Ex vivo expanded patient-derived γδ T-cell immunotherapy enhances neuroblastoma tumor regression in a murine model

Jaquelyn T Zoine1,2, Kristopher A Knight1, Lauren C Fleischer1,3

  • 1Aflac Cancer and Blood Disorders Center, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.

Oncoimmunology
|August 16, 2019
PubMed

An effective therapy regimen for relapsed/refractory high-risk neuroblastoma (NB) includes the anti-GD2 monoclonal antibody, dinutuximab, in combination with temozolomide and irinotecan, supporting a role for chemo-immunotherapy in NB. γδ T cells are an attractive anti-tumor immunotherapy because of their direct cytotoxic activity mediated through cell surface receptors NKG2D and CD16. NKG2D facilitates the innate recognition of stress-induced ligands whereas CD16 recognizes antibody bound to tumors and activates mechanisms of antibody-dependent cellular cytotoxicity (ADCC). This study demonstrates an efficient method for expanding and storing γδ T cells from NB patient-derived apheresis products at clinically relevant amounts. The expanded patient-derived γδ T cells were cytotoxic against the K562 cell line and multiple NB cell lines. Combining γδ T cells with dinutuximab led to a 30% increase in tumor cell lysis compared to γδ T cells alone. Furthermore, low-dose temozolomide in combination with expanded γδ T cells and dinutuximab resulted in increased IFNγ secretion and increased γδ T-cell surface expression of FasL and CD107a. IMR5 NB cell line xenografts established subcutaneously in NSG mice were treated with a regimen of dinutuximab, temozolomide, and γδ T cells. This combination caused targeted killing of NB xenografts in vivo, reducing tumor burden and prolonging survival. These data support the continued preclinical testing of dinutuximab and temozolomide in conjunction with γδ T-cell immunotherapy for patients with recurrent/refractory NB.

Related Concept Videos

Tumor Immunotherapy01:27

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
1.8K
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.9K
Multiple Regression01:25

Multiple Regression

Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.8K
Correlation and Regression00:53

Correlation and Regression

In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.1K
Regression Analysis01:11

Regression Analysis

Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.1K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.5K