Investigating the tumor-immune microenvironment through extracellular vesicles from frozen patient biopsies and 3D cultures

Abstract

Melanomas are highly immunogenic tumors that have been shown to activate the immune response. Nonetheless, a significant portion of melanoma cases are either unresponsive to immunotherapy or relapsed due to acquired resistance. During melanomagenesis, melanoma and immune cells undergo immunomodulatory mechanisms that aid in immune resistance and evasion. The crosstalk within melanoma microenvironment is facilitated through the secretion of soluble factors, growth factors, cytokines, and chemokines. In addition, the release and uptake of secretory vesicles known as extracellular vesicles (EVs) play a key role in shaping the tumor microenvironment (TME). Melanoma-derived EVs have been implicated in immune suppression and escape, promoting tumor progression. In the context of cancer patients, EVs are usually isolated from biofluids such as serum, urine, and saliva. Nonetheless, this approach neglects the fact that biofluid-derived EVs reflect not only the tumor, but also include contributions from different organs and cell types. For that, isolating EVs from tissue samples allows for studying different cell populations resident at the tumor site, such as tumor-infiltrating lymphocytes and their secreted EVs, which play a central anti-tumor role. Herein, we outline the first instance of a method for EV isolation from frozen tissue samples at high purity and sensitivity that can be easily reproduced without the need for complicated isolation methods. Our method of processing the tissue not only circumvents the need for hard-to-acquire freshly isolated tissue samples, but also preserves EV surface proteins which allows for multiplex surface markers profiling. Tissue-derived EVs provide insight into the physiological role of EVs enrichment at tumor sites, which can be overlooked when studying circulating EVs coming from different sources. Tissue-derived EVs could be further characterized in terms of their genomics and proteomics to identify possible mechanisms for regulating the TME. Additionally, identified markers could be correlated to overall patient survival and disease progression for prognostic purposes.