Biomarkers in solid organ transplantation: establishing personalized transplantation medicine.

Technological advances in molecular and in silico research have enabled significant progress towards personalized transplantation medicine. It is now possible to conduct comprehensive biomarker development studies of transplant organ pathologies, correlating genomic, transcriptomic and proteomic information from donor and recipient with clinical and histological phenotypes. Translation of these advances to the clinical setting will allow assessment of an individual patient's risk of allograft damage or accommodation. Transplantation biomarkers are needed for active monitoring of immunosuppression, to reduce patient morbidity, and to improve long-term allograft function and life expectancy. Here, we highlight recent pre- and post-transplantation biomarkers of acute and chronic allograft damage or adaptation, focusing on peripheral blood-based methodologies for non-invasive application. We then critically discuss current findings with respect to their future application in routine clinical transplantation medicine. Complement-system-associated SNPs present potential biomarkers that may be used to indicate the baseline risk for allograft damage prior to transplantation. The detection of antibodies against novel, non-HLA, MICA antigens, and the expression of cytokine genes and proteins and cytotoxicity-related genes have been correlated with allograft damage and are potential post-transplantation biomarkers indicating allograft damage at the molecular level, although these do not have clinical relevance yet. Several multi-gene expression-based biomarker panels have been identified that accurately predicted graft accommodation in liver transplant recipients and may be developed into a predictive biomarker assay

Identification of new candidate biomarkers for prostate cancer by affinity proteomics

Prostate cancer (PCA) is a complex malignancy that needs to be more thoroughly studied and understood at a molecular level to fill the current knowledge gap, and optimize diagnosis and to treatment. Prostate specific antigen (PSA) showed to be not specific for PCA, therefore a demand for novel specific biomarkers exists. The aim of our work was to identify new specific candidate biomarkers for PCA in tissue and plasma samples by means of affinity proteomics approaches such as reverse phase protein array and antigen arrays. Tissue samples are an invaluable source of biomarkers for cancer, but very limited in amount and requiring invasive procedures for collection. Still, they allow to directly profiling the molecular status of tumor itself. Beside tissue, a screening procedure on biological fluid such as plasma would be highly desirable, thanks to the less invasiveness and low-costs of samples collection. Among the biomarkers detectable in plasma are the autoantibodies. The first part of this thesis summarizes the current status of PCA epidemiology, treatment, and biomarkers research. Beside this, an overview of the affinity proteomics platforms available for biomarkers research, and the critical variables to consider in the biomarkers validation process are presented. The second part of the thesis reports the main results of two original studies where the author of the thesis is the main contributor. Paper I is based on the profiling of PCA tissue samples using RPPA. Our results indicate the feasibility of combining laser capture microdissection (LCM) and RPPA for evaluating the molecular architecture and cross-talking of epithelial and stromal compartments. Paper II is based on profiling the autoimmune response to PCA patients, comparing early and late stage of the disease. The authors identified and characterized the IgG reactivity toward a novel epitope for the candidate biomarker prostein. The data presented in this thesis provide two robust frameworks based on affinity proteomics platforms applied for protein profiling in tissue, and autoantibodies profiling in plasma in the context of PCA biomarkers discovery.Co-supervisors: Peter Nilsson (Biotechnology Department, KTH-Royal Institute of Technology, Stockholm, Sweden), Mariaelena Pierobon (Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA, USA)openDottorato di ricerca in Medicina cellulare e molecolareopenPin, Elis

