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

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

Expression of Ki-67 and P16 are related with HPV in squamous cell carcinoma of the external auditory canal

Background

Squamous cell carcinoma of the external auditory canal (EACSCC) is an uncommon tumor and responsible for no more than 0.2% of all the head and neck malignancies. Although there is remarkable research evidence exhibiting that high-risk human papillomavirus (HPV) accounts for considerable head and neck malignancies, its role in the pathogenesis of EACSCC is yet to be determined.

Methods

We evaluated 16 patients with EACSCC treated at our department. We employed PCR to assay for high-risk subtypes of HPV. Two pathologists reviewed the histopathological staining via hematoxylin and eosin along with immunohistochemical staining of p16INK4a and Ki‑67.

Results

Detection of HPV DNA was done via PCR in 3 (18.75%) patients, and 8 (50%) positive (+) cases were determined via p16INK4a immunostaining. Besides, 3 (37.5%) individuals were HPV positive as per p16INK4a PCR results. In addition, all of the p16INK4a-positive specimens were diagnosed as moderately differentiated carcinomas.

Conclusions

Expression of Ki-67 was related to HPV status. This is the first report implicating high-risk HPV in squamous cell carcinoma of the external auditory canal. However, p16INK4a immunostaining is a suspectable approach for diagnosing HPV for EACSCC. In addition, HPV might enhance an elevated proliferation rate in EACSCC, illustrated via expression of Ki-67.

Graphical Abstract

Impact of HPV infection on oral squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinomas (HNSCC) are often divided by their aetiology. Noxae associated collectives are compared with the human papilloma virus (HPV)-associated group, whereas different localisations of oral (OSCC) and oropharyngeal (OPSCC) squamous cell carcinomas are mostly discussed as one single group. Our aim was to show that classification by aetiology is not appropriate for OSCC.

RESULTS

HPV DNA was detected by PCR in 7 (3.47%) patients, and we identified 12 (5.94%) positive (+) cases by p16INK4a immunostaining. Only 4 (1.98%) of the p16INK4a+ cases were + for HPV using PCR. Our homogenous collective of OSCC allowed us to compare HPV+ and HPV negative (-) patients without creating bias for tumour localisation, age, gender or tumour stage.

MATERIALS AND METHODS

After testing OSCC samples for HPV positivity, we compared the results of two commonly used HPV detection methods, p16INK4a immunostaining and HPV DNA-related PCR, on 202 OSCC patients. HPV subtypes were determined with an HPV LCD Array Kit. Clinicopathological features of the patients were analysed, and the disease specific survival rates (DSS) for HPV+ and HPV- patients were obtained.

CONCLUSIONS

p16INK4a immunostaining is a not a reliable HPV detection method for OSCC. Positive p16INK4a immunostaining did not agree with + results from PCR of HPV DNA. Furthermore, the influence of HPV-related oncogenic transformation in OSCC is overestimated. The significance of HPV infection remains clinically unclear, and its influence on survival rates is not relevant to OSCC cases.

Tumour heterogeneity: principles and practical consequences

Two major reasons compel us to study tumour heterogeneity: firstly, it represents the basis of acquired therapy resistance, and secondly, it may be one of the major sources of the low level of reproducibility in clinical cancer research. The present review focuses on the heterogeneity of neoplastic disease, both within the primary tumour and between primary tumour and metastases. We discuss different levels of heterogeneity and the current understanding of the phenomenon, as well as imminent developments relevant for clinical research and diagnostic pathology. It is necessary to develop new tools to study heterogeneity and new biomarkers for heterogeneity. Established and new in situ methods will be very useful. In future studies, not only clonal heterogeneity needs to be addressed but also non-clonal phenotypic heterogeneity which might be important for therapy resistance. We also review heterogeneity established in major tumour types, in order to explore potential similarities that might help to define new strategies for targeted therapy.

