTMS) treatments were shown to transform native silicon into a protein-binding substrate comparable to nitrocellulose.

Microarrays as validation strategies in clinical samples: tissue and protein microarrays

The widespread use of DNA microarrays has led to the discovery of many genes whose expression profile may have significant clinical relevance. The translation of this data to the bedside requires that gene expression be validated as protein expression, and that annotated clinical samples be available for correlative and quantitative studies to assess clinical context and usefulness of putative biomarkers. We review two microarray platforms developed to facilitate the clinical validation of candidate biomarkers: tissue microarrays and reverse-phase protein microarrays. Tissue microarrays are arrays of core biopsies obtained from paraffin-embedded tissues, which can be assayed for histologically-specific protein expression by immunohistochemistry. Reverse-phase protein microarrays consist of arrays of cell lysates or, more recently, plasma or serum samples, which can be assayed for protein quantity and for the presence of post-translational modifications such as phosphorylation. Although these platforms are limited by the availability of validated antibodies, both enable the preservation of precious clinical samples as well as experimental standardization in a high-throughput manner proper to microarray technologies. While tissue microarrays are rapidly becoming a mainstay of translational research, reverse-phase protein microarrays require further technical refinements and validation prior to their widespread adoption by research laboratories.

Down-Regulation of Bax and Bak in Immuno-Chemotherapy Resistant Non-Hodgkin’s Lymphoma Cells

The balance between pro-apoptotic (Bax, Bak) and anti-apoptotic (Bcl-2, Bcl-xL, Mcl-1) Bcl-2 family proteins is essential for the maintenance of B-cell homeostasis. Disruption of this critical balance occurs in the majority of B-cell neoplasms. Clinically, high Bcl-2/Bak and Bcl-2/Bax ratios have been associated with decreased median survival (7.3 years and 3.8 years, respectively) in follicular lymphoma patients1. Recent work in mouse embryonic fibroblasts deficient for the multi-domain pro-apoptotic Bcl-2 family proteins Bax and Bak has shown that they are essential for induction of cell death following apoptotic stimuli that act through the mitochondrial (intrinsic) pathway2. The vast majority of clinically available anti-neoplastic agents, including rituximab, are known to induce cell death via this pathway and therefore likely rely on Bax and/or Bak to exert their anti-tumor effects. Alteration in expression of Bax and/or Bak could therefore underlie acquired resistance to rituximab and chemotherapy in NHL patients. To study the phenomenon of rituximab resistance we developed several rituximab-resistant cell lines (RRCL) that we subsequently showed were also resistant to chemotherapy. RRCL were generated by exposing Raji, SU-DHL-4 and RL cells to escalating doses of rituximab +/− human serum and subsequently cloning by limited dilution. In our present work we studied the efficacy of clinically-applicable chemotherapeutic agents against RRCL. Additionally we studied the intrinsic apoptotic pathway in an attempt to explain shared mechanisms of resistance to chemotherapy and rituximab. We found that RRCL have dramatically reduced levels of both Bax and Bak proteins by Western blot while levels of Bcl-2, Bcl-xL and Mcl-1 protein were comparable to parental cells. Transfection of RRCL with Bax or Bak sensitized them to apoptotic cell death. Currently, we are attempting to validate previous studies that have shown that down-regulation of Bax and/or Bak correlates with a poor prognosis in NHL. Additionally, we are exploring the mechanism(s) by which Bax and Bak are down-regulated in RRCL and primary patient samples.

Technology insight: pharmacoproteomics for cancer--promises of patient-tailored medicine using protein microarrays

Patient-tailored medicine can be defined as the selection of specific therapeutics to treat disease in a particular individual based on genetic, genomic or proteomic information. While individualized treatments have been used in medicine for years, advances in cancer treatment have now generated a need to more precisely define and identify those patients who will derive the most benefit from new-targeted agents. Cellular signaling pathways are a protein-based network, and the intended drug effect is to disrupt aberrant protein phosphorylation-based enzymatic activity and epigenetic phenomena. Pharmacoproteomics, or the tailoring of therapy based on proteomic knowledge, will begin to take a central role in this process. A new type of protein array platform, the reverse-phase protein microarray, shows potential for providing detailed information about the state of the cellular 'circuitry' from small samples such as patient biopsy specimens. Measurements of hundreds of specific phosphorylated proteins that span large classes of important signaling pathways can be obtained at once from only a few thousand cells. Clinical implementation of these new proteomic tools to aid the clinical, medical and surgical oncologist in making decisions about patient care will now require thoughtful communication between practicing clinicians and research scientists.

Genomics and proteomics: emerging technologies in clinical cancer research

Fueled by the complete genomic data acquired from the human genome project and the desperate clinical need of comprehensive analytical tools to study a heterogeneous disease like cancer, genomic and proteomic technologies have evolved rapidly, accelerating the rate and number of discoveries in clinical cancer research. These discoveries include mechanistic understanding of cancer biology as well as the identification of biomarkers supporting early detection, molecular classification of tumors, molecular predictors of metastasis, treatment response, and prognosis. While the technical advances have been significant, clinical researchers and practicing physicians are now confronted with the challenges of understanding technically and statistically complex data sets, translating this complex information to fit clinical contexts and incorporating it into clinical studies. In this review, we will summarize the available technologies and associated bioinformatics, discuss studies that are clinically relevant, and discuss the limitations we are still facing. We will present a framework for future directions of these technologies and how we believe they should be applied in clinical studies.

Array-based proteomics: mapping of protein circuitries for diagnostics, prognostics, and therapy guidance in cancer

The human proteome, due to the enormity of post-translational permutations that result in large numbers of isoforms, is much more complex than the genome and alterations in cancer can occur in ways that are not predictable by translational analysis alone. Proteomic analysis therefore represents a more direct way of investigating disease at the individual patient level. Furthermore, since most novel therapeutic targets are proteins, proteomic analysis potentially has a central role in patient care. At the same time, it is becoming clear that mapping entire networks rather than individual markers may be necessary for robust diagnostics as well as tailoring of therapy. Consequently, there is a need for high-throughput multiplexed proteomic techniques, with the capability of scanning multiple cases and analysing large numbers of endpoints. New types of protein arrays combined with advanced bioinformatics are currently being used to identify molecular signatures of individual tumours based on protein pathways and signalling cascades. It is envisaged that analysing the cellular 'circuitry' of ongoing molecular networks will become a powerful clinical tool in patient management.