Challenges and solutions in the development of genomic biomarker panels: a systematic phased approach

The evolution of patient-specific precision biomarkers to guide personalized heart-transplant care

Introduction

In parallel to the clinical maturation of heart transplantation over the last 50 years, rejection testing has been revolutionized within the systems biology paradigm triggered by the Human Genome Project.

Areas Covered

We have co-developed the first FDA-cleared diagnostic and prognostic leukocyte gene expression profiling biomarker test in transplantation medicine that gained international evidence-based medicine guideline acceptance to rule out moderate/severe acute cellular cardiac allograft rejection without invasive endomyocardial biopsies. This work prompted molecular re-classification of intragraft biology, culminating in the identification of a pattern of intragraft myocyte injury, in addition to acute cellular rejection and antibody-mediated rejection. This insight stimulated research into non-invasive detection of myocardial allograft injury. The addition of a donor-organ specific myocardial injury marker based on donor-derived cell-free DNA further strengthens the non-invasive monitoring concept, combining the clinical use of two complementary non-invasive blood-based measures, host immune activity-related risk of acute rejection as well as cardiac allograft injury.

Expert Opinion

This novel complementary non-invasive heart transplant monitoring strategy based on leukocyte gene expression profiling and donor-derived cell-free DNA that incorporates longitudinal variability measures provides an exciting novel algorithm of heart transplant allograft monitoring. This algorithm's clinical utility will need to be tested in an appropriately designed randomized clinical trial which is in preparation.

The AlloMap™ genomic biomarker story: 10 years after

Over the last >20 years, we have co-developed the rationale for the first diagnostic and prognostic leukocyte gene expression profiling (GEP) biomarker test in transplantation medicine that gained US-FDA-regulatory clearance and international evidence-based medicine guideline acceptance to rule out moderate/severe acute cellular cardiac allograft rejection without invasive endomyocardial biopsies (EMB). Based on this test, a non-invasive clinical algorithm was implemented since 2005. After clinical implementation, this GEP-based monitoring in direct comparison with an EMB-based strategy was non-inferior with respect to detection of clinical rejection, defined as new onset allograft dysfunction with/without histology of ACR, re-transplantation or death, and at the same time improved patient satisfaction. Subsequently, we demonstrated the test's capacity when used as serial monitoring tool to predict these clinical rejection events. In this Personal Viewpoint article, I will discuss the various decision-making branching points that were made in the AlloMap biomarker test development to inform future genomic biomarker test development projects.

Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials

Background

Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood.

Methods

Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based).

Results

Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS.

Conclusions

The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols.

ACTN3 R577X polymorphism and long-term survival in patients with chronic heart failure

Background

Previous studies have shown the occurrence of actinin-3 deficiency in the presence of the R577X polymorphism in the ACTN3 gene. Our hypothesis is that this deficiency, by interfering with the function of skeletal muscle fiber, can result in a worse prognosis in patients with chronic heart failure.

Methods

A prospective cohort study was conducted from 2002 to 2004. The eligibility criteria included diagnosis of chronic heart failure stage C from different etiologies. We excluded all patients with concomitant disease that could be related to poor prognosis. ACTN3 rs1815739 (R577X) polymorphism was detected by high resolution melting analysis. Survival curves were calculated with the Kaplan-Meier method and evaluated with the log-rank statistic. The relationship between the baseline variables and the composite end-point of all-cause death was assessed using a Cox proportional hazards survival model.

Results

A total of 463 patients were included in this study. The frequency of the ACTN3 577X variant allele was 39.0%. The LVEF mean was 45.6 ± 18.7% and the most common etiology of this study was hypertensive. After a follow-up of five years, 239 (51.6%) patients met the pre-defined endpoint. Survival curves showed higher mortality in patients carrying RX or XX genotypes compared with patients carrying RR genotype (p = 0.01).

Conclusion

R577X polymorphism in the ACTN3 gene was independently associated with worse survival in patients with chronic heart failure. Further studies are necessary to ensure its use as a marker of prognosis for this syndrome.