Similarities of prosurvival signals in Bcl-2-positive and Bcl-2-negative follicular lymphomas identified by reverse phase protein microarray

B-cell Lymphoma 6 (BCL6): From Master Regulator of Humoral Immunity to Oncogenic Driver in Pediatric Cancers

B-cell lymphoma 6 (BCL6) is a protooncogene in adult and pediatric cancers, first identified in diffuse large B-cell lymphoma (DLBCL) where it acts as a repressor of the tumor suppressor TP53, conferring survival, protection, and maintenance of lymphoma cells. BCL6 expression in normal B cells is fundamental in the regulation of humoral immunity, via initiation and maintenance of the germinal centers (GC). Its role in B cells during the production of high affinity immunoglobins (that recognize and bind specific antigens) is believed to underpin its function as an oncogene. BCL6 is known to drive the self-renewal capacity of leukemia-initiating cells (LIC), with high BCL6 expression in acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), and glioblastoma (GBM) associated with disease progression and treatment resistance. The mechanisms underpinning BCL6-driven therapy resistance are yet to be uncovered; however, high activity is considered to confer poor prognosis in the clinical setting. BCL6's key binding partner, BCL6 corepressor (BCOR), is frequently mutated in pediatric cancers and appears to act in concert with BCL6. Using publicly available data, here we show that BCL6 is ubiquitously overexpressed in pediatric brain tumors, inversely to BCOR, highlighting the potential for targeting BCL6 in these often lethal and untreatable cancers. In this review, we summarize what is known of BCL6 (role, effect, mechanisms) in pediatric cancers, highlighting the two sides of BCL6 function, humoral immunity, and tumorigenesis, as well as to review BCL6 inhibitors and highlight areas of opportunity to improve the outcomes of patients with pediatric cancer.

Proteomic Strategies and their Application in Cancer Research

The understanding of carcinogenesis and tumor progression on a molecular basis needs a detailed study of proteins as effector molecules and as critical components of the multiple interconnected signaling pathways that drive the neoplastic phenotype. Thus, the proteomic approach represents a powerful tool for the challenge of the post-genomic era. The term “cancer proteome” refers to the collection of proteins expressed by a given cancer cell and should be considered as a highly dynamic entity within the cell, which affects a variety of cellular activities. The emerging proteomic analysis platforms including 2D-PAGE, mass spectrometry technologies, and protein microarrays represent powerful tools to study and understand cancer. These systems aim to not only identify, catalogue, and characterize cancer proteins, but also to unveil how they interact to affect overall tumor progression. Moreover, recent studies on various cancers have reported promising results concerning the detection of novel molecular biomarkers useful in the early diagnosis of cancer and in drug discovery. Thus, a new subdiscipline named clinical proteomics, concomitant with new molecular technologies that are developed, demonstrates promise to discover new cancer biomarkers. The early diagnosis of cancer, even in a premalignant state, is crucial for the successful treatment of this disease. For these reasons, it is clear that the identification of biomarkers for the early diagnosis of cancer should represent one of the main goals of this emerging field of study.

Unraveling Tumor Heterogeneity in an Apparently Monolithic Disease: BCL2 and Other Players in the Genetic Landscape of Nodal Follicular Lymphoma

Follicular lymphoma (FL) is the most common form of non-Hodgkin lymphoma in Western countries. Although traditionally considered a well-defined, easy to diagnose lymphoproliferative disorder, in the last few years it has become clear that it is in fact composed of many different clinicopathological entities, encompassing a variegated and complex genetic background. This has led to the inclusion of specific FL variants and separate entities in the latest update of the WHO classification. However, even in the context of classical FL, many aspects of intra- and inter-tumoral heterogeneity have been recognized, with a major influence on diagnosis and clinical practice at different time points during the course of the disease. This review focuses on the molecular cytogenetic heterogeneity in classical FL from precursors and early development to progression and transformation, in terms of both clonal heterogeneity and unusual genetic features. Several factors have been investigated and suggested to contribute to the broad spectrum of clinicopathological, phenotypic, and genetic features observed in otherwise morphologically classical cases. Among them, deregulation of the epigenetic machinery and interactions with tumor microenvironment seem to play a pivotal role, together with genetic aberrations involving well-known molecular pathways and mechanisms physiologically operating in the germinal center. In the era of personalized medicine, precision diagnostics based both on understanding of the complex interplay among all these factors and on novel developments will become crucial to predict the outcome and guide the treatment of FL patients.

Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.

The PI3K pathway in B cell metabolism

B cell growth and proliferation is tightly regulated by signaling through the B cell receptor and by other membrane bound receptors responding to different cytokines. The PI3K signaling pathway has been shown to play a crucial role in B cell activation, differentiation and survival. Activated B cells undergo metabolic reprograming in response to changing energetic and biosynthetic demands. B cells also need to be able to coordinate metabolic activity and proliferation with nutrient availability. The PI3K signaling network has been implicated in regulating nutrient acquisition, utilization and biosynthesis, thus integrating receptor-mediated signaling with cell metabolism. In this review, we discuss the current knowledge about metabolic changes induced in activated B cells, strategies to adapt to metabolic stress and the role of PI3K signaling in these processes.