Reverse Phase Protein Arrays-Quantitative Assessment of Multiple Biomarkers in Biopsies for Clinical Use

Reverse Phase Protein Arrays (RPPA) represent a very promising sensitive and precise high-throughput technology for the quantitative measurement of hundreds of signaling proteins in biological and clinical samples. This array format allows quantification of one protein or phosphoprotein in multiple samples under the same experimental conditions at the same time. Moreover, it is suited for signal transduction profiling of small numbers of cultured cells or cells isolated from human biopsies, including formalin fixed and paraffin embedded (FFPE) tissues. Owing to the much easier sample preparation, as compared to mass spectrometry based technologies, and the extraordinary sensitivity for the detection of low-abundance signaling proteins over a large linear range, RPPA have the potential for characterization of deregulated interconnecting protein pathways and networks in limited amounts of sample material in clinical routine settings. Current aspects of RPPA technology, including dilution curves, spotting, controls, signal detection, antibody validation, and calculation of protein levels are addressed.

Analytical challenges translating mass spectrometry-based phosphoproteomics from discovery to clinical applications

Phosphoproteomics is the systematic study of one of the most common protein modifications in high throughput with the aim of providing detailed information of the control, response, and communication of biological systems in health and disease. Advances in analytical technologies and strategies, in particular the contributions of high-resolution mass spectrometers, efficient enrichments of phosphopeptides, and fast data acquisition and annotation, have catalyzed dramatic expansion of signaling landscapes in multiple systems during the past decade. While phosphoproteomics is an essential inquiry to map high-resolution signaling networks and to find relevant events among the apparently ubiquitous and widespread modifications of proteome, it presents tremendous challenges in separation sciences to translate it from discovery to clinical practice. In this mini-review, we summarize the analytical tools currently utilized for phosphoproteomic analysis (with focus on MS), progresses made on deciphering clinically relevant kinase-substrate networks, MS uses for biomarker discovery and validation, and the potential of phosphoproteomics for disease diagnostics and personalized medicine.

Antibody-based proteomics and biomarker research - current status and limitations

Antibody-based proteomics play a very important role in biomarker discovery and validation, facilitating the high-throughput evaluation of candidate markers. Most proteomics-driven discovery is nowadays based on the use of MS. MS has many advantages, including its suitability for hypothesis-free biomarker discovery, since information on protein content of a sample is not required prior to analysis. However, MS presents one main caveat which is the limited sensitivity in complex samples, especially for body fluids, where protein expression covers a huge dynamic range. Antibody-based technologies remain the main solution to address this challenge since they reach higher sensitivity. In this article, we review the benefits and limitations of antibody-based proteomics in preclinical and clinical biomarker research for discovery and validation in body fluids and tissue. The combination of antibodies and MS, utilizing the best of both worlds, opens new avenues in biomarker research.

Proteogenomic convergence for understanding cancer pathways and networks

During the past several decades, the understanding of cancer at the molecular level has been primarily focused on mechanisms on how signaling molecules transform homeostatically balanced cells into malignant ones within an individual pathway. However, it is becoming more apparent that pathways are dynamic and crosstalk at different control points of the signaling cascades, making the traditional linear signaling models inadequate to interpret complex biological systems. Recent technological advances in high throughput, deep sequencing for the human genomes and proteomic technologies to comprehensively characterize the human proteomes in conjunction with multiplexed targeted proteomic assays to measure panels of proteins involved in biologically relevant pathways have made significant progress in understanding cancer at the molecular level. It is undeniable that proteomic profiling of differentially expressed proteins under many perturbation conditions, or between normal and "diseased" states is important to capture a first glance at the overall proteomic landscape, which has been a main focus of proteomics research during the past 15-20 years. However, the research community is gradually shifting its heavy focus from that initial discovery step to protein target verification using multiplexed quantitative proteomic assays, capable of measuring changes in proteins and their interacting partners, isoforms, and post-translational modifications (PTMs) in response to stimuli in the context of signaling pathways and protein networks. With a critical link to genotypes (i.e., high throughput genomics and transcriptomics data), new and complementary information can be gleaned from multi-dimensional omics data to (1) assess the effect of genomic and transcriptomic aberrations on such complex molecular machinery in the context of cell signaling architectures associated with pathological diseases such as cancer (i.e., from genotype to proteotype to phenotype); and (2) target pathway- and network-driven changes and map the fluctuations of these functional units (proteins) responsible for cellular activities in response to perturbation in a spatiotemporal fashion to better understand cancer biology as a whole system.

