September 29, 2021
Justyna Lisowska & Marie-Ange Kouassi


Although cell immunotherapies offer great potential to eradicate cancer and autoimmune and infectious diseases, their unique nature gives rise to many challenges that must be overcome before their widespread application.1,2  Unlike standard therapeutics, cell therapies are based on living material, which evolves and responds to changes in the surrounding environment. As a result, the activity and quality of cell therapies depend not only on the choice of an appropriate therapeutic target, a reliable manufacturing process, and the specific desired attributes of the cellular product, but also on the complex interplay between the targeted cells, immune and stromal cells, and the host microbiome.

Given the high cost of cell therapies and the complex and invasive procedures involved in their development and administration, thorough patient evaluation before treatment delivery is crucial. This helps to ensure the maximum therapeutic benefit and minimize the risk of wasting valuable biological resources. Systemic profiling of donors is also essential to provide a product with optimal attributes and match the right cell therapy to the right patient. Throughout the development process, it is highly important to perform molecular and functional characterization of the product and its target to guarantee its therapeutic benefit.

Also, regulatory authorities require long-term post-treatment patient monitoring to confirm the efficacy of the therapy and reduce the risk of adverse events.3 As we are still learning from such therapies, this data is also used to define standards for the best patient healthcare outcomes. Consequently, to improve and broaden the clinical success of cell therapies, information should be collected and analyzed throughout all stages of cell therapy product development and delivery.

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Patient Profiling Before Therapy Administration

Cell therapies are highly personalized treatments whose efficacy relies on the biological compatibility between the living drug and the patient. Hence, the evaluation of patient suitability for this treatment is of high importance. A major patient inclusion criterion is the antigen expression level on target cells. As indicated by preclinical studies, a minimum expression threshold needs to be achieved to trigger persistent anti-cancer activity.4,5,6 At the same time, the antigen expression ratio between cancerous and non-malignant cells should also be assessed to limit on-target, off-tumor toxicities which results from the recognition of the same, non-specific antigen on healthy cells.7 The presence of negative checkpoint regulators (NCRs) such as PD-L1 on tumor cells should be verified in advance to prevent NCR-dependent suppression of T-cell proliferation and cytotoxic activity. In addition to the antigen and NCR expression level and/or presence of pre-existing antigen-negative subclones within the patient’s tumor, genetic alterations such as TMB (tumor mutational burden), MSI (microsatellite instability), and DNA repair dysfunction should be evaluated. Genetic instability may be a positive indicator for the therapy as it contributes to the generation of neo-antigens which in turn triggers immune reactions.8 On the other hand, a higher disease burden is associated with an increased likelihood of immunotoxicity.4,9 Evaluation of a patient’s baseline level of inflammatory mediators or expressed cytokine receptors could mitigate the potential risk of such toxicity.

A patient’s treatment history can also affect cell therapy efficacy. It has been shown that the risk of antigen-negative relapse can be increased by previous immunotherapies targeting the same antigens.10 In contrast, chemotherapy has been shown to improve cell therapy efficacy by triggering increased tumor cell immunogenicity, depleting suppressive immune cell populations11,12, and facilitating tumor infiltration by T-cells.13 Also, chemotherapy-dependent lymphodepletion, required before administration of adoptive cell therapies, has been shown to improve in-vivo T-cell expansion and persistence14 by upregulating cytokine production and suppressing myeloid-derived suppressor cells.15

Donor Evaluation before Cell Therapy Manufacturing

Underlying pre-existing comorbidities and pharmacotherapies can drastically decrease T-cell yield, proliferative potential, or response to cytokines.15 This prevents the cells from being useful for autologous therapy development. Therefore, an assessment of the donor’s medical condition is of prime importance to ensure the quality and safety of the final product during allogeneic therapy development. It is well documented that chronic diseases and uncontrolled viral infections may lead to T-cell dysfunction and exhaustion. This eventually limits in-vitro and in-vivo expansion as well as post-implantation persistence.16 Finally, the immunological compatibility between the donor and the patient needs to be assessed to prevent immunorejection of the therapeutic product.

Key Factors to Consider During Cell Product Manufacturing

Cell Phenotype Characterization

Once the right donor is chosen and the cells are collected, a thorough assessment of cell phenotype and biological function is required. This enables the selection of cells with characteristics reflective of a high-quality product. Ensuring the purity of the starting material by eliminating inhibitory cell populations is essential. Following this, it is important to select the appropriate subtypes for engineering to achieve long-term desired effects in-vivo. For example, it has been shown that cell populations with high expression of the IL-6 receptor and genes involved in early memory differentiation result in a better therapeutic response.17 While both CD4+ and CD8+ T cells are commonly used for adoptive cell therapies, the ratio between these cell populations may affect their persistence and expansion in-vivo.4 Understanding the differences between T cell subtypes and selecting those with optimal properties can increase product efficacy.