Invited Review: Toxicoproteomics: Proteomics Applied to Toxicology and Pathology

Global measurement of proteins and their many attributes in tissues and biofluids defines the field of proteomics. Toxicoproteomics, as part of the larger field of toxicogenomics, seeks to identify critical proteins and pathways in biological systems that are affected by and respond to adverse chemical and environmental exposures using global protein expression technologies. Toxicoproteomics integrates 3 disciplinary areas: traditional toxicology and pathology, differential protein and gene expression analysis, and systems biology. Key topics to be reviewed are the evolution of proteomics, proteomic technology platforms and their capabilities with exemplary studies from biology and medicine, a review of over 50 recent studies applying proteomic analysis to toxicological research, and the recent development of databases designed to integrate -Omics technologies with toxicology and pathology. Proteomics is examined for its potential in discovery of new biomarkers and toxicity signatures, in mapping serum, plasma, and other biofluid proteomes, and in parallel proteomic and transcriptomic studies. The new field of toxicoproteomics is uniquely positioned toward an expanded understanding of protein expression during toxicity and environmental disease for the advancement of public health.

The serine-threonine kinase p90RSK is a new target of enzastaurin in follicular lymphoma cells

BACKGROUND AND PURPOSE

Follicular lymphoma is the second most common non-Hodgkin's lymphoma and, despite the introduction of rituximab for its treatment, this disease is still considered incurable. Besides genetic alterations involving Bcl-2, Bcl-6 or c-Myc, follicular lymphoma cells often display altered B-cell receptor signalling pathways including overactive PKC and PI3K/Akt systems.

EXPERIMENTAL APPROACH

The effect of enzastaurin, an inhibitor of PKC, was evaluated both in vitro on follicular lymphoma cell lines and in vivo on a xenograft murine model. Using pharmacological inhibitors and siRNA transfection, we determined the different signalling pathways after enzastaurin treatment.

KEY RESULTS

Enzastaurin inhibited the serine-threonine kinase p90RSK which has downstream effects on GSK3β. Bad and p70S6K. These signalling proteins control follicular lymphoma cell survival and apoptosis; which accounted for the inhibition by enzastaurin of cell survival and its induction of apoptosis of follicular lymphoma cell lines in vitro. Importantly, these results were replicated in vivo where enzastaurin inhibited the growth of follicular lymphoma xenografts in mice.

CONCLUSIONS AND IMPLICATIONS

The targeting of p90RSK by enzastaurin represents a new therapeutic option for the treatment of follicular lymphoma.

Constitutive AKT activation in follicular lymphoma

BACKGROUND

The phosphoinositide 3- kinase (PI3K) pathway is involved in the growth of various human cancers, including lymphoid malignancies. However its role in the pathogenesis of follicular lymphoma (FL) has not been yet described.

METHODS

To clarify this point, biopsy tissue samples from 38 human FL cases were investigated for PIK3CA somatic mutations in exon 9 and 20 using direct sequencing. The same samples were analyzed using western blotting and immunohistochemistry to detect expression of AKT, phosphorylated AKT (pAKT), and PTEN proteins. Two cases of benign lymphadenitis were used as controls.

RESULTS

AKT expression was present in all FL and lymphadenitis cases. 14/38 (37%) FL and 2/2 lymphadenitis cases expressed pAKT. 9/38 (24%) FL samples showed high level of pAKT, whereas 5/38 (13%) FL cases and 2/2 benign lymphadenitis samples expressed low level of pAKT. PTEN expression was observed in 30/38 (79%) FL and 2/2 benign lymphadenitis cases, whereas 8/38 (21%) FL cases showed loss of PTEN expression. 3 cases with positive pAKT did not express PTEN. PIK3CA mutations were not detected in any sample.

CONCLUSIONS

These data suggest that the PI3K/AKT signaling pathway could be activated in a subset of FL cases, due to either AKT phosphorylation or PTEN downregulation, in the absence of PIK3CA mutations.

Protein pathway analysis in Clinical Proteomics using protein microarrays

Molecular diagnostics research within the field of cancer is increasingly focused on detecting low-abundance protein endpoints that can be used to define a patient's disease more completely. Protein microarrays represent an important Clinical Proteomics tool for directly measuring protein endpoints in samples extracted from patient tissues. By combining laser capture microdissection, arraying devices, validated isoform-specific antibodies and advanced reporter technology tools, Clinical Proteomics laboratories are currently generating molecular portraits of cancer cells harvested from patient biopsies.:

Disruption of follicular dendritic cells-follicular lymphoma cross-talk by the pan-PI3K inhibitor BKM120 (Buparlisib)

PURPOSE

To uncover the signaling pathways underlying follicular lymphoma-follicular dendritic cells (FL-FDC) cross-talk and its validation as new targets for therapy.