Predictive biomarker candidates for the response of gastric cancer to targeted and cytotoxic agents

Gastric cancer is the second most common cause of cancer death worldwide. Recent development of targeted agents provides clinicians with additional systemic treatment options to conventional cytotoxic agents. Predictive markers are undoubtedly important for guiding the appropriate use of targeted and cytotoxic agents. Currently, however, HER2 is the only predictive biomarker validated for gastric cancer. In this review, candidate predictive markers for response to other targeted agents and cytotoxic chemotherapeutic agents are discussed.

Delayed times to tissue fixation result in unpredictable global phosphoproteome changes

Protein phosphorylation controls the activity of signal transduction pathways regulated by kinases and phosphatases. Little is known, however, about the impact of preanalytical factors, for example, delayed times to tissue fixation, on global phosphoprotein levels in tissues. The aim of this study was to characterize the potential effects of delayed tissue preservation (cold ischemia) on the levels of phosphoproteins using targeted and nontargeted proteomic approaches. Rat and murine liver samples were exposed to different cold ischemic conditions ranging from 10 to 360 min prior to cryopreservation. The phosphoproteome was analyzed using reverse phase protein array (RPPA) technology and phosphoprotein-enriched quantitative tandem mass spectrometry (LC-MS/MS). RPPA analysis of rat liver tissues with long (up to 360 min) cold ischemia times did not reveal statistically significant alterations of specific phosphoproteins even though nonphosphorylated cytokeratin 18 (CK18) showed increased levels after 360 min of delay to freezing. Keeping the samples on ice prior to cryopreservation prevented this effect. LC-MS/MS-based quantification of 1684 phosphorylation sites in rat liver tissues showed broadening of their distribution compared to time point zero, but without reaching statistical significance for individual phosphosites. Similarly, RPPA analysis of mouse liver tissues with short (<60 min) cold ischemia times did not reveal directed or predictable changes of protein and phosphoprotein levels. Using LC-MS/MS and quantification of 791 phosphorylation sites, we found that the distribution of ratios compared to time point zero broadens with prolonged ischemia times, but these were rather undirected and diffuse changes, as we could not detect significant alterations of individual phosphosites. On the basis of our results from RPPA and LC-MS/MS analysis of rat and mouse liver tissues, we conclude that prolonged cold ischemia results in unspecific phosphoproteome changes that can be neither predicted nor assigned to individual proteins. On the other hand, we identified a number of phosphosites which were extraordinarily stable even after 360 min of cold ischemia and, therefore, may be used as general reference markers for future companion diagnostics for kinase inhibitors.

Leveraging systems biology approaches in clinical pharmacology

Computational modeling has been adopted in all aspects of drug research and development, from the early phases of target identification and drug discovery to the late-stage clinical trials. The different questions addressed during each stage of drug R&D has led to the emergence of different modeling methodologies. In the research phase, systems biology couples experimental data with elaborate computational modeling techniques to capture lifecycle and effector cellular functions (e.g. metabolism, signaling, transcription regulation, protein synthesis and interaction) and integrates them in quantitative models. These models are subsequently used in various ways, i.e. to identify new targets, generate testable hypotheses, gain insights on the drug's mode of action (MOA), translate preclinical findings, and assess the potential of clinical drug efficacy and toxicity. In the development phase, pharmacokinetic/pharmacodynamic (PK/PD) modeling is the established way to determine safe and efficacious doses for testing at increasingly larger, and more pertinent to the target indication, cohorts of subjects. First, the relationship between drug input and its concentration in plasma is established. Second, the relationship between this concentration and desired or undesired PD responses is ascertained. Recognizing that the interface of systems biology with PK/PD will facilitate drug development, systems pharmacology came into existence, combining methods from PK/PD modeling and systems engineering explicitly to account for the implicated mechanisms of the target system in the study of drug–target interactions. Herein, a number of popular system biology methodologies are discussed, which could be leveraged within a systems pharmacology framework to address major issues in drug development.

