Background Checkpoint inhibition (CPI) therapies have led to large successes in treating certain cancer types, but they are largely ineffective in immunologically 'cold' tumors, with an immunosuppressive microenvironment. The immunosuppressive tumor microenvironment (TME) is dominated by Treg and suppressive myeloid cells. Patients who respond well to CPI therapies exhibit a Th1-biased TME driven by IFNg and related genes. Thus, approaches that can safely transform an immunosuppressive TME would be beneficial. Methods mRNA-based therapies are a rapidly growing class of medications that can redefine how many diseases are treated. These therapies enable the production of biologics directly in the patient and mRNA LNPs are straightforward to manufacture at scale. Despite these key advantages, mRNA therapeutics are yet to show their true potential in oncology. Dose limiting toxicities of mRNA immunotherapies are driven, in part, by systemic payload (encoded protein) toxicity, which can be avoided by engineering the mRNA to improve its onco-selectivity and thereby reduce its on-target off-tumor toxicity. To tackle this challenge, Kernal Biologics has developed onco-selective mRNA LNP therapies that utilize a computational pipeline enabled by machine learning. The aim is to overcome the immunosuppressive conditions within the tumor microenvironment. Results Previously, we have shown that local onco-selective mRNA LNP therapy via intratumoral injections can results in complete responses in various preclinical models, including those that are resistant to checkpoint inhibitors. Here we report the outcome of in vivo proof-of-concept studies for systemic mRNA LNP administration. In a syngeneic MC38 tumor model, KR-336 was administered intravenously as a monotherapy, resulting in impressive anti-tumor effectiveness. This was evidenced by tumor regression, multiple complete responses, and enhanced overall survival rates. The mRNA LNPs were well-tolerated and prompted immune activation, fostering a pro-inflammatory tumor microenvironment. Conclusions These findings collectively indicate the viability of systemic onco-selective mRNA LNP therapy as a potential treatment option for cancers characterized by an immunosuppressive tumor microenvironment. Additionally, it has the potential to drastically expand the patient population that can benefit from cancer immunotherapy. Ethics Approval All in vivo animal studies were performed in accordance with the IACUC number 2021–1309 at CRADL, Cambridge MA

Novel improved cancer immunotherapies are needed, since most cancer patients exhibit a treatment resistant tumor microenvironment to currently available immunotherapeutic modalities. Due to primary resistance or the development of acquired resistance to therapeutic approaches these patients unfortunately do not benefit from a long-lasting overall survival benefit. Combination treatments are a promising approach to induce a sustained anti-tumor immune response. However, dose limiting adverse events in healthy tissues and/or the complex expensive production requirements have limited the full therapeutic potential of combinatorial applications. mRNA-based combinatorial therapy options have evolved by recent advancements in the production, purification, and delivery of mRNA to cells. Today, mRNA therapies are a rapidly growing class of medications that can redefine how many diseases are treated. These therapies enable the production of biologics directly in the patient and mRNA LNPs are easy to manufacture at scale. Despite these key advantages, mRNA therapeutics are yet to show their true potential in oncology. Dose limiting toxicities of mRNA immunotherapies are driven, in part, by systemic payload (encoded protein) toxicity, which can be avoided by engineering the mRNA to improve its onco-selectivity and thereby reduce systemic target-mediated adverse events. Kernal Biologics develops novel onco-selective mRNA therapies directed to breach the immunosuppressive tumor microenvironment. Based on our proprietary machine learning-enabled computational pipeline, we designed our next generation mRNA therapeutics. These mRNAs have the potential to increase the depth and breadth of anti-PD1/PD-L1 treatment plus enable responses in patients that are currently non-responders or refractory to the clinically approved immune checkpoint blockade therapies. Here, we describe combination therapies of tumor-selective mRNA LNPs that achieve strong and lasting anti-tumor efficacy in syngeneic tumor models. We observed regression of established tumors, complete responses (CRs) and improved overall survival. At efficacious doses the mRNA LNPs were well tolerated while driving anti-tumor immune activation and modulation of the tumor microenvironment. Mouse blood hematology and chemistry analyses were within a normal range. Similarly, pathological immunohistochemistry analysis of liver, spleen and bone marrow revealed no findings. In summary, our data support the feasibility of onco-selective mRNA combination treatment of a variety of cancers with poor T cell infiltration and immunosuppressive TME, major obstacles in cancer immunotherapy. Citation Format: Manfred Kraus, Rudy Christmas, Tom A. Addison, Yulia Rybakova, Leona Lee, Jieni Xu, Mark Krimmer, Cafer Ozdemir, Burak Yilmaz, Yusuf Erkul. Combination therapy with onco-selective mRNA LNPs targets the complex immunosuppressive tumor microenvironment and is well tolerated at efficacious doses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3232.

Background Cancer immunotherapy has made significant advancements in revolutionizing cancer treatment, but the presence of T regulatory (Treg) cells within tumors presents a major hurdle. These cells can suppress the activation of effector immune cells induced by the immunotherapy, thus hindering the desired anti-tumor response. Specific depletion of tumor Tregs is proven to be an efficient strategy to improve efficacy of anti-PD-1/PD-L1 therapies. Methods mRNA-based combinatorial therapy options have evolved by recent advancements in the production, purification, and delivery of mRNA to cells. Today, mRNA therapies are a rapidly growing class of medications that can redefine how many diseases are treated. These therapies enable the production of biologics directly in the patient and mRNA LNPs are straightforward to manufacture at scale. Despite these key advantages, mRNA therapeutics are yet to show their true potential in oncology. Dose limiting toxicities of mRNA immunotherapies are driven, in part, by systemic payload (encoded protein) toxicity, which can be avoided by engineering the mRNA to improve its onco-selectivity and thereby reduce systemic target-mediated adverse events. To address that challenge, Kernal Biologics has developed onco-selective mRNA LNP therapies (KR-505) using a machine learning-enabled computational pipeline, targeting Treg cells within the immunosuppressive tumor microenvironment. Results In preclinical studies using a syngeneic tumor model (C57BL6/MC38), KR-505 demonstrated strong anti-tumor efficacy, leading to tumor regression, complete responses, and improved overall survival. These mRNA LNPs (lipid nanoparticles) were well-tolerated, promoting anti-tumor immune activation and modulating the tumor microenvironment. Furthermore, combination treatment with anti-PD-1 therapies showed even better efficacy. Notably, treatment with KR-505, but not the inactive drug analog, led to a significant reduction in Treg cell numbers within the tumors. Reimplantation of complete responders resulted in no tumor growth, indicating the development of anti-tumor immunity. Conclusions Our findings support the feasibility of onco-selective mRNA combination therapy as a potential solution for cancers characterized by an immunosuppressive tumor microenvironment and can help broaden the number of patients who can benefit from anti-PD-1 treatment.