Kurt Krapfenbauer

Pitfalls and limitations in translation from biomarker discovery to clinical utility in predictive and personalised medicine

Since the emergence of the so-called omics technology, thousands of putative biomarkers have been identified and published, which have dramatically increased the opportunities for developing more effective therapeutics. These opportunities can have profound benefits for patients and for the economics of healthcare. However, the transfer of biomarkers from discovery to clinical practice is still a process filled with lots of pitfalls and limitations, mostly limited by structural and scientific factors. To become a clinically approved test, a potential biomarker should be confirmed and validated using hundreds of specimens and should be reproducible, specific and sensitive. Besides the lack of quality in biomarker validation, a number of other key issues can be identified and should be addressed. Therefore, the aim of this article is to discuss a series of interpretative and practical issues that need to be understood and resolved before potential biomarkers become a clinically approved test or are already on the diagnostic market. Some of these issues are shortly discussed here.

Medicine in the early twenty-first century: paradigm and anticipation - EPMA position paper 2016.

Background Challenges of “standardisation” and “individualisation” have always been characteristic for medical services. In terms of individualisation, the best possible individual care is the ethical imperative of medicine, and it is a good right of any patient to receive it. However, in terms of standardisation, all the available treatments are based on guideline recommendations derived from large multicentre trials with many thousands of patients involved. In the most optimal way, the standardisation and individualisation should go hand-in-hand, in order to identify the right patient treating him/her with the right medication and the right dose at the right time point! Further, in paradigm and anticipation, there is a big discrepancy between “disease care” and “health care” which dramatically impacts ethical and economical aspects of medical services. Several approaches have been suggested in ancient and modern medicine to conduct medical services in a possibly optimal way. What is the difference amongst all of them and how big is the potential beyond corresponding approach to satisfy the needs of the individual, the patient, professional groups involved and society at large? On behalf of the “European Association for Predictive, Preventive and Personalised Medicine,” the dedicated EPMA working group provides a deep analysis in the issue followed by the expert recommendations considering the multifaceted aspects of both “disease care” and “health care” practices including ethics and economy, life quality of individuals and patients, interests of professional groups involved, benefits of subpopulations, health care system(s) and society as a whole.

Potential involvement of MYC- and p53-related pathways in tumorigenesis in human oral squamous cell carcinoma revealed by proteomic analysis.

Oral squamous cellular carcinoma is a malignant tumor with poor prognosis. Discovery of early markers to discriminate between malignant and normal cells is of high importance in clinical diagnosis. Subcellular fractions from 10 oral squamous cell carcinoma and corresponding control samples, enriched in mitochondrial and cytosolic proteins, as well as blood from the tumor were analyzed by proteomics, two-dimensional gel electrophoresis, followed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Three-hundred and fifty different gene products were identified. Twenty proteins showed deranged levels in oral squamous cell carcinoma in comparison with the control samples and are potentially involved in tumor growth and metastasis. Of these, 16 proteins were upregulated. By applying pathway analysis, we found 8 of the upregulated gene products to be linked to three main locus genes, p53, MYC, and MYCN, and could be candidate biomarkers for OSCC. The findings of this pilot study show that OSCC gene ontology combined with proteomic analysis is a powerful tool in systems biology for the elucidation of the complexity of expression profiles in cellular processes. Application of such pathway analysis has the potential to generate new insights into complex molecular mechanisms underlying disease related processes and could therefore significantly contribute to the efficient performance of the entire discovery process.

The role of laboratory medicine in healthcare: quality requirements of immunoassays, standardisation and data management in prospective medicine

In the last 10 years, the area of ELISA and protein-chip technology has developed and enthusiastically applied to an enormous variety of biological questions. However, the degree of stringency required in data analysis appears to have been underestimated. As a result, there are numerous published findings that are of questionable quality, requiring further confirmation and/or validation. In the course of feasibility and validation studies a number of key issues in research, development and clinical trial studies must be outlined, including those associated with laboratory design, analytical validation strategies, analytical completeness and data managements. The scope of the following review should provide assistance for defining key parameters in assay evaluation and validation in research and clinical trial projects in prospective medicine.

Economic concerns about global healthcare in lung, head and neck cancer: meeting the economic challenge of predictive, preventive and personalized medicine

The introduction of biological science into the practice of medicine was a big transforming event for the profession, leading to different new medical models such as predictive, preventive and personalized medicine. Each of them is a rapidly emerging field that helps us to determine the risk for individuals to develop specific diseases, detect the disease’s earliest onset and prevent or intervene early enough to provide maximum benefit for each patient. However, to realize this new potential, new healthcare models must be created, improved and validated. New healthcare models that are more proactive than reactive because prevention is less expensive than reactive medicine. Current knowledge about predictive, preventive and personalized medicine is already sufficient to implement this approach, but there are no effective practice models, delivery systems and appropriate reimbursement mechanisms. In the course of this review, we describe the economic components and benefits of a predictive, preventive and personalized health plan for lung as well as head and neck cancer and show how prospective care could relate to a community or group of covered individuals.

Identification of tumour-related proteins as potential screening markers by proteome analysis—protein profiles of human saliva as a predictive and prognostic tool

The analysis of biomarkers in saliva as a clinical application offers an attractive, simple and rapid diagnostic tool for the short- and long-term monitoring of pathological disorders and drug therapy. The collection of saliva, either in the pure or in its fractionated form, is a relatively easy and non-invasive procedure that is not harmful to the patients and has no complications at all. However, the fluid collection must be clearly defined due to variations in saliva composition, flow rate and day-to-day variability. In order to minimise possible variations, saliva from five patients without squamous cell carcinoma (SCC) pathology and five with suspicion of oral squamous carcinoma (OSCC) were collected and matched at different days and analysed by two-dimensional polyacrylamide gel electrophoresis (2DE-PAGE). Approximately 800 spots were identified, corresponding to 151 different gene products. The list of identified proteins includes a large number of structural proteins like keratins, keratin subunits, enzymes and enzyme inhibitors, cytokines, immunoglobulins as well as amylase and other salivary specific glycoproteins. The majority of proteins that are localised in oral epithelia cells were found as unsolved debris in saliva. One of the identified proteins was significantly overexpressed in OSCC and was selected for further validation by Western blot analysis.

