IND-Enabling Studies for a Clinical Trial to Genetically Program a Persistent Cancer-Targeted Immune System

PURPOSE: To improve persistence of adoptively transferred T-cell receptor (TCR)-engineered T cells and durable clinical responses, we designed a clinical trial to transplant genetically-modified hematopoietic stem cells (HSCs) together with adoptive cell transfer of T cells both engineered to express an NY-ESO-1 TCR. Here, we report the preclinical studies performed to enable an investigational new drug (IND) application. EXPERIMENTAL DESIGN: HSCs transduced with a lentiviral vector expressing NY-ESO-1 TCR and the PET reporter/suicide gene HSV1-sr39TK and T cells transduced with a retroviral vector expressing NY-ESO-1 TCR were coadministered to myelodepleted HLA-A2/Kb mice within a formal Good Laboratory Practice (GLP)-compliant study to demonstrate safety, persistence, and HSC differentiation into all blood lineages. Non-GLP experiments included assessment of transgene immunogenicity and in vitro viral insertion safety studies. Furthermore, Good Manufacturing Practice (GMP)-compliant cell production qualification runs were performed to establish the manufacturing protocols for clinical use. RESULTS: TCR genetically modified and ex vivo-cultured HSCs differentiated into all blood subsets in vivo after HSC transplantation, and coadministration of TCR-transduced T cells did not result in increased toxicity. The expression of NY-ESO-1 TCR and sr39TK transgenes did not have a detrimental effect on gene-modified HSC's differentiation to all blood cell lineages. There was no evidence of genotoxicity induced by the lentiviral vector. GMP batches of clinical-grade transgenic cells produced during qualification runs had adequate stability and functionality. CONCLUSIONS: Coadministration of HSCs and T cells expressing an NY-ESO-1 TCR is safe in preclinical models. The results presented in this article led to the FDA approval of IND 17471

Epigenetic Suppression of Transgenic T-cell Receptor Expression via Gamma-Retroviral Vector Methylation in Adoptive Cell Transfer Therapy

Transgenic T-cell receptor (TCR) adoptive cell therapies recognizing tumor antigens are associated with robust initial response rates, but frequent disease relapse. This usually occurs in the setting of poor long-term persistence of cells expressing the transgenic TCR, generated using murine stem cell virus (MSCV) γ-retroviral vectors. Analysis of clinical transgenic adoptive cell therapy products in vivo revealed that despite strong persistence of the transgenic TCR DNA sequence over time, its expression was profoundly decreased over time at the RNA and protein levels. Patients with the greatest degrees of expression suppression displayed significant increases in DNA methylation over time within the MSCV promoter region, as well as progressive increases in DNA methylation within the entire MSCV vector over time. These increases in vector methylation occurred independently of its integration site within the host genomes. These results have significant implications for the design of future viral vector gene-engineered adoptive cell transfer therapies. SIGNIFICANCE: Cellular immunotherapies' reliance on retroviral vectors encoding foreign genetic material can be vulnerable to progressive acquisition of DNA methylation and subsequent epigenetic suppression of the transgenic product in TCR adoptive cell therapy. This must be considered in the design of future generations of cellular immunotherapies for cancer.This article is highlighted in the In This Issue feature, p. 1611

Infusion Product TNFα, Th2, and STAT3 Activities Are Associated with Clinical Responses to Transgenic T-cell Receptor Cell Therapy

Transgenic T-cell receptor (TCR) T cell-based adoptive cell therapies for solid tumors are associated with dramatic initial response rates, but there remain many instances of treatment failure and disease relapse. The association of infusion product cytokine profiles with clinical response has not been explored in the context of TCR T-cell therapy products. Single-cell antigen-dependent secretomic and proteomic analysis of preinfusion clinical TCR T-cell therapy products revealed that TNFα cytokine functionality of CD8+ T cells and phospho-STAT3 signaling in these cells were both associated with superior clinical responsiveness to therapy. By contrast, CD4+ T-helper 2 cell cytokine profiles were associated with inferior clinical responses. In parallel, preinfusion levels of IL15, Flt3-L, and CX3CL1 were all found to be associated with clinical response to therapy. These results have implications for the development of therapeutic biomarkers and identify potential targets for enrichment in the design of transgenic TCR T-cell therapies for solid tumors

Development of Hematopoietic Stem Cell-Engineered Invariant Natural Killer T Cell Therapy for Cancer.

Invariant natural killer T (iNKT) cells are potent immune cells for targeting cancer; however, their clinical application has been hindered by their low numbers in cancer patients. Here, we developed a proof-of-concept for hematopoietic stem cell-engineered iNKT (HSC-iNKT) cell therapy with the potential to provide therapeutic levels of iNKT cells for a patient's lifetime. Using a human HSC engrafted mouse model and a human iNKT TCR gene engineering approach, we demonstrated the efficient and long-term generation of HSC-iNKT cells in vivo. These HSC-iNKT cells closely resembled endogenous human iNKT cells, could deploy multiple mechanisms to attack tumor cells, and effectively suppressed tumor growth in vivo in multiple human tumor xenograft mouse models. Preclinical safety studies showed no toxicity or tumorigenicity of the HSC-iNKT cell therapy. Collectively, these results demonstrated the feasibility, safety, and cancer therapy potential of the proposed HSC-iNKT cell therapy and laid a foundation for future clinical development

Development of Hematopoietic Stem Cell-Engineered Invariant Natural Killer T Cell Therapy for Cancer.

Invariant natural killer T (iNKT) cells are potent immune cells for targeting cancer; however, their clinical application has been hindered by their low numbers in cancer patients. Here, we developed a proof-of-concept for hematopoietic stem cell-engineered iNKT (HSC-iNKT) cell therapy with the potential to provide therapeutic levels of iNKT cells for a patient's lifetime. Using a human HSC engrafted mouse model and a human iNKT TCR gene engineering approach, we demonstrated the efficient and long-term generation of HSC-iNKT cells in vivo. These HSC-iNKT cells closely resembled endogenous human iNKT cells, could deploy multiple mechanisms to attack tumor cells, and effectively suppressed tumor growth in vivo in multiple human tumor xenograft mouse models. Preclinical safety studies showed no toxicity or tumorigenicity of the HSC-iNKT cell therapy. Collectively, these results demonstrated the feasibility, safety, and cancer therapy potential of the proposed HSC-iNKT cell therapy and laid a foundation for future clinical development

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community