Key Techniques in Cell Therapy Quality Control
The development of cell therapies is being pursued in the hope of treating a broad range of conditions and intractable diseases. Quality control (QC) techniques and protocols are needed to support the development of immunotherapies and regenerative medicine. Developing proper regulatory standards for the QC of cell-based therapy products is essential to the protection of patients receiving such treatments, and the protection of the industry. For example, unlicensed and self-described “stem cell clinics” have inflicted serious adverse effects on patients; one case was reported where patients were under the impression they were participating in a clinical trial, yet paid to receive bilateral intravitreal injections that resulted in vision loss.1 These cases can also damage the reputation of legitimate stem cell research.
Just like a personalized approach is used to treat patients, there is likely to be no “one-size-fits-all” set of procedures for assessing QC in cell therapy manufacturing.
To encourage the industry to reach an agreement on what “quality” means, the Global Alliance for iPSC (induced pluripotent stem cell) Therapies (GAiT) surveyed members on how they understood critical quality attributes in the context of clinical-grade iPSC lines as starting material for allogeneic therapeutic development. These are the critical quality attributes for iPSCs:2
● Identity (authentic genotype and phenotype as originally described)
● Microbiological sterility (mycoplasma, bacteriology and viral testing)
● Endotoxin
● Genetic fidelity and stability
● Viability
● Characterization
● Potency
Opinions vary on the exact parameters, assays, and standards that should be applied to assess the above list, but experts agree on one thing: the overall QC strategy should not only rely on finished product testing. Instead, it should encompass the whole manufacturing process.
In this list, we explore some of the latest key techniques in cell therapy QC that aim to address the above attributes.
1) Tests for assessing starting material
The safety and efficacy of cell therapy products depends highly on the quality of the starting material from which they are derived. Ideally, there would be an internationally accepted "criteria" for what constitutes a "clinical grade" iPSC line. To achieve this, the industry must agree on critical quality attributes that take many factors into consideration, including identity, stability, viability, potency, and sterility. These are likely to complement existing standard assays associated with master cell banks. Examples of quality control assays for starting material include:
Karyotype analysis
Karyotype analysis, or "karyotyping" is the process of pairing and ordering all chromosomes and is used to assess whether pluripotent stem cells have accumulated culture-driven mutations. Gross genetic changes can be observed, as well as more subtle changes including deletions, duplications, translocations or inversions.3
Tests for pluripotency
How can we be sure that iPSCs are in fact pluripotent? Pluripotent stem cells are defined by their ability to differentiate into cells from any of the three germ layers, and so performing this differentiation test is one approach. Pluripotency markers can be used to predict cells with “functional pluripotency”, to be used in flow cytometry and immunohistochemistry. Validated analysis templates are needed for flow cytometry, as flow threshold markers involve some subjectivity.2,4
Short tandem repeat analysis
Short tandem repeat (STR) genotyping of cells is used to evaluate specific repeated segments of DNA that are typically two to six base pairs in length, called STRs. STR genotyping can be used to discriminate between DNA profiles and in the routine authentication of cells and tissues. It should be performed by an accredited laboratory using a commercially available kit.2
2) Single cell transcriptomics
Next-generation sequencing (NGS) has dramatically advanced our understanding of different pathologies and disease risk, while enabling new diagnostic capabilities. However, as in-depth transcriptome analysis requires the profiling of a large number of cells, conventional bulk population sequencing only provides the average expression signal for a group of cells.5 As cells from a particular tissue are not necessarily homogeneous, important cell-to-cell variability may be missed.
Single-cell transcriptomics is here to change that, and is seen to be one of the most promising emerging technologies for cell therapy QC. One of the major priorities for the cell therapy industry is to identify the genes and pathways that define differences in cell states, and single-cell transcriptomics could help achieve this by enabling researchers to:5,6
● Identify panels of markers for cell monitoring and control during manufacture
● Track the trajectories of distinct cell lineages in development
● Uncover regulatory relationships between genes
● Classify cells and study their clustering
● Identify rare cell populations
Single-cell RNA sequencing (sc-RNA-seq) protocols allow the transcriptional profile of thousands of single cells to be characterized at one time,7 as well as studies of DNA methylation,8 histone modification9 and chromatin accessibility.9 scRNA-seq technologies differ in the way that cells are separated and labeled, but all typically work on the same general process; cells are isolated, lysed and RNA is reverse transcribed into cDNA using uniquely barcoded nanoparticles. Following second-strand synthesis, cDNA is amplified through polymerase chain reaction and then sequenced using NGS.5 By tracking the uniquely barcoded nanoparticles, researchers can keep track of which transcripts came from which cells.
