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Predictive Biomarkers for the Responsiveness of Recurrent Glioblastomas to Activated Killer Cell Immunotherapy

ABSTRACT: Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor, but the current therapeutic approaches have very limited impact on increase of the patients’s survival with GBM. Our recent clinical trial with autologous activated nature killer (NK) cells (AKCs) including 14 patients with recurrent GBM found that the progression-free and overall survival times were significantly increased in some patients in the treatment group. In the present study, we identified TNFRSF18, TNFSF4, and IL12RB2 as biomarkers that predict response to NK cell therapeutics by studying the tumor-immune microenvironment using NanoString and qRT-PCR analyses. In addition, our results show that responders to NK therapy have an immune-activated tumor microenvironment, whereas non-responders do not. Considering that immune and inflammatory response-enrichment is related to the high-risk group in this tumor type, our findings highlight a new treatment strategy of NK cell therapeutics for patients with highly aggressive recurrent GBM.

ORGANISM(S): Homo sapiens

PROVIDER: GSE207753 | GEO | 2023/02/01

REPOSITORIES: GEO

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Project description:Treating recurrent GBM is a clinical challenge due to its highly resistant and aggressive nature. In order to develop new therapeutic targets for recurrent GBM a better understanding of its molecular landscape is necessary. Here we used a cellular model, developed in our lab which generates paired primary and recurrent samples from GBM cell lines and primary patient samples hence allowing us to compare the molecular differences between the two populations. Total RNA seq analysis of parent and recurrent population of two cell lines and one patient sample revealed a significant upregulation of Extracellular matrix interaction in recurrent population. Since matrix stiffness plays a pivotal role in cell-ECM interaction and downstream signaling, we developed a system that mimicked the brain like substrate stiffness by using collagen coated polyacrylamide-based substrate whose stiffness can be modified from normal brain (0.5kPa) to tumorigenic (10kPa). Using these substrates, we were able to capture the morphological and physiological differences between parent and recurrent GBM which were not evident on plastic surfaces (~1 GPa). On 0.5kPa, unlike circular parent cells, recurrent GBM cells showed two morphologies (circular and elongated). The recurrent cells growing on 0.5kPa also showed higher proliferation, invasion, migration and in-vivo tumorigenicity in orthotropic GBM mouse model, compared to parent cells. Furthermore, recurrent cells exhibited elevated velocity irrespective of substrate stiffness, which indicated that recurrent cells may possess inherent differential mechanosignalling ability which was reflected by higher expression of ECM proteins like Collagen IVA, MMP2 and MMP9. Moreover, mice brain injected with recurrent cells grown on 0.5kPa substrate showed higher Young’s modulus values suggesting that recurrent cells conditioned on 0.5kPa make the surrounding ECM stiffer. Importantly, inhibition of EGFR signaling, that is amplified with tissue stiffening in GBM resulted in decreased invasion, migration and proliferation in 0.5kPa recurrent cells, but interestingly survival remained unaffected, highlighting the importance of mimicking the physiological stiffness of the brain mimicking clinical scenario. Total RNA seq analysis of parent and recurrent cells grown on plastic and 0.5kPa substrate identified PLEKHA7 as significantly upregulated gene specifically in 0.5kPa recurrent sample. Higher protein expression of PLEKHA7 in recurrent GBM as compared to primary GBM was validated in patient biopsies. Accordingly, PLEKHA7 knockdown reduced invasion and survival of recurrent GBM cells. Together, these data provides a model system that captures the differential mechanosensing signals of primary and recurrent GBM cells and identifies a novel potential target specific for recurrent GBM.

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Predictive Biomarkers for the Responsiveness of Recurrent Glioblastomas to Activated Killer Cell Immunotherapy

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