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FRIMEDBIO-Fri prosj.st. med.,helse,biol

Tumor-macrophage Interactions - The Promised Land for Identifying Novel Anti-cancer Targets

Alternative title: Tumor-makrofag interaksjoner - Nye muligheter for identifisering av alternative kreftbehandlinger

Awarded: NOK 3.5 mill.

Cancer is among the most common mortality factors in the western world, with breast cancer being the most frequent in women. Many patients will benefit from conventional therapy, nevertheless, a large subset of patients eventually experiences disease relapse and drug resistance. This is often followed by disease progression into metastatic disease, of which current treatment is inadequate, and in most cases only palliative. Thus, there is an urgent need for more effective therapies in the clinic today, as this could greatly improve the outcome for these patients. Within the tumor, other cell types, like immune cells, are essential alongside the cancer cells in shaping the tumor microenvironment. This project aimed to examine how cancer cells take advantage of immune cells, and especially a subgroup of these cells called macrophages, in order to promote tumor progression and escape cancer targeted treatments. Preliminary studies in the OHSU lab utilizing a spontaneous mouse model of metastatic breast cancer, of which the lab is world leading, revealed certain novel treatment combinations to reduce tumor progression through increased chemotherapy efficacy and diminished pulmonary metastases. Such a model is beneficial for studying cancer, as the spontaneous development of tumors is reflecting the process of cancer developing in humans. Initially, reduced number of tumor promoting macrophages, as well as changes in other immune populations creating a more anti-tumor environment, could be seen as an effect of the different treatment combinations. This is desirable as, as the immune system can be used to specifically target the cancer cells and not other cells in the body. To further elucidate on the mechanisms behind this response, we utilize RNA-sequencing (RNA-seq), generating an overview of the gene expression across tumor samples from the different treatment groups. Together with the already generated flow cytometry/protein data, used for characterizing the immune subpopulations in the tumors, we identified changes in genes and gene expression pathways associated with the different responses to treatment, for both targeted and conventional therapies. Changes were among others linked to genes associated with the myeloid population of immune cells. As some nuances were difficult to identify, single cell RNA-seq (scRNA-seq) was also performed. This allowed us to further elucidate the gene expressional changes in smaller sub-populations of cells. In this way we were able to identify specific pathways changing primarily in certain subpopulations of immune cells associated with response to treatment. Next, we have used available datasets at both institutes in USA and Norway, to confirm relevant changes in novel treatment combinations, but how cancer cells are escaping conventional chemotherapy. Currently validation of mechanisms and immune populations involved in generating response/no response to treatment are under completion. The final analyses will be published in internationally recognized journals for cancer research. These studies do not only give information on novel treatment combinations as alternative to the standard-of-care but will also be important knowledge for the further improvement of targeted therapy in BC patients with few alternatives for treatment in the clinic today.

The project will contribute significantly to the field of immune oncology, in particular the ongoing studies of interactions in the tumor-immune microenvironment (including tumor-or-macrophage interactions). It will also aid in development om novel drugs targeting these interactions. Multiple manuscripts (>3 manuscripts) are now in preparation and will be submitted during 2023. These cover the functional changes after treatment both with novel targeted drugs, as well as with treatments currently used as standard-of-care. The combination of conventional multiparametric flow, for identifying relevant immune sub-populations, with multiple levels of omics-data has been used in order to characterize changes associated with the treatments. Several nodes associated with response to the different treatments has been identified, both on gene and protein level, but also through changes in pathways and cell sub-populations after treatment. These specific results will be communicated through the manuscript in preparation.

Cancer is among the most common mortality factors in the western world. Many patients benefit from conventional therapy, nevertheless, a large subset experiences relapse and develops drug resistance. Eventually many of these patients will progress into metastatic disease, of which treatment is inadequate and in most cases not curative. Thus, there is an urgent clinical need for more effective anti-metastatic therapy. In addition to the cancer cells, tumors consist of distinct stromal cells, like tumor-associated macrophages (TAMs), and the dynamic interactions between these cells are crucial for growth and survival. Such interactions are also essential when cancer cells switch their phenotype to a more aggressive mesenchymal state, promoting metastatic progression and treatment resistance. By characterizing central nodes involved in this process, therapeutic targets with potential impact on clinical management of metastatic disease may be identified. This project aims to use an animal model of metastatic breast cancer, PyMT, to elucidate the bi-directional communication between the cancer cells and TAMs. Preliminary data has shown that targeting pro-tumorigenic TAMs (with Paclitaxel and anti-CSF1R) prior to treatment with immunotherapy (aPD-1), improves survival and reduces tumor growth. We are interested in identifying how addition of aPD-1 impacts the remaining TAMs. Particularly interesting is also the observation that animals treated with the triple combination can be divided into two distinct subgroups, responders and non-responders. In the present project we will elucidate whether the differences in response to treatment is due to differences in the macrophage compartment. Initially through use of bulk RNAseq, to identify large scale changes in the transcriptome of tumor responding and not responding to treatment. By combining this with single cell RNA-sequencing (scRNAseq) we would identify not only broad specter changes in tumors after treatment, but also cell specific changes in macrophages, as well as other distinct immune cell populations. This will allow us to examine how the addition of aPD-1 affect these, and whether specific signatures or targets can be used to identify responders and non-responders. Changes in expression of macrophages would be validated, before potential targets will undergo stringent evaluation in vitro before immune-competent mice will be used to validate the targets/factors. Finally, the clinical relevance of potential targets will be validated utilizing tumor tissue collected from breast cancer patients. We anticipate that through this study novel therapeutic targets/strategies and/or biomarkers to tailor phenotype-based treatment against metastatic cancer will be revealed.

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FRIMEDBIO-Fri prosj.st. med.,helse,biol

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