EXPERIMENTAL DESIGN

FL primary cells and cell lines were cocultured in the presence or absence of FDC. After 24 and 48 hours, RNA was isolated from FL cells and subjected to gene expression profiling (GEP) and data meta-analysis using DAVID and GSEA softwares. Blockade of PI3K pathway by the pan-PI3K inhibitor BKM120 (buparlisib; Novartis Pharmaceutical Corporation) and the effect of PI3K inhibition on FL-FDC cross-talk were analyzed by means of ELISA, RT-PCR, human umbilical vein endothelial cell tube formation, adhesion and migration assays, Western blot, and in vivo studies in mouse FL xenografts.

RESULTS

GEP of FL-FDC cocultures yields a marked modulation of FL transcriptome by FDC. Pathway assignment by DAVID and GSEA software uncovered an overrepresentation of genes related to angiogenesis, cell adhesion, migration, and serum-response factors. We demonstrate that the addition of the pan-PI3K inhibitor BKM120 to the cocultures was able to downregulate the expression and secretion of proangiogenic factors derived from FL-FDC cocultures, reducing in vitro and in vivo angiogenesis. Moreover, BKM120 efficiently counteracts FDC-mediated cell adhesion and impedes signaling and migration induced by the chemokine CXCL12. BKM120 inhibits both constitutive PI3K/AKT pathway and FDC- or CXCL12-induced PI3K/AKT pathway, hampers FDC survival signaling, and reduces cell proliferation of FL cells in vitro and in mouse xenografts.

CONCLUSIONS

These data support the use of BKM120 in FL therapy to counteract microenvironment-related survival signaling in FL cells.

Another look at follicular lymphoma: immunophenotypic and molecular analyses identify distinct follicular lymphoma subgroups

AIMS

The aim of this study was to analyse the immunophenotypic and molecular features of a large series of follicular lymphomas, focusing in particular on atypical cases that fail to express CD10 and/or bcl-2. Such cases present diagnostic pitfalls, especially with regard to the differential diagnosis from follicular hyperplasia and marginal zone B-cell lymphoma. Therefore, we also included an immunohistochemical evaluation of stathmin, which is strongly expressed by germinal centre B cells, as a putative new marker for follicular lymphomas, particularly those with an atypical phenotype.

METHODS AND RESULTS

Two hundred and five follicular lymphomas were investigated with immunohistochemistry and fluorescence in-situ hybridization (FISH). The use of three distinct anti-bcl-2 antibodies together with CD10 expression data and FISH analysis for bcl-2 and bcl-6 rearrangements allowed subclassification of follicular lymphoma into four distinct subgroups: (i) CD10-positive/bcl-2-positive, (ii) CD10-positive/bcl-2-negative, (iii) CD10-negative/bcl-2-positive, and (iv) CD10-negative/bcl-2-negative. All cases were bcl-6-positive. STMN1 (stathmin) was shown to be helpful in diagnosing bcl-2-negative and/or CD10-negative follicular lymphomas, and in their distinction from marginal zone B-cell lymphoma.

CONCLUSIONS

Combined immunohistological and molecular analyses reveal that follicular lymphomas showing an atypical immunophenotypic and molecular profile exist, and we demonstrate that STMN1 represents a novel useful diagnostic marker for these.

Immunohistochemical Expression Study of Proapoptotic BH3-Only Protein Bad in Canine Nonneoplastic Tissues and Canine Lymphomas

The BH3-only protein Bad is a proapoptotic Bcl-2 family member that acts as a sensitizer in intrinsic apoptosis by inactivating antiapoptotic members through heterodimer formation. Bad has been shown to contribute to tumorigenesis, including lymphoma formation in humans and mice, through alteration in expression or functional status. Here, its immunohistochemical expression was analyzed in canine nonneoplastic and lymphoma tissues using tissue microarrays. Bad was expressed in the cytoplasm of a wide range of nonneoplastic tissues, especially epithelial cells. Nonneoplastic lymph nodes displayed weak immunostaining in the follicular germinal centers only. Immunoblotting supported these observations but also revealed presence of nonspecific labeling in some organs. Of 81 lymphomas, 29 (35.8%) displayed moderate to strong immunohistochemical Bad labeling, and a significant expression increase was found in lymphomas (especially B cell and double negative) compared to nonneoplastic lymph nodes. These findings warrant further investigations of the functional status, the involvement of partner proteins, and a possible impact of Bad on prognosis in canine lymphoma.

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.

