Developing mechanistic insights into cardiovascular cell therapy: Cardiovascular Cell Therapy Research Network Biorepository Core Laboratory rationale

Abstract

Moderate improvements in cardiac performance have been reported in some clinical settings after delivery of bone marrow mononuclear cells to patients with cardiovascular disease. However, mechanistic insights into how these cells impact outcomes are lacking. To address this, the National Heart, Lung and Blood Institute (NHLBI) Cardiovascular Cell Therapy Research Network (CCTRN) established a Biorepository Core for extensive phenotyping and cell function studies and storing bone marrow and peripheral blood for 10 years. Analyzing cell populations and cell function in the context of clinical parameters and clinical outcomes after cell or placebo treatment empower the development of novel diagnostic and prognostics. Developing such biomarkers that define the safety and efficacy of cell therapy is a major Biorepository aim.

Conflict of interest statement

Conflict of Interest Disclosure: The authors declare no conflicts of interest.

Copyright © 2011 Mosby, Inc. All rights reserved.

Figures

Figure 1

Overview of clinical cell therapy studies in IHD and outcome using different cell types at different clinical stages (BM-MNC, bone marrow mononuclear cells; MSC, mesenchymal cells; EPC, endothelial progenitor cells; CPC, cardiac progenitor cells; ADC, adipose-derived cells; SKMB, skeletal myoblasts)

Figure 2

Blood collection across time points in CCTRN TIME, Late-TIME, and FOCUS protocols.

Figure 3. Cell Function Analyses of Bone Marrow and Peripheral Blood Cells From Subjects Enrolled in CCTRN Clinical Trials

(A) Micrograph of bone marrow cells upon receipt to core laboratory. Trypan blue exclusion staining is used to evaluate viable cell number. (B) Micrograph of a CFU-EC colony. (C) Micrograph of an ECFC colony. (D) Micrograph of a CFU-F colony.

Figure 4

Peripheral blood shipped under different conditions. A) comparison of overall cell viability as determined by Guava count. B) comparison of total nucleated cell (TNC) number per mL of blood. C) Comparison of cell numbers of subpopulations in peripheral blood shipped under different conditions. The MNC subpopulations are determined by surface markers and expressed as a % of the unshipped control. All data are expressed as mean ± standard error. Statistical differences determined by ANOVA, * p<0.05, *** p<0.0001

Figure 5

Peripheral blood maintained at 4°C and processed at different times post-draw. A) Comparison of overall viability as determined by Guava count, B) comparison of total nucleated cell number per mL of blood.. C) Comparison of cell numbers of subpopulations in peripheral blood at different time points following collection. The subpopulations were determined by surface markers and expressed relative to percentages at the time of collection. All data are expressed as mean ± standard error. Statistical differences determined by ANOVA, * p<0.05, ** p<0.01, *** p<0.0001

Figure 6

Comparison of viabilities for each center for the first 10 peripheral blood samples shipped at the beginning of the studies, and 10 peripheral blood samples for each center shipped at least one year later.

Figure 7. Effect of Shipping Time on Cell Viability of Bone Marrow and Peripheral Blood Received in the Cell Function Core Laboratory

(A) Scatter plot and regression line for percent non-viable BM-MNCs versus Total Shipping Time (hours). There was a slight increase in non-viable cells with increasing shipping time, however the correlation was statistically insignificant (p=0.7283). (B) Scatter plot and regression line for percent non-viable BM-MNCs versus Total Shipping Time (hours). There was a slight decrease in non-viable cells with increasing shipping time, however the correlation was statistically insignificant (p=0.7147).