Investigator
Karolinska Institutet
Adaptive NK Cells Exhibit Tumor-Specific Immune Memory and Cytotoxicity in Ovarian Cancer
Abstract Adaptive NK (aNK) cells have emerged as a subset of NK cells with memory-like properties and specific cytotoxicity, offering promising therapeutic potential in cancer immunotherapy. In this study, we explored the role of aNK cells in high-grade serous ovarian cancer, focusing on their ability to establish tumor-specific immune memory and effectively target autologous tumors. Through a combination of in silico, in vitro, and ex vivo approaches, we demonstrated that aNK cells, in contrast to conventional NK cells, exhibit recall responses, specific cytotoxicity, and preferential infiltration into the tumor microenvironment. Our data revealed that aNK cells interact with dendritic cells within the tumor microenvironment via the HLA-E/NKG2C axis and CXCR2 signaling, contributing to their memory formation and tumor-targeting capabilities. These findings suggest that aNK cells could serve as potent agents in NK cell–based immunotherapies, particularly in solid tumors such as high-grade serous ovarian cancer, in which they resist immunosuppressive signals and maintain robust antitumor activity. This study provides new insights into the adaptive-like properties of aNK cells, underscoring their potential for advancing cancer immunotherapy strategies.
Protocol for generating an in vitro 3D multicellular culture model of ovarian high-grade serous carcinoma
The development of translational ovarian cancer models to investigate and overcome treatment resistance, while accounting for the impact of the tumor microenvironment, is critical. Here, we present a protocol to establish a multicellular culture model that retains both genetic complexity and the microenvironment of patient tumors and is amenable to molecular and phenotypic analyses and high-throughput drug testing. We describe steps for culturing and characterizing stromal cells derived from cryopreserved and fresh samples and detail procedures for combining them with organoids.
Efficacy and Safety of Glycosphingolipid SSEA-4 Targeting CAR-T Cells in an Ovarian Carcinoma Model
Abstract Chimeric antigen receptor (CAR) T-cell immunotherapies for solid tumors face critical challenges such as heterogeneous antigen expression. We characterized stage-specific embryonic antigen-4 (SSEA-4) cell-surface glycolipid as a target for CAR T-cell therapy. SSEA-4 is mainly expressed during embryogenesis but is also found in several cancer types making it an attractive tumor-associated antigen. Anti-SSEA-4 CAR-T cells were generated and assessed preclinically in vitro and in vivo for antitumor response and safety. SSEA-4 CAR-T cells effectively eliminated SSEA-4–positive cells in all the tested cancer cell lines, whereas SSEA-4–negative cells lines were not targeted. In vivo efficacy and safety studies using NSG mice and the high-grade serous ovarian cancer cell line OVCAR4 demonstrated a remarkable and specific antitumor response at all the CAR T-cell doses used. At high T-cell doses, CAR T cell–treated mice showed signs of health deterioration after a follow-up period. However, the severity of toxicity was reduced with a delayed onset when lower CAR T-cell doses were used. Our data demonstrate the efficacy of anti-SSEA-4 CAR T-cell therapy; however, safety strategies, such as dose-limiting and/or equipping CAR-T cells with combinatorial antigen recognition should be implemented for its potential clinical translation.
Adaptive RSK‐EphA2‐GPRC5A signaling switch triggers chemotherapy resistance in ovarian cancer
Metastatic cancers commonly activate adaptive chemotherapy resistance, attributed to both microenvironment-dependent phenotypic plasticity and genetic characteristics of cancer cells. However, the contribution of chemotherapy itself to the non-genetic resistance mechanisms was long neglected. Using high-grade serous ovarian cancer (HGSC) patient material and cell lines, we describe here an unexpectedly robust cisplatin and carboplatin chemotherapy-induced ERK1/2-RSK1/2-EphA2-GPRC5A signaling switch associated with cancer cell intrinsic and acquired chemoresistance. Mechanistically, pharmacological inhibition or knockdown of RSK1/2 prevented oncogenic EphA2-S897 phosphorylation and EphA2-GPRC5A co-regulation, thereby facilitating a signaling shift to the canonical tumor-suppressive tyrosine phosphorylation and consequent downregulation of EphA2. In combination with platinum, RSK inhibitors effectively sensitized even the most platinum-resistant EphA2
Mesothelin-Specific CAR T Cells Target Ovarian Cancer
Abstract New therapeutic options for patients with ovarian cancer are urgently needed. Therefore, we evaluated the efficacy of two second-generation mesothelin (MSLN)-directed CAR T cells in orthotopic mouse models of ovarian cancer. Treatment with CAR T cells expressing an MSLN CAR construct including the CD28 domain (M28z) significantly prolonged survival, but no persistent tumor control was observed. Despite lower response rates, MSLN-4–1BB (MBBz) CAR T cells induced long-term remission in some SKOV3–bearing mice. Tumor-infiltrating M28z and MBBz CAR T cells upregulated PD-1 and LAG3 in an antigen-dependent manner while MSLN+ tumor cells expressed the corresponding ligands (PD-L1 and HLA-DR), demonstrating that coinhibitory pathways impede CAR T-cell persistence in the ovarian tumor microenvironment. Furthermore, profiling plasma soluble factors identified a cluster of M28z- and MBBz-treated mice characterized by elevated T-cell secreted factors that had increased survival, higher CD8+ T-cell tumor infiltration, less exhausted CAR T-cell phenotypes, and increased HLA-DR expression by tumor cells. Altogether, our study demonstrates the therapeutic potential of MSLN-CAR T cells to treat ovarian cancer. Significance: These findings demonstrate that MSLN-directed CAR T cells can provide antitumor immunity against ovarian cancer.
Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones
Abstract Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number of possible drug-dose combinations vastly exceeds what could be tested in patient cells. Here, we describe a machine learning approach, scTherapy, which leverages single-cell transcriptomic profiles to prioritize multi-targeting treatment options for individual patients with hematological cancers or solid tumors. Patient-specific treatments reveal a wide spectrum of co-inhibitors of multiple biological pathways predicted for primary cells from heterogenous cohorts of patients with acute myeloid leukemia and high-grade serous ovarian carcinoma, each with unique resistance patterns and synergy mechanisms. Experimental validations confirm that 96% of the multi-targeting treatments exhibit selective efficacy or synergy, and 83% demonstrate low toxicity to normal cells, highlighting their potential for therapeutic efficacy and safety. In a pan-cancer analysis across five cancer types, 25% of the predicted treatments are shared among the patients of the same tumor type, while 19% of the treatments are patient-specific. Our approach provides a widely-applicable strategy to identify personalized treatment regimens that selectively co-inhibit malignant cells and avoid inhibition of non-cancerous cells, thereby increasing their likelihood for clinical success.