Optimizing targeted cancer therapy: towards clinical application of systems biology approaches

In cancer, genetic and epigenetic alterations ultimately culminate in discordant activation of signal transduction pathways driving the malignant process. Pharmacological or biological inhibition of such pathways holds significant promise with respect to devising rational therapy for cancer. Thus, technical concepts pursuing robust characterization of kinase activity in tissue samples from cancer patients have been subject of investigation. In the present review we provide a comprehensive overview of these techniques and discuss their advantages and disadvantages for systems biology approaches to identify kinase targets in oncological disease. Recent advances in the development and application of array-based peptide-substrate kinase activity screens show great promise in overcoming the discrepancy between the evaluation of aberrant cell signaling in specific malignancies or even individual patients and the currently available ensemble of highly specific targeted treatment strategies. These developments have the potential to result in a more effective selection of kinase inhibitors and thus optimize mechanism-based patient-specific therapeutic strategies. Given the results from current research on the tumor kinome, generating network views on aberrant tumor cell signaling is critical to meet this challenge.

Variation in BCL2 protein expression in follicular lymphomas without t(14;18) chromosomal translocations

AIM

The hallmark of follicular lymphoma is the t(14;18)(q32;q21) chromosomal translocations that lead to deregulation of BCL2 expression in tumour cells. However, not all cases of follicular lymphoma express BCL2, nor is the t(14;18) translocation always present. Follicular lymphomas lacking the BCL2 rearrangement are less well studied with regards to their immunohistochemical and molecular features. This study aims to investigate the BCL2 protein expression pattern in t(14;18) negative follicular lymphomas.

METHODS

BCL2 protein expression pattern was analysed in 26 cases of t(14;18) negative follicular lymphoma [determined by fluorescence in situ hybridisation (FISH)], using antibodies against two-different epitopes, i.e., the widely-used antibody BCL2/124 and an alternative antibody E17.

RESULTS

Two of the t(14;18) negative cases showed evidence of BCL2 amplification and trisomy 18. A total of 13 cases (50%) lacked BCL2 expression. In 10 cases (38%) the expression was heterogeneous and in only three cases (12%) the BCL2 expression was strongly positive. These cases could thus be subdivided into three subgroups: Group I, normal BCL2 genes (i.e., no evidence of translocation or amplification), and BCL2 protein negative; Group II, normal BCL2 genes but BCL2 protein positive; and Group III, presence of other genetic alterations, i.e., BCL2 amplification and trisomy 18, and BCL2 protein positive.

CONCLUSIONS

This study suggests that it may be possible on the basis of staining to predict that the t(14;18) translocation is absent if a case is either negative for BCL2 protein with different antibodies or has heterogeneous BCL2 expression, possibly acquired through a physiological process of differentiation.

Surface Adjustment of Reverse Phase Protein Arrays using Positive Control Spots

Reverse phase protein arrays (RPPA) measure the relative expression levels of a protein in many samples simultaneously. Observed signal from these arrays is a combination of true signal, additive background, and multiplicative spatial effects. Background subtraction alone is not sufficient to remove all nonbiological trends from the data. We developed a surface adjustment that uses information from positive control spots to correct for spatial trends on the array beyond additive background. This method uses a generalized additive model to estimate a smoothed surface from positive controls. When positive controls are printed in a dilution series, a nested surface adjustment performs an intensity-based correction. When applicable, surface adjustment is able to remove spatial trends and increase within slide replicate agreement better than background subtraction alone as demonstrated on two sets of arrays. This work demonstrates the importance of including positive control spots on the array.

Targeting the PI3K/AKT/mTOR pathway in non-Hodgkin's lymphoma: results, biology, and development strategies

Signaling by the PI3K/AKT/mTOR pathway is frequently deregulated in non-Hodgkin's lymphoma (NHL), prompting evaluation of the rapamycin-analog (rapalog) mTOR inhibitors in multiple clinical trials. The drugs show activity as single agents, and the rapalog temsirolimus is now accepted as a therapeutic option in relapsed/refractory mantle cell lymphoma. Response rates, however, are typically below 50%, resulting in remissions that are neither complete nor durable. Results of preclinical studies shed important new light on resistance mechanisms that may explain results. Looking ahead, it is likely PI3K/AKT/mTOR inhibition will find expanded roles in NHL therapy due to 1) assessments of the rapalogs in combination with other therapies and in less heavily pretreated patients, 2) the development and evaluation of multiple novel inhibitors of the pathway that may increase specificity and potency, 3) alternative treatment strategies able to bypass particular resistance mechanisms, and 4) increased efforts to identify biomarkers for better pretreatment patient stratification.