3) Quantitative software to analyze live cell imaging data
Pluripotent stem cells are renowned for their potential to differentiate into different cell types, and their many possible applications in regenerative medicine. Pluripotent stem cells, which include iPSCs and embryonic stem cells, vary in their tendency to differentiate into specific lineages.10 Therefore, a selection process is needed to ensure that pluripotent stem cells with high pluripotency are the ones that are used in regenerative medicine.
Ideally, the selection process would be inexpensive, fast and relatively effortless. While it is likely that a series of techniques would be used to identify the desired cells, one of the first stops of the QC train might be live cell imaging. With major advances in cell microscopy, scientists can now visualize organelles, map the movement of chromosome loci and sense mechanical forces.
Despite the huge capabilities that live cell imaging allows, deciding how to manage and use the data generated is another challenge. Developing algorithms that allow scientists to make confident decisions during quality control processes is a major priority for the field. One recent paper in Scientific Reports describes the development of an imaging system which enables quantitative evaluation of the degrees of somatic cell reprogramming and pluripotent stem cell differentiation.11 Through the generation of a “Phase Distribution” index, pluripotent stem cells can be grouped into colonies with high or low pluripotency, in a way that is both non-invasive and unbiased.
4) Tools for assessing tumorigenicity
Human embryonic cells have been likened to a “double-edged sword”; the traits that enable them to self-renew and differentiate into cells of the three germ layers also make them tumorigenic.12 When injected into immunodeficient mice, human embryonic stem cells form benign germ cell tumors, known as teratomas.13 Although they are not identical, human iPScs also share their tumorigenic traits.12 This is a critical safety hurdle, as undifferentiated pluripotent stem cells persisting in the final product could initiate tumor development in transplanted patients.4 Other factors such as cell transformation or genomic instability can also contribute to tumorigenicity.
Therefore, tools are needed to evaluate tumorigenic potential of cell therapies. Despite the increasing number of cell therapy products entering clinical trials, there is currently no global consensus on the best method for tumorigenicity evaluation.14 In light of this, the Health and Environmental Sciences Institute (HESI, a nonprofit institution) established a committee to generate science-based evidence needed to reach a consensus on the strategy for evaluating tumorigenicity (CT-TRACS: Cell Therapy—TRAcking, Circulation, and Safety).
In 2019, the CT-TRACS committee published a position paper in Cytotherapy that highlighted the limitations of current available approaches and likely future directions.4 They noted that:
● Tumorigenicity testing theoretically refers to the detection of either residual undifferentiated cells or transformed cells in the final product, both of which are seen as “contaminants” or “impurities” to the final differentiated cell therapy product
● Due to the complexities of cell therapies, it is likely that a suite of tumorigenicity tests will be developed on a case-by-case basis for individual cell products
● Cell tumorigenicity is distinct from cell oncogenicity
Currently available technologies
In vivo tests
Several immunocompromised animal models provide opportunities for in vivo tumorigenicity assessment, provided proof of engraftment and survival of the transplanted cell product can be successfully demonstrated.4 Just like in vitro tests, there is no global consensus about the parameters required to show that the cells are unlikely to form tumors.
In vitro tests:
Listed in the table below are methods that can be used to detect different aspects of tumorigenicity:4
Methods | Used to detect |
Flow cytometry, quantitative RT-PCR, droplet digital PCR, highly efficient culture of pluripotent stem cells, detection of marker molecules released into culture medium | Pluripotent stem cells |
Cell proliferation assay | Immortalized cells |
Digital soft agar colony formation assay | Anchorage-independent cell growth |
Karyotype analysis, array comparative genomic hybridization, fluorescence in situ hybridization, NGS | Genomic instability |
Emerging technologies: Organ-on-a-chip
Organ-on-a-chip technology could be used to simulate tissue transplantation into patient-derived cells and identify tumor development.15 Although this approach is in early stages of development, several proof-of-concept studies have shown its potential.