Following genetic manipulation aimed at enhancing cells’ anti-tumor properties, consistent monitoring of CAR/TCR expression levels on T-cells is required. It is also recommended to check the expression of negative checkpoint regulators since T-cell dysfunction seems to correlate with co-expression of PD-1, TIM-3, and LAG-3.16 Assessment of T cell activation following stimulation by the tumor antigen could also be helpful to determine the efficacity of the final product. For instance, engineered antigen-presenting cell surfaces have been successfully used to mimic the interaction of CAR-T cells with target tumor cells and measure the level of activation and degranulation of effector cells.18 Other ex-vivo, cell-mediated cytotoxicity readouts such as chromium(51Cr)-release, bioluminescence, impedance-based, or flow cytometry assays could also be used to confirm the capacity of T-cells to effectively eliminate/kill tumor.19 Finally, in addition to cell phenotype, an optimal cell yield needs to be achieved to ensure successful therapy transfer. While the optimal protocol for T cell culture is yet to be established, T cell expansion may be dependent on TCR expression.20

Cell Genetic Engineering

Other key aspects to take into consideration include approaches used during gene editing/transfer. The design of the genetic construct—including the choice of suitable antigen-binding or co-stimulatory domain—influences various aspects of the biological activity of the final product in-vivo, such as expansion kinetics, duration of persistence, and tumor-killing properties. Optimal gene transfer and gene insertion approaches must also be used to maximize anti-tumor responses.4

Throughout manufacturing, approaches such as targeted locus amplification (TLA) can be applied to verify targeted gene insertion. This technology can also be used to perform variant analysis to identify desired (or undesired) characteristics of cells for further downstream engineering (using e.g., CRISPR). To ensure a high-quality end product, assessing cells efficiently for identity, stability, as well as biosafety, is crucial.  In fact, there are multiple potential entry points for contamination of cell therapies by adventitious agents (viruses, bacteria, and mycoplasma) that could impose harm on patients. Companies developing advanced therapy medicinal products (ATMPs) must adopt advanced technological solutions tailored to address these challenges with a data-driven approach. 

Monitoring Patients after Treatment Administration

Following infusion with the cell therapy, it is critical to monitor the patient’s health condition in the long term to ensure product safety and continuous efficacy. This involves monitoring disease burden as well as the assessment of vital signs, blood counts, CRP measurement, chemistry panels, cardiac telemetry, daily fluid balance, body weights, and much more. In addition to monitoring clinical signs, gaining insights into the patient’s immune response and tumor characteristics through the collection of genetic, proteomic, functional assay, and phenotypic cellular data is paramount to assess the functionality and safety of the therapy. Evaluating the systemic level of cytokines post-infusion can help prevent or alleviate adverse effects such as Cytokine Release Syndrome (CRS) or CAR-T related encephalopathy syndrome (CRES). One can perform this by gathering and analyzing blood chemistry data to identify predictive biomarkers. Studies have indicated that soluble factors produced in the first 3 days following CAR-T-cell infusion (IFN-γ, IL1RA, and soluble gp130), could be useful predictors of severe CRS in most patients.15 A systems approach may also help to decipher the contribution of other factors (macrophages, IL-6, IL-1, and endothelial activation) in the pathogenesis of cell therapy-induced toxicity.11

The efficacy of the cells following infusion depends on their ability to remain activated, expand exponentially, and persist in vivo. Short-term relapse can occur within one year of remission due to a lack of cell persistence. Long-term relapse can result from tumor resistance mechanisms such as antigen loss or modulation due to alternative splicing or the emergence of antigen-negative clones. Therefore, to mitigate the risk of relapse and ensure product efficacy, it is important to perform ongoing surveillance of the T-cell attributes (e.g., persistence, expression of CAR/TCR) and tumor biology.

Unlocking the Path to Precision

The large amounts of complex data collected during donor and patient profiling, cell therapy manufacturing, and post-treatment patient monitoring, contain a wealth of valuable information that could guide cell therapy development. By extracting knowledge from this data, we can maximize cell therapy quality and efficacy and prevent adverse toxicity-related events. To facilitate this, a scalable, flexible, and agile system capable of processing and analyzing the ever-increasing amounts of data generated throughout the entire process of therapy development is required. Genedata Profiler® enables scientists to automatically gather such data from a variety of sources into a centralized site for efficient harmonization and integration. Thanks to its superior interoperability, this collaborative enterprise software allows rapid presentation of data collected as intuitive customizable dashboards on almost any BI or analytics tool. With Genedata Profiler, physicians and scientists are equipped with the data they need to identify the best donor for a particular therapy or a patient likely to respond to treatment. This data accessibility is also crucial during cell therapy manufacturing, allowing scientists to monitor characteristics of the cell therapy or monitor a patient’s condition following treatment. Being informed with the right data at the right time is the core of a precision medicine approach. This is exactly how we aim to support companies developing the next generation of safe, efficacious, and fit-for-purpose cell therapies. 

Learn More About Genedata Profiler

Justyna Lisowska, Ph.D., Scientific Communication Specialist, Genedata Profiler
Marie-Ange Kouassi, Ph.D., Scientific Communication Specialist, Genedata Profiler


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