A new frontier in personalized cancer therapy: mapping molecular changes

Mutations in the genome of a normal cell can affect the function of its many genes and pathways. These alterations could eventually transform the cell from a normal to a malignant state by allowing an uncontrolled proliferation of the cell and formation of a cancer tumor. Each tumor in an individual patient can have hundreds of mutated genes and perturbed pathways. Cancers clinically presenting as the same type or subtype could potentially be very different at the molecular level and thus behave differently in response to therapy. The challenge is to distinguish the key mutations driving the cancer from the background of mutational noise and find ways to effectively target them. The promise is that such a molecular approach to classifying cancer will lead to better diagnostic, prognostic and personalized treatment strategies. This article provides an overview of advances in the molecular characterization of cancers and their applications in therapy.

The Role of mTOR Inhibitors for the Treatment of B-Cell Lymphomas

Despite the fact that the majority of lymphomas initially respond to treatment, many patients relapse and die from disease that is refractory to current regimens. The need for new treatment strategies in lymphomas has led to the investigation and evaluation of novel agents that target cellular pathways. The mammalian target of rapamycin (mTOR) is a representative pathway that may be implicated in lymphomagenesis. Rapamycin and especially its derivatives (temsirolimus, everolimus, and deforolimus) represent the first described mTOR inhibitors. These agents have shown promising results in the treatment of lymphoid malignancies. On the other hand, new ATP-competitive mTOR inhibitors that provoke a broader inhibition of mTOR activity are in early stages of clinical development. The purpose of this paper is to summarize the existing knowledge about mTOR inhibitors and their use in the treatment of B-cell lymphomas. Relevant issues regarding mTOR biology in general as well as in B-cell lymphoid neoplasms are also discussed in short.

Reverse phase protein microarrays for clinical applications

Phosphorylated proteins represent one of the most important constituents of the proteome and are under intense analysis by the biotechnology and pharmaceutical industry because of their central role for cellular signal transduction. Indeed, alterations in cellular signaling and control mechanisms that modulate signal transduction, functionally underpin most human cancers today. Beyond their central role as the causative components of tumorigenesis, these proteins have become an important research focus for discovery of predictive and prognostic biomarkers. Consequently, these pathway constituents comprise a powerful biomarker subclass whereby the same analyte that provides prediction and/or prognosis is also the drug target itself: a theranostic marker. Reverse phase protein microarrays have been developed to generate a functional patient-specific circuit "map" of the cell signaling networks based directly on cellular analysis of a biopsy specimen. This patient-specific circuit diagram provides key information that identifies critical nodes within aberrantly activated signaling that may serve as drug targets for individualized or combinatorial therapy. The protein arrays provide a portrait of the activated signaling network by the quantitative analysis of the phosphorylated, or activated, state of cell signaling proteins. Based on the growing realization that each patient's tumor is different at the molecular level, the ability to measure and profile the ongoing phosphoprotein biomarker repertoire provides a new opportunity to personalize therapy based on the patient-specific alterations.

Reverse phase protein microarrays advance to use in clinical trials

Individualizing cancer therapy for molecular targeted inhibitors requires a new class of molecular profiling technology that can map the functional state of the cancer cell signal pathways containing the drug targets. Reverse phase protein microarrays (RPMA) are a technology platform designed for quantitative, multiplexed analysis of specific phosphorylated, cleaved, or total (phosphorylated and non-phosphorylated) forms of cellular proteins from a limited amount of sample. This class of microarray can be used to interrogate tissue samples, cells, serum, or body fluids. RPMA were previously a research tool; now this technology has graduated to use in research clinical trials with clinical grade sensitivity and precision. In this review we describe the application of RPMA for multiplexed signal pathway analysis in therapeutic monitoring, biomarker discovery, and evaluation of pharmaceutical targets, and conclude with a summary of the technical aspects of RPMA construction and analysis.

Pseudonegative BCL2 protein expression in a t(14;18) translocation positive lymphoma cell line: a need for an alternative BCL2 antibody

AIM

The t(14;18)(q32;q21) chromosomal translocation induces BCL2 protein expression in most follicular lymphomas. However, a small number of cases lack BCL2 expression despite carrying the t(14;18)(q32;q21) translocation. This study aims to explore the mechanism accounting for the lack of BCL2 protein expression when the t(14;18) translocation is present.

METHODS

BCL2 expression in the t(14;18) positive cell lines FL18, Karpas-422, SU-DHL-4 and SU-DHL-6, was analysed by Western blotting and by immunohistochemistry using two different antibodies. FISH analysis was performed to confirm the cytogenetic changes in the cell lines and real time quantitative PCR was used to evaluate the BCL2 mRNA level. Sequence analysis of translocated BCL2 was performed on FL18, Karpas-422, SU-DHL-4 and SU-DHL-6 cell lines.

