Analysis of organoid and immune cell co-cultures by machine learning-empowered image cytometry

Organoids are three-dimensional (3D) structures that can be derived from stem cells or adult tissue progenitor cells and exhibit an extraordinary ability to autonomously organize and resemble the cellular composition and architectural integrity of specific tissue segments. This feature makes them a useful tool for analyzing therapeutical relevant aspects, including organ development, wound healing, immune disorders and drug discovery. Most organoid models do not contain cells that mimic the neighboring tissue’s microenvironment, which could potentially hinder deeper mechanistic studies. However, to use organoid models in mechanistic studies, which would enable us to better understand pathophysiological processes, it is necessary to emulate the in situ microenvironment. This can be accomplished by incorporating selected cells of interest from neighboring tissues into the organoid culture. Nevertheless, the detection and quantification of organoids in such co-cultures remains a major technical challenge. These imaging analysis approaches would require an accurate separation of organoids from the other cell types in the co-culture. To efficiently detect and analyze 3D organoids in co-cultures, we developed a high-throughput imaging analysis platform. This method integrates automated imaging techniques and advanced image processing tools such as grayscale conversion, contrast enhancement, membrane detection and structure separation. Based on machine learning algorithms, we were able to identify and classify 3D organoids within dense co-cultures of immune cells. This procedure allows a high-throughput analysis of organoid-associated parameters such as quantity, size, and shape. Therefore, the technology has significant potential to advance contextualized research using organoid co-cultures and their potential applications in translational medicine

MCT4 blockade increases the efficacy of immune checkpoint blockade

Background & Aims Intratumoral lactate accumulation and acidosis impair T-cell function and antitumor immunity. Interestingly, expression of the lactate transporter monocarboxylate transporter (MCT) 4, but not MCT1, turned out to be prognostic for the survival of patients with rectal cancer, indicating that single MCT4 blockade might be a promising strategy to overcome glycolysis-related therapy resistance. Methods To determine whether blockade of MCT4 alone is sufficient to improve the efficacy of immune checkpoint blockade (ICB) therapy, we examined the effects of the selective MCT1 inhibitor AZD3965 and a novel MCT4 inhibitor in a colorectal carcinoma (CRC) tumor spheroid model co-cultured with blood leukocytes in vitro and the MC38 murine CRC model in vivo in combination with an antibody against programmed cell death ligand-1(PD-L1). Results Inhibition of MCT4 was sufficient to reduce lactate efflux in three-dimensional (3D) CRC spheroids but not in two-dimensional cell-cultures. Co-administration of the MCT4 inhibitor and ICB augmented immune cell infiltration, T-cell function and decreased CRC spheroid viability in a 3D co-culture model of human CRC spheroids with blood leukocytes. Accordingly, combination of MCT4 and ICB increased intratumoral pH, improved leukocyte infiltration and T-cell activation, delayed tumor growth, and prolonged survival in vivo. MCT1 inhibition exerted no further beneficial impact. Conclusions These findings demonstrate that single MCT4 inhibition represents a novel therapeutic approach to reverse lactic-acid driven immunosuppression and might be suitable to improve ICB efficacy

Analysis of organoid and immune cell co-cultures by machine learning-empowered image cytometry

Organoids are three-dimensional (3D) structures that can be derived from stem cells or adult tissue progenitor cells and exhibit an extraordinary ability to autonomously organize and resemble the cellular composition and architectural integrity of specific tissue segments. This feature makes them a useful tool for analyzing therapeutical relevant aspects, including organ development, wound healing, immune disorders and drug discovery. Most organoid models do not contain cells that mimic the neighboring tissue’s microenvironment, which could potentially hinder deeper mechanistic studies. However, to use organoid models in mechanistic studies, which would enable us to better understand pathophysiological processes, it is necessary to emulate the in situ microenvironment. This can be accomplished by incorporating selected cells of interest from neighboring tissues into the organoid culture. Nevertheless, the detection and quantification of organoids in such co-cultures remains a major technical challenge. These imaging analysis approaches would require an accurate separation of organoids from the other cell types in the co-culture. To efficiently detect and analyze 3D organoids in co-cultures, we developed a high-throughput imaging analysis platform. This method integrates automated imaging techniques and advanced image processing tools such as grayscale conversion, contrast enhancement, membrane detection and structure separation. Based on machine learning algorithms, we were able to identify and classify 3D organoids within dense co-cultures of immune cells. This procedure allows a high-throughput analysis of organoid-associated parameters such as quantity, size, and shape. Therefore, the technology has significant potential to advance contextualized research using organoid co-cultures and their potential applications in translational medicine

MCT4 blockade increases the efficacy of immune checkpoint blockade

Background & Aims Intratumoral lactate accumulation and acidosis impair T-cell function and antitumor immunity. Interestingly, expression of the lactate transporter monocarboxylate transporter (MCT) 4, but not MCT1, turned out to be prognostic for the survival of patients with rectal cancer, indicating that single MCT4 blockade might be a promising strategy to overcome glycolysis-related therapy resistance.Methods To determine whether blockade of MCT4 alone is sufficient to improve the efficacy of immune checkpoint blockade (ICB) therapy, we examined the effects of the selective MCT1 inhibitor AZD3965 and a novel MCT4 inhibitor in a colorectal carcinoma (CRC) tumor spheroid model co-cultured with blood leukocytes in vitro and the MC38 murine CRC model in vivo in combination with an antibody against programmed cell death ligand-1(PD-L1).Results Inhibition of MCT4 was sufficient to reduce lactate efflux in three-dimensional (3D) CRC spheroids but not in two-dimensional cell-cultures. Co-administration of the MCT4 inhibitor and ICB augmented immune cell infiltration, T-cell function and decreased CRC spheroid viability in a 3D co-culture model of human CRC spheroids with blood leukocytes. Accordingly, combination of MCT4 and ICB increased intratumoral pH, improved leukocyte infiltration and T-cell activation, delayed tumor growth, and prolonged survival in vivo. MCT1 inhibition exerted no further beneficial impact.Conclusions These findings demonstrate that single MCT4 inhibition represents a novel therapeutic approach to reverse lactic-acid driven immunosuppression and might be suitable to improve ICB efficacy