Advanced proteomics procedure as a detection tool for predictive screening in type 2 pre-Diabetes.

It has been suggested that a more precise selection of predictive biomarkers may prove useful in the early diagnosis of type 2 diabetes (T2D), even when glucose tolerance is normal. This is vital since many T2D cases may be preventable by avoiding those factors that trigger the disease process (primary prevention) or by use of therapy that modulates the disease process before the onset of clinical symptoms (secondary prevention) occurs. The selection of predictive markers must be carefully assessed and depends mainly on three important parameters: sensitivity, specificity and positive predictive value. Unfortunately, biomarkers with ideal specificity and sensitivity are difficult to find. One potential solution is to use the combinatorial power of different biomarkers, each of which alone may not offer satisfactory specificity and sensitivity. Recent technological advances in proteomics and bioinformatics offer a great opportunity for the discovery of different potential predictive markers. In this review, we described a cellular T2D model as an example with the intent of providing specific enrichment and new identification strategies, which might have the potential to improve predictive biomarker identification and to bring accuracy in disease diagnosis and classification, as well as therapeutic monitoring in the early phase of T2D.

Improved prognostic diagnosis of systemic lupus erythematosus in an early stage of disease by a combination of different predictive biomarkers identified by proteome analysis

BackgroundSince the original characterizations of the pathological features defining glomerulonephritis in systemic lupus erythematosus (SLE) were reported, numerous studies have linked the development of pathology to the abnormal expression of protein in urine. The determination of proteinuria is important and necessary; however, this alone is not predictive enough to confirm a suspected diagnosis, especially in an early state of disease when symptoms are not yet observed. Furthermore, several studies have already highlighted the pitfalls of proteinuria both as a clinical prognostic marker and as a factor predicting the progressive loss of renal function. Therefore, the identification of more accurate and predictive biomarkers is urgently needed. To address this, comparative urinary and kidney profiling was performed in the MRL-lpr/lpr mouse as a model of lupus tubulointerstitial nephritis and lupus glomerulonephritis corresponding to SLE in humans.ResultsTamm-Horsfall glycoprotein (THG; uromodulin) and beta2-microglubulin (β2M) were identified as immune process-related molecules in the urine and kidney of the MRL-lpr/lpr mouse model. Furthermore, we show that the combinatory expression profile of THG and β2M as biomarkers, normalized by the proteinuria level, is more predictive than proteinuria determination alone. Data were confirmed by comparative urinary profiling of SLE in mice by Western blot and quantitative polymerase chain reaction (qPCR) analysis.ConclusionBased on our results, we are able to diagnose SLE in the MRL-lpr/lpr mouse in a very early state of disease, when the proteinuria level alone is not able to confirm a suspected diagnosis. The pre-validation of our urinary biomarkers is associated with clinical outcomes of glomerulonephritis in humans and merits additional investigation. Further conformations of our predictive biomarkers in the urine of SLE patients in the course of a clinical study are still ongoing.

Strategic aspects of higher education reform to cultivate specialists in diagnostic and biopharma industry as applicable to Predictive, Preventive and Personalized Medicine as the Medicine of the Future.

Predictive, Preventive and Personalized Medicine as the Medicine of the Future represents an innovative model for advanced healthcare and robust platform for relevant industrial branches for diagnostics and pharmaceutics. However, rapid market penetration of new medicines and technologies demands the implementation of reforms not only in the spheres of biopharmaceutical industries and healthcare, but also in education. Therefore, the problem of the fundamental, modern preparation of specialists in bioengineering and affiliated fields is becoming particularly urgent, and it requires significant revision of training programs of higher education practice into current medical universities. Modernization and integration of widely accepted medical and teaching standards require consolidation of both the natural sciences and medical sciences that may become the conceptual basis for a university medical education. The main goal of this training is not simply to achieve advanced training and expansion of technological skills, but to provide development of novel multifaceted approaches to build academic schools for future generations.

Identification of Biomarkers for Beta Cell Failure as Detection Tools for Predictive Screening in Type 2 Pre-diabetes

It has been suggested that a more precise selection of predictive biomarkers may prove useful in the early diagnosis of type 2 diabetes (T2D), even when glucose tolerance is normal. This is vital since many T2D cases may be preventable by avoiding those factors that trigger the disease process (primary prevention) or by use of therapy that modulates the disease process before the onset of clinical symptoms (secondary prevention) occurs. The selection of predictive markers must be carefully assessed and depends mainly on three important parameters: sensitivity, specificity and positive predictive value. Unfortunately, biomarkers with ideal specificity and sensitivity are difficult to find. One potential solution is to use the combinatorial power of a large number of biomarkers, each of which alone may not offer satisfactory specificity and sensitivity. Recent technological advances in proteomics and bioinformatics offer a great opportunity for discovery of potential predictive markers. In this chapter, we described a cellular T2D model as an example with the intent of providing specific enrichment and new identification strategies, which might have the potential to improve predictive biomarker identification and to bring accuracy in disease diagnosis and classification, as well as therapeutic monitoring in the early phase of T2D.