RESULTS

In FL18, Karpas-422, and SU-DHL-4, the BCL2 mRNA level correlated with the BCL2 protein expression. In contrast, BCL2 protein was not detected in SU-DHL-6 line using standard anti-BCL2 antibody (BCL2/124), despite the presence of the t(14;18) translocation and high level of mRNA. cDNA sequencing of translocated BCL2 showed three mutations in the SU-DHL-6 cell line, one of which resulted in an amino acid substitution (I48F) in the region recognised by the standard BCL2 antibody, whereas the other two were silent mutations at aa71 and aa72. Interestingly, when BCL2 expression was tested with an alternative antibody, E17, the protein was detected in SU-DHL-6, suggesting that the 'negativity' of SU-DHL-6 line for BCL2 using the standard antibody is spurious. Amino acid changes were found in Karpas-422 (G47D, P59L) and SU-DHL-4 (P59T, S117R) but these did not affect BCL2 detection.

CONCLUSIONS

This study suggests that some somatic mutations of the translocated BCL2 gene may prevent epitope recognition by BCL2 antibodies, and hence cause false negative expression using the standard antibody. It is recommended that in practice all BCL2 negative cases should routinely be stained with an alternative antibody to prevent false negativity.

Prognostic Factors in Follicular Lymphoma

Follicular lymphoma (FL) is one of the most common types of non-Hodgkin's lymphoma. It is usually diagnosed at an advanced stage, for which many treatment options exist, however, no curative standard therapy has been identified. The outcome is highly variable with a median survival of approximately 10 years. The life expectancy of patients with FL has been extended with the use of rituximab, a monoclonal antibody targeting the CD20 antigen on FL cells, but there remains a group of patients who fail to respond to chemoimmunotherapy and die early of their disease. Transformation of FL to an aggressive histology is an important event with high morbidity and mortality. The Follicular Lymphoma International Prognostic Index has become the clinically useful prognostic tool, but gives only a rough estimate of expected outcome. There is a need for useful biomarkers for prediction of the disease course of single patients to individualize therapy, especially in the new era of chemoimmunotherapy.

Future of personalized medicine in oncology: a systems biology approach

The development of cost-effective technologies able to comprehensively assess DNA, RNA, protein, and metabolites in patient tumors has fueled efforts to tailor medical care. Indeed validated molecular tests assessing tumor tissue or patient germline DNA already drive therapeutic decision making. However, many theoretical and regulatory challenges must still be overcome before fully realizing the promise of personalized molecular medicine. The masses of data generated by high-throughput technologies are challenging to manage, visualize, and convert to the knowledge required to improve patient outcomes. Systems biology integrates engineering, physics, and mathematical approaches with biologic and medical insights in an iterative process to visualize the interconnected events within a cell that determine how inputs from the environment and the network rewiring that occurs due to the genomic aberrations acquired by patient tumors determines cellular behavior and patient outcomes. A cross-disciplinary systems biology effort will be necessary to convert the information contained in multidimensional data sets into useful biomarkers that can classify patient tumors by prognosis and response to therapeutic modalities and to identify the drivers of tumor behavior that are optimal targets for therapy. An understanding of the effects of targeted therapeutics on signaling networks and homeostatic regulatory loops will be necessary to prevent inadvertent effects as well as to develop rational combinatorial therapies. Systems biology approaches identifying molecular drivers and biomarkers will lead to the implementation of smaller, shorter, cheaper, and individualized clinical trials that will increase the success rate and hasten the implementation of effective therapies into the clinical armamentarium.

Immunoexpression of Survivin in non-neoplastic lymphoid tissues and malignant lymphomas using a new monoclonal antibody reactive on paraffin sections

Survivin is a member of the inhibitor of apoptosis gene family, which is also implicated in mitosis regulation. Most reports in the literature impute poor prognosis to neoplasms with overexpression of this protein. The purpose of the present study is to validate and compare the immunohistochemical reactivity of malignant lymphomas and reactive lymphoid tissue using a new mouse monoclonal antibody to Survivin produced in our laboratory, 6-78. Survivin was detected by immunohistochemistry on tissue microarrays. It was shown that the antibody anti-Survivin 6-78 reliably stains formalin-fixed, paraffin-embedded reactive and neoplastic lymphoid tissues, mostly in a nuclear pattern. We confirmed using this novel antibody that Survivin immunostaining has a tendency to be lower in reactive lymphoid tissues and low-grade B cell lymphomas than in aggressive lymphomas. This antibody may represent a useful tool for standardizing the study of the immunoexpression of Survivin in neoplasms.

Proteomics and systems biology: application in drug discovery and development

Studies of complex biological systems aimed at understanding their functions at a global level are the goals of systems biology. Proteomics, generally regarded as the comprehensive study of the expression of all the proteins at a particular time in different organs, tissues, and cell types is a key enabling technology for the systems biology approach. Rapid advances in this regard have been made following the success of the human genome project as well as those of various animals and microorganisms. Possibly, one of the most promising outcomes from studies on the human genome and proteome is the identification of potential new drugs for the treatment of different diseases and tailoring the drugs for individualized patient therapy. Following the identification of a new drug candidate, knowledge on organ and system-level responses helps prioritize the drug targets and design clinical trials based on their efficacy and safety. Toxicoproteomics is playing an important role in that respect. In essence, over the past decade, proteomics has played a major role in drug discovery and development. In this review article, we explain systems biology, discuss the current proteomic technologies, and highlight some important applications of proteomics and systems biology approaches in drug discovery and development.