Genomic Medicine Frontier in Human Solid Tumors: Prospects and Challenges

Recent discoveries of genomic alterations that underlie and promote the malignant phenotype, together with an expanded repertoire of targeted agents, have provided many opportunities to conduct hypothesis-driven clinical trials. The ability to profile each unique cancer for actionable aberrations by using high-throughput technologies in a cost-effective way provides unprecedented opportunities for using matched therapies in a selected patient population. The major challenges are to integrate and make biologic sense of the substantial genomic data derived from multiple platforms. We define two different approaches for the analysis, interpretation, and clinical applicability of genomic data: (1) the genomically stratified model originates from the “one test-one drug” paradigm and is currently being expanded with an upfront multicategorical approach following recent advances in multiplexed genotyping platforms; and (2) the comprehensive assessment model is based on whole-genome, -exome, and -transcriptome data and allows identification of novel drivers and subsequent therapies in the experimental setting. Tumor heterogeneity and evolution of the diverse populations of cancer cells during cancer progression, influenced by the effects of systemic treatments, will need to be addressed in the new scenario of early drug development. Logistical issues related to prescreening strategies and trial allocation, in addition to concerns in the economic and ethical domains, must be taken into consideration. Here we present a historical view of how increased understanding of cancer genomics has been translated to the clinic and discuss the prospects and challenges for further implementation of a personalized treatment strategy for human solid tumors.

Multiple protein analysis of formalin-fixed and paraffin-embedded tissue samples with reverse phase protein arrays

Reverse-phase protein arrays (RPPAs) have become an important tool for the sensitive and high-throughput detection of proteins from minute amounts of lysates from cell lines and cryopreserved tissue. The current standard method for tissue preservation in almost all hospitals worldwide is formalin fixation and paraffin embedding, and it would be highly desirable if RPPA could also be applied to formalin-fixed and paraffin embedded (FFPE) tissue. We investigated whether the analysis of FFPE tissue lysates with RPPA would result in biologically meaningful data in two independent studies. In the first study on breast cancer samples, we assessed whether a human epidermal growth factor receptor (HER) 2 score based on immunohistochemistry (IHC) could be reproduced with RPPA. The results showed very good concordance between the IHC and RPPA classifications of HER2 expression. In the second study, we profiled FFPE tumor specimens from patients with adenocarcinoma and squamous cell carcinoma in order to find new markers for differentiating these two subtypes of non-small cell lung cancer. p21-activated kinase 2 could be identified as a new differentiation marker for squamous cell carcinoma. Overall, the results demonstrate the technical feasibility and the merits of RPPA for protein expression profiling in FFPE tissue lysates.

Is phosphoproteomics ready for clinical research?

BACKGROUND

For many diseases such as cancer where phosphorylation-dependent signaling is the foundation of disease onset and progression, single-gene testing and genomic profiling alone are not sufficient in providing most critical information. The reason for this is that in these activated pathways the signaling changes and drug resistance are often not directly correlated with changes in protein expression levels. In order to obtain the essential information needed to evaluate pathway activation or the effects of certain drugs and therapies on the molecular level, the analysis of changes in protein phosphorylation is critical.

METHODS

Existing approaches do not differentiate clinical disease subtypes on the protein and signaling pathway level, and therefore hamper the predictive management of the disease and the selection of therapeutic targets.

CONCLUSIONS

The mini-review examines the impact of emerging systems biology tools and the possibility of applying phosphoproteomics to clinical research.

Computational approaches for analyzing information flow in biological networks

The advancements in "omics" (proteomics, genomics, lipidomics, and metabolomics) technologies have yielded large inventories of genes, transcripts, proteins, and metabolites. The challenge is to find out how these entities work together to regulate the processes by which cells respond to external and internal signals. Mathematical and computational modeling of signaling networks has a key role in this task, and network analysis provides insights into biological systems and has applications for medicine. Here, we review experimental and theoretical progress and future challenges toward this goal. We focus on how networks are reconstructed from data, how these networks are structured to control the flow of biological information, and how the design features of the networks specify biological decisions.

Antibody validation by combining immunohistochemistry and protein extraction from formalin-fixed paraffin-embedded tissues

AIMS

  Personalized cancer treatment strategies depend on comprehensive and detailed characterization of individual human malignancies. Clinical pathology, particularly immunohistochemical evaluation of biomarkers in tissues, is considered to be the approved standard for diagnostic and therapeutic decisions, having a direct influence on patient management and therapy. Although antibody-based approaches are established and integrated successfully into both clinical and research applications, for personalized treatment regimens new demands have been placed on the quality, reproducibility and accuracy of antibody-based assays. To ensure the accuracy of specific antigen detection in immunohistochemistry, we introduce a novel approach for antibody validation.

