While mortality for all cancers combined has declined1, certain tumors such as glioblastoma (GBM) remain incurable, and death rates from liver cancer increased 43% in the past 15 years. These tumors are highly refractory to treatment, and share commonalities in their complex tumor microenvironments participating to their inflammatory and immunosuppressive nature. More specifically, they both contain tissue-resident macrophage populations established early during development5, which functions as tumor-associated macrophages (TAMs) is still unclear. We have implemented research projects to functionally address the complexity and dynamics of macrophage subpopulation phenotype in GBM and hepatocellular carcinoma (HCC), in the context of other components of the tumor immune microenvironment (TIME).
We have identified that recurrent GBM post-standard of care treatment display an altered TIME composition compared to primary tumors, with increased content of infiltrating monocytes, macrophages and neutrophils. Our preliminary results suggest that fine-tuned dependencies on specific immune populations occur based on the genetic make-up of cancer cells and on the timing and duration of therapy implementation. Using GBM murine models based on different oncogenic drivers, we now aim to determine the molecular basis of these dynamic changes and gain insights into tumor cell-stromal interactions that benefit relapse. Importantly, these findings can be exploited to enhance the efficacy of cytotoxic treatment, by either targeting whole immune cell populations or altering their adaptive phenotype in the course of treatment.
We performed RNA sequencing on infiltrating bone-marrow derived macrophages (BMDM) and tissue resident microglia MG sorted from recurrent tumors compared to untreated murine GBM. We identified a convergence of the transcriptional signature of these two subpopulations of macrophages, specific to tumor relapse, and validated it in human GBM5. Importantly, the nodes of transcription factors at the center of this acquired signature, and the upstream signaling pathways are neither active in untreated GBM, nor in early phases of radiotherapy response, suggesting a rewiring of MG and infiltrating BMDM programming at recurrence. These include potentially targetable pathways, as Notch, ApoE and TGF-b. Our preliminary results from patient sample analyses support these observations and underline their relevance to the human pathology. We now plan to genetically target each macrophage subpopulations and the network of signaling pathways underlying their evolution in recurrent gliomas.
Emerging evidence suggests that the genetic make-up of cancer cells shapes the immune landscape of cancers, a feature complicated in HCC by its underlying chronic inflammation. In order to reproduce the diversity of oncogenic events and immune cell recruitment found in HCC, we implemented the liver cancer model based hydrodynamic gene delivery system of Sleeping Beauty-mediated somatic integration and CRISPR-mediated knock out for long-term in vivo gene expression in mouse hepatocytes. We are using different genetic combination relevant to the human pathology to drive these murine HCC (B-catenin, Myc, pTEN or p53). Supporting results obtained in our glioma studies, we found that the adaptive and innate immune cell content was affected by cancer cell genetic background, with macrophages showed the largest differences in content and education. We now aim to unravel the cancer cell-intrinsic regulation mechanisms underlying TIME shaping in genetically distinct HCC, which could guide personalized treatment approach targeting immune cells in this disease.