Application of physicochemically modified silicon substrates as reverse-phase protein microarrays

Physicochemically modified silicon substrates can provide a high quality alternative to nitrocellulose-coated glass slides for use in reverse-phase protein microarrays. Enhancement of protein microarray sensitivities is an important goal, especially because molecular targets within patient tissues exist in low abundance. The ideal array substrate has a high protein binding affinity and low intrinsic background signal. Silicon, which has low intrinsic autofluorescence, is being explored as a potential microarray surface. In a previous paper ( Nijdam , A. J. ; Cheng , M. M.-C. ; Fedele , R. ; Geho , D. H. ; Herrmann , P. ; Killian , K. ; Espina , V. ; Petricoin , E. F. ; Liotta , L. A. ; Ferrari , M. Physicochemically Modified Silicon as Substrate for Protein Microarrays . Biomaterials 2007 , 28 , 550 - 558 ), it is shown that physicochemical modification of silicon substrates increases the binding of protein to silicon to a level comparable with that of nitrocellulose. Here, we apply such substrates in a reverse-phase protein microarray setting in two model systems.

Variable slope normalization of reverse phase protein arrays

MOTIVATION

Reverse phase protein arrays (RPPA) measure the relative expression levels of a protein in many samples simultaneously. A set of identically spotted arrays can be used to measure the levels of more than one protein. Protein expression within each sample on an array is estimated by borrowing strength across all the samples, but using only within array information. When comparing across slides, it is essential to account for sample loading, the total amount of protein printed per sample. Currently, total protein is estimated using either a housekeeping protein or the sample median across all slides. When the variability in sample loading is large, these methods are suboptimal because they do not account for the fact that the protein expression for each slide is estimated separately.

RESULTS

We propose a new normalization method for RPPA data, called variable slope (VS) normalization, that takes into account that quantification of RPPA slides is performed separately. This method is better able to remove loading bias and recover true correlation structures between proteins.

AVAILABILITY

Code to implement the method in the statistical package R and anonymized data are available at (http://bioinformatics.mdanderson.org/supplements.html).

Bcl-xL gene expression correlated with lower apoptotic cell numbers and shorter progression-free survival in PCFCL

The expression of bcl-x(L), an antiapoptotic member of the bcl-2 family, has been correlated with poor prognosis in nodal follicular lymphomas (NFLs). So far, it has not been studied in primary cutaneous follicle center lymphomas (PCFCLs), which, compared with NFLs, express less frequently t(14;18)(q32;q21) and bcl-2. Using real-time PCR we measured bcl-xL and bcl-2 gene expression levels in laser-microdissected lymphoma cells of 20 PCFCL frozen sections. Numbers of apoptotic cells labeled by TUNEL assay were negatively correlated with bcl-xL expression levels (r=-0.840, P<0.005). Bcl-xL expression was significantly higher in biopsies of patients who developed relapse or disease progression later compared with patients who did not (P=0.022), and higher levels of bcl-xL gene expression were significantly correlated with shorter progression-free survival (PFS) (P=0.017). None of these features was correlated with bcl-2 gene expression levels. Our findings indicate that bcl-xL overexpression is inversely correlated with PFS in PCFCL. Moreover, the inverse correlation between bcl-xL expression levels and apoptotic cell numbers suggests that bcl-xL, through its antiapoptotic effect, might contribute to tumor cell survival in PCFCL.

Studying Cellular Processes and Detecting Disease with Protein Microarrays

Protein microarrays are a rapidly developing analytic tool with diverse applications in biomedical research. These applications include profiling of disease markers or autoimmune responses, understanding molecular pathways, protein modifications, and protein activities. One factor that is driving this expanding usage is the wide variety of experimental formats that protein microarrays can take. In this review, we provide a short, conceptual overview of the different approaches for protein microarray. We then examine some of the most significant applications of these microarrays to date, with an emphasis on how global protein analyses can be used to facilitate biomedical research.

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.