METHODS AND RESULTS

  In a tandem approach we used the same archival tissue of interest for antibody validation by combining extraction of immunoreactive proteins from formalin-fixed, paraffin-embedded tissue with Western blot analysis and immunohistochemistry. This procedure allows for specification of the antigen detected and for localization of the protein in the tissue. Of the 32 antibodies tested used in research and routine diagnostics, 19 showed reliable specificity in both assays.

CONCLUSION

  This study emphasizes the advantage of combining suitable methods to ensure reproducibility and specific antigen detection. Based on our results, we propose a novel step-by-step strategy to validate antibody specificity and reduce variability of immunohistochemical results.

Adverse effects of simulated hyper- and hypo-phosphatemia on endothelial cell function and viability

Background

Dysregulaiton of phosphate homeostasis as occurs in chronic kidney disease is associated with cardiovascular complications. It has been suggested that both hyperphosphatemia and hypophosphatemia can cause cardiovascular disease. The molecular mechanisms by which high or low serum phosphate levels adversely affect cardiovascular function are poorly understood. The purpose of this study was to explore the mechanisms of endothelial dysfunction in the presence of non-physiologic phosphate levels.

Methodology/Principal Findings

We studied the effects of simulated hyper- and hypophosphatemia in human umbilical vein endothelial cells in vitro. We found both simulated hyperphosphatemia and hypophosphatemia decrease eNOS expression and NO production. This was associated with reduced intracellular calcium, increased protein kinase C β2 (PKCβ2), reduced cell viability, and increased apoptosis. While simulated hyperphosphatemia was associated with decreased Akt/p-Akt, Bcl-xl/Bax ratios, NFkB-p65 and p-Erk abundance, simulated hypophosphatemia was associated with increased Akt/p-Akt and Bcl-xl/Bax ratios and p-Mek, p38, and p-p38 abundance.

Conclusions/Significance

This is the first demonstration of endothelial dysfunction with hypophosphatemia. Our data suggests that both hyperphosphatemia and hypophosphatemia decrease eNOS activity via reduced intracellular calcium and increased PKCβ2. Hyperphosphatemia also appears to reduce eNOS transcription via reduced signaling through PI3K/Akt/NF-kB and MAPK/NF-kB pathways. On the other hand, hypophosphatemia appears to activate these pathways. Our data provides the basis for further studies to elucidate the relationship between altered phosphate homeostasis and cardiovascular disease. As a corollary, our data suggests that the level of phosphate in the culture media, if not in the physiologic range, may inadvertently affect experimental results.

Targeted therapies in cancer - challenges and chances offered by newly developed techniques for protein analysis in clinical tissues

In recent years, new anticancer therapies have accompanied the classical approaches of surgery and radio- and chemotherapy. These new forms of treatment aim to inhibit specific molecular targets namely altered or deregulated proteins, which offer the possibility of individualized therapies.The specificity and efficiency of these new approaches, however, bring about a number of challenges. First of all, it is essential to specifically identify and quantify protein targets in tumor tissues for the reasonable use of such targeted therapies. Additionally, it has become even more obvious in recent years that the presence of a target protein is not always sufficient to predict the outcome of targeted therapies. The deregulation of downstream signaling molecules might also play an important role in the success of such therapeutic approaches. For these reasons, the analysis of tumor-specific protein expression profiles prior to therapy has been suggested as the most effective way to predict possible therapeutic results. To further elucidate signaling networks underlying cancer development and to identify new targets, it is necessary to implement tools that allow the rapid, precise, inexpensive and simultaneous analysis of many network components while requiring only a small amount of clinical material.Reverse phase protein microarray (RPPA) is a promising technology that meets these requirements while enabling the quantitative measurement of proteins. Together with recently developed protocols for the extraction of proteins from formalin-fixed, paraffin-embedded (FFPE) tissues, RPPA may provide the means to quantify therapeutic targets and diagnostic markers in the near future and reliably screen for new protein targets.With the possibility to quantitatively analyze DNA, RNA and protein from a single FFPE tissue sample, the methods are available for integrated patient profiling at all levels of gene expression, thus allowing optimal patient stratification for individualized therapies.