Oncoproteomics: Opportunities, Challenges & Advanced Technologies

Oncoproteomics is nothing but the analysis of proteins and their interactions in a cancer cell through proteomic technologies. Oncoproteomics is playing a progressively significant part in diagnosis and the management of cancer. It also helps in the advancement of personalized therapy of cancer. Oncoproteomics holds great potential not only for opening the complicated molecular episodes of tumorigenesis but also for those that regulate clinically essential tumor habits, like metastasis, invasion, and resistance to treatment. Protein molecules show a significant impact on the evolution of cancer as it mainly develops due to abnormal signaling pathways. Detection and comprehension of these alterations is the major concept of oncoproteomics. Novel proteomic technologies related to cancer are defined in short, which are assisting not only in the comprehension of the mechanism of drug-resistant in cancer but also bestow some guides in management. For the diagnostic and prognostic categorization of the disease condition, and in measuring the drug efficiency and toxicity acclimatization of proteomic technologies in clinical laboratories is the fundamental objective of oncoproteomics. A considerable influence on the management of cancer patients and on a spectacular revolution in cancer research might notice by data obtained through such novel technologies. For the cancer therapy, the identification of novel targets, as well as an understanding of tumor development, might permit by the research of tumor-specific proteomic profiles. A wide perspective on drug-resistant and anticancer drug discovery, proteomic biomarkers and its function in the diagnosis of cancer, current innovation in proteomic technologies have tried to give in this review

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

Identification of blood biomarkers of rheumatoid arthritis by transcript profiling of peripheral blood mononuclear cells from the rat collagen-induced arthritis model

Rheumatoid arthritis (RA) is a chronic debilitating autoimmune disease that results in joint destruction and subsequent loss of function. To better understand its pathogenesis and to facilitate the search for novel RA therapeutics, we profiled the rat model of collagen-induced arthritis (CIA) to discover and characterize blood biomarkers for RA. Peripheral blood mononuclear cells (PBMCs) were purified using a Ficoll gradient at various time points after type II collagen immunization for RNA preparation. Total RNA was processed for a microarray analysis using Affymetrix GeneChip technology. Statistical comparison analyses identified differentially expressed genes that distinguished CIA from control rats. Clustering analyses indicated that gene expression patterns correlated with laboratory indices of disease progression. A set of 28 probe sets showed significant differences in expression between blood from arthritic rats and that from controls at the earliest time after induction, and the difference persisted for the entire time course. Gene Ontology comparison of the present study with previous published murine microarray studies showed conserved Biological Processes during disease induction between the local joint and PBMC responses. Genes known to be involved in autoimmune response and arthritis, such as those encoding Galectin-3, Versican, and Socs3, were identified and validated by quantitative TaqMan RT-PCR analysis using independent blood samples. Finally, immunoblot analysis confirmed that Galectin-3 was secreted over time in plasma as well as in supernatant of cultured tissue synoviocytes of the arthritic rats, which is consistent with disease progression. Our data indicate that gene expression in PBMCs from the CIA model can be utilized to identify candidate blood biomarkers for RA

Zebrafish Whole-Adult-Organism Chemogenomics for Large-Scale Predictive and Discovery Chemical Biology

The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly), is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated) aromatic hydrocarbons [P(H)AHs] and estrogenic compounds (ECs), we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR) and estrogen receptor (ER) agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology

Quantitative and systems pathology for therapeutic response prediction

The measurement of tissue biomarkers for therapeutic response prediction in cancer patients has become standard pathological practice, but only for a very limited number of targets. This is in spite of massive intellectual and financial investment in molecular pathology for translational cancer research. A re-evaluation of current approaches, and the testing of new ones, is required in order to meet the challenges of predicting responses to existing and novel therapeutics, and individualising therapy.Herein I critique the current state of tissue biomarker analysis and quantification in cancer pathology and the reasons why so few novel biomarkers have entered the clinic. In particular, we examine the central role of signalling pathway biology in sensitivity and resistance to targeted therapy. I discuss how accurate quantification, and the ability to simulate biological responses over time and space, may lead to more accurate prediction of therapeutic response. I propose that different mathematical techniques used in the nascent field of systems biology (ordinary differential equation-based, S-systems, and Bayesian approaches) may provide promising new avenues to improve prediction in clinical and pathological practice. I also discuss the challenges and opportunities for quantification in pathological research and practice.I have examined the role of cellular signalling pathways in therapeutic sensitivity and resistance in three different ways. Firstly, I have taken a hypothesis-driven and reductionist approach and shown that decreased Sprouty 2, a feedback inhibitor of MAPK and PI3K signalling, is associated with trastuzumab-resistance in vitro and in a cohort of breast cancer patients treated with trastuzumab. Secondly, I have characterised the activation state of ten growth and survival pathways across different histological subtypes of ovarian cancer using quantitative fluorescence microscopy. I have shown that unsupervised clustering of phosphoprotein expression profiles results in new subgroups with distinct biological properties (in terms of proliferation and apoptosis), and which predict therapeutic response to chemotherapy. Thirdly, I have developed a new mathematical model of PI3K signalling, parameterised using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays, and shown that quantitative PTEN protein expression is the key determinant of resistance to anti-HER2 therapy in silico. Furthermore, the quantitative measurement of PTEN is more predictive of response than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalised therapy in cancer, and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision-making in patients treated with anti-HER2 therapies

Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women

BACKGROUND: Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. OBJECTIVES: Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. METHODS: Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM(10) in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM(2.5) and PM(10) exposures over 2-years were estimated for each participant’s residential address using spatiotemporal interpolation in combination with a dispersion model. RESULTS: Average long-term PM(10) was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m(3) in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM(10) and the expression of individual genes differed by sex. In the validation cohort, long-term PM(10) was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 (p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM(10) in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM(10) exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). CONCLUSIONS: Expression of the sex-specific candidate genes identified in the discovery population predicted PM(10) exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects. CITATION: Vrijens K, Winckelmans E, Tsamou M, Baeyens W, De Boever P, Jennen D, de Kok TM, Den Hond E, Lefebvre W, Plusquin M, Reynders H, Schoeters G, Van Larebeke N, Vanpoucke C, Kleinjans J, Nawrot TS. 2017. Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women. Environ Health Perspect 125:660–669; http://dx.doi.org/10.1289/EHP37

One-Step Preservation of Phosphoproteins and Tissue Morphology at Room Temperature for Diagnostic and Research Specimens

BACKGROUND: There is an urgent need to measure phosphorylated cell signaling proteins in cancer tissue for the individualization of molecular targeted kinase inhibitor therapy. However, phosphoproteins fluctuate rapidly following tissue procurement. Snap-freezing preserves phosphoproteins, but is unavailable in most clinics and compromises diagnostic morphology. Formalin fixation preserves tissue histomorphology, but penetrates tissue slowly, and is unsuitable for stabilizing phosphoproteins. We originated and evaluated a novel one-step biomarker and histology preservative (BHP) chemistry that stabilizes signaling protein phosphorylation and retains formalin-like tissue histomorphology with equivalent immunohistochemistry in a single paraffin block. RESULTS: Total protein yield extracted from BHP-fixed, routine paraffin-embedded mouse liver was 100% compared to snap-frozen tissue. The abundance of 14 phosphorylated proteins was found to be stable over extended fixation times in BHP fixed paraffin embedded human colon mucosa. Compared to matched snap-frozen tissue, 8 phosphoproteins were equally preserved in mouse liver, while AMPKβ1 Ser108 was slightly elevated after BHP fixation. More than 25 tissues from mouse, cat and human specimens were evaluated for preservation of histomorphology. Selected tissues were evaluated in a multi-site, independent pathology review. Tissue fixed with BHP showed equivalent preservation of cytoplasmic and membrane cytomorphology, with significantly better nuclear chromatin preservation by BHP compared to formalin. Immunohistochemical staining of 13 non-phosphorylated proteins, including estrogen receptor alpha, progesterone receptor, Ki-67 and Her2, was equal to or stronger in BHP compared to formalin. BHP demonstrated significantly improved immunohistochemical detection of phosphorylated proteins ERK Thr202/Tyr204, GSK3-α/β Ser21/Ser9, p38-MAPK Thr180/Tyr182, eIF4G Ser1108 and Acetyl-CoA Carboxylase Ser79. CONCLUSION: In a single paraffin block BHP preserved the phosphorylation state of several signaling proteins at a level comparable to snap-freezing, while maintaining the full diagnostic immunohistochemical and histomorphologic detail of formalin fixation. This new tissue fixative has the potential to greatly facilitate personalized medicine, biobanking, and phospho-proteomic research