Protein microchips in biomedicine and biomarker discovery

Protein microarray technology is of high recent interest, especially for generating confirmatory and complementary information for transcriptomic studies. In this paper, the advantages, technical limitations, main application fields, and some early results of protein microarrays are reviewed. Today protein microchip technology is mostly available in the form of printed glass slides, bioaffinity surfaces, and tissue microarray (TMA)-based techniques. The advantages of glass slide-based microchips are the simplicity of their application and their relatively low cost. Affinity surface-based protein chip techniques are applicable to minute amounts of starting material (< 1 microg), but interrogation of these chips requires expensive instrumentation, such as mass spectrometers. TMAs are useful for parallel testing of antibody specificities on a broad range of histological specimens in a single slide. Protein microarrays have been successfully implemented for serum tumor marker profiling, cell physiology studies, and mRNA expression study verification. Some of the bottlenecks of the technology are protein instability, problems with nonspecific interactions, and the lack of amplification techniques to generate sufficient amounts of the lower abundance proteins. In spite of the current difficulties, protein microchips are envisioned to be available for routine biomedical and diagnostic applications provided that the ongoing technological developments are successful in improving sensitivity, specificity, and reducing costs.

The critical role of histology in an era of genomics and proteomics: a commentary and reflection

The role of histologic examination in lymphoma diagnosis has been called into question by proponents of new technologies, such as genomics and proteomics. We review the history and salient features of morphologic evaluation in lymphoid diseases, and discuss the general and specific limitations of mature ancillary techniques, such as immunohistochemistry, flow cytometry, and molecular studies. We then speculate on the future relationship between morphology and the new genomic and proteomic technologies as they become integrated into clinical practice.

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.

Non-parametric quantification of protein lysate arrays

MOTIVATION

Proteins play a crucial role in biological activity, so much can be learned from measuring protein expression and post-translational modification quantitatively. The reverse-phase protein lysate arrays allow us to quantify the relative expression levels of a protein in many different cellular samples simultaneously. Existing approaches to quantify protein arrays use parametric response curves fit to dilution series data. The results can be biased when the parametric function does not fit the data.

RESULTS

We propose a non-parametric approach which adapts to any monotone response curve. The non-parametric approach is shown to be promising via both simulation and real data studies; it reduces the bias due to model misspecification and protects against outliers in the data. The non-parametric approach enables more reliable quantification of protein lysate arrays.

AVAILABILITY

Code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/jhu/lysatearray-analysis/

Bcl2-negative follicular lymphomas frequently have Bcl6 translocation and/or Bcl6 or p53 expression

Bcl2 is an important protein involved in the pathogenesis of follicular lymphoma (FL). However, approximately 10% of FL cases do not express Bcl2. The present study was designed to compare gene aberrations, prosurvival gene expression, apoptosis and proliferation rates in Bcl2-positive and -negative FL cases. Bcl2 translocation and Bcl6 translocation were detected and compared using fluorescence in situ hybridization (FISH). A tendency for Bcl6 translocation to occur was found more frequently in Bcl2-negative FL than in the Bcl2-positive cases. The expression of Bcl-X, BAX, p53, Bcl6 was analyzed by immunohistochemistry. Bcl2 family proteins Bcl-X and BAX were expressed similarly in the two FL types. In some cases of Bcl2-negative FL there was high expression of Bcl6 or p53 but no such Bcl2-positive FL cases were detected. Furthermore, there was an inverse relationship between the expression of Bcl6 and p53. These results indicate that the Bcl6 translocation occurs more frequently in Bcl2-negative FL. Furthermore, other prosurvival proteins such as p53 and Bcl6 may play an important role in the pathogenesis of Bcl2-negative FL.

Reverse phase protein array: validation of a novel proteomic technology and utility for analysis of primary leukemia specimens and hematopoietic stem cells

Proteomics has the potential to provide answers in cancer pathogenesis and to direct targeted therapy through the comprehensive analysis of protein expression levels and activation status. The realization of this potential requires the development of new, rapid, high-throughput technologies for performing protein arrays on patient samples, as well as novel analytic techniques to interpret them. Herein, we describe the validation and robustness of using reverse phase protein arrays (RPPA) for the analysis of primary acute myelogenous leukemia samples as well as leukemic and normal stem cells. In this report, we show that array printing, detection, amplification, and staining precision are very high, reproducible, and that they correlate with traditional Western blotting. Using replicates of the same sample on the same and/or separate arrays, or using separate protein samples prepared from the same starting sample, the intra- and interarray reproducibility was extremely high. No statistically significant difference in protein signal intensities could be detected within the array setups. The activation status (phosphorylation) was maintained in experiments testing delayed processing and preparation from multiple freeze-thawed samples. Differences in protein expression could reliably be detected in as few as three cell protein equivalents. RPPA prepared from rare populations of normal and leukemic stem cells were successfully done and showed differences from bulk populations of cells. Examples show how RPPAs are ideally suited for the large-scale analysis of target identification, validation, and drug discovery. In summary, RPPA is a highly reliable, reproducible, high-throughput system that allows for the rapid large-scale proteomic analysis of protein expression and phosphorylation state in primary acute myelogenous leukemia cells, cell lines, and in human stem cells.

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.

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.

Modeling of protein signaling networks in clinical proteomics

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomic endpoints in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states. One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor microenvironment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination, clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.