5) Sterility tests
Unlike some biopharmaceutical products, cell therapy products cannot be put through a final sterile filtration step. Furthermore, the limited product shelf-life of cell therapy products poses an additional challenge. This creates a need for rapid microbial methods to ensure contaminants are removed during the manufacturing process. While a range of tests exist for identifying mycoplasma, bacteria and viruses, rapid qPCR is one that shows particular promise. Last year, a rapid qPCR test for mycoplasma was approved by the Food and Drug Administration, Health Canada and the European Medicines Agency for use in CAR-T products in clinical studies.16
Establishing protocols for cell therapy QC requires the industry to come to a consensus on the standardization of parameters and analytics. Understanding the implications of specific mutations, passage number and other factors will help guide the industry towards the most suitable techniques and quality parameters.
References:
2. Sullivan S, Stacey GN, Akazawa C, et al. Quality control guidelines for clinical-grade human induced pluripotent stem cell lines. Regen Med. 2018;13(7):859-866. doi:10.2217/rme-2018-0095
3. O'Connor, C. (2008) Karyotyping for chromosomal abnormalities. Nature Education 1(1):27
4. Sato Y, Bando H, Di Piazza M, et al. Tumorigenicity assessment of cell therapy products: The need for global consensus and points to consider. Cytotherapy. 2019;21(11):1095-1111. doi:10.1016/j.jcyt.2019.10.001
5. Hwang B, Lee JH, Bang D. Single-cell RNA sequencing technologies and bioinformatics pipelines. Exp Mol Med. 2018;50(8):1-14. doi:10.1038/s12276-018-0071-8
6. Wagner A, Regev A, Yosef N. Revealing the vectors of cellular identity with single-cell genomics. Nat Biotechnol. 2016;34(11):1145-1160. doi:10.1038/nbt.3711
7. AlJanahi AA, Danielsen M, Dunbar CE. An Introduction to the Analysis of Single-Cell RNA-Sequencing Data. Mol Ther Methods Clin Dev. 2018;10:189-196. doi:10.1016/j.omtm.2018.07.003
8. Karemaker ID, Vermeulen M. Single-Cell DNA Methylation Profiling: Technologies and Biological Applications. Trends Biotechnol. 2018;36(9):952-965. doi:10.1016/j.tibtech.2018.04.002
9. Ku WL, Nakamura K, Gao W, et al. Single-cell chromatin immunocleavage sequencing (scChIC-seq) to profile histone modification. Nat Methods. 2019;16(4):323-325. doi:10.1038/s41592-019-0361-7
10. Osafune K, Caron L, Borowiak M, et al. Marked differences in differentiation propensity among human embryonic stem cell lines. Nat Biotechnol. 2008;26(3):313-315. doi:10.1038/nbt1383
11. Nishimura K, Ishiwata H, Sakuragi Y, Hayashi Y, Fukuda A, Hisatake K. Live-cell imaging of subcellular structures for quantitative evaluation of pluripotent stem cells. Sci Rep. 2019;9(1):1777. doi:10.1038/s41598-018-37779-x
12. Ben-David U, Benvenisty N. The tumorigenicity of human embryonic and induced pluripotent stem cells. Nat Rev Cancer. 2011;11(4):268-277. doi:10.1038/nrc3034
13. Kooreman NG, Wu JC. Tumorigenicity of pluripotent stem cells: biological insights from molecular imaging. J R Soc Interface. 2010;7 Suppl 6:S753-763. doi:10.1098/rsif.2010.0353.focus
14. S de Wilde, Hj G, Ml Z, P M. Clinical development of gene- and cell-based therapies: overview of the European landscape. Mol Ther Methods Clin Dev. 2016;3:16073-16073. doi:10.1038/mtm.2016.73
15. Caballero D, Kaushik S, Correlo VM, Oliveira JM, Reis RL, Kundu SC. Organ-on-chip models of cancer metastasis for future personalized medicine: From chip to the patient. Biomaterials. 2017;149:98-115. doi:10.1016/j.biomaterials.2017.10.005
16. Dreolini L, Cullen M, Yung E, et al. A Rapid and Sensitive Nucleic Acid Amplification Technique for Mycoplasma Screening of Cell Therapy Products. Molecular therapy Methods & clinical development. 2020;17:393—399. doi:10.1016/j.omtm.2020.01.009