Pro- and Antitumorigenic Capacity of Immunoproteasomes in Shaping the Tumor Microenvironment.
Hanna LeisterMaik LuuDaniel StaudenrausAleksandra Lopez KrolHans-Joachim MollenkopfArjun SharmaNils SchmererLeon N SchulteWilhelm BertramsBernd SchmeckMarkus BosmannUlrich SteinhoffAlexander VisekrunaPublished in: Cancer immunology research (2021)
Apart from the constitutive proteasome, the immunoproteasome that comprises the three proteolytic subunits LMP2, MECL-1, and LMP7 is expressed in most immune cells. In this study, we describe opposing roles for immunoproteasomes in regulating the tumor microenvironment (TME). During chronic inflammation, immunoproteasomes modulated the expression of protumorigenic cytokines and chemokines and enhanced infiltration of innate immune cells, thus triggering the onset of colitis-associated carcinogenesis (CAC) in wild-type mice. Consequently, immunoproteasome-deficient animals (LMP2/MECL-1/LMP7-null mice) were almost completely resistant to CAC development. In patients with ulcerative colitis with high risk for CAC, immunoproteasome-induced protumorigenic mediators were upregulated. In melanoma tumors, the role of immunoproteasomes is relatively unknown. We found that high expression of immunoproteasomes in human melanoma was associated with better prognosis. Similarly, our data revealed that the immunoproteasome has antitumorigenic activity in a mouse model of melanoma. The antitumor immunity against melanoma was compromised in immunoproteasome-deficient mice because of the impaired activity of CD8+ CTLs, CD4+ Th1 cells, and antigen-presenting cells. These findings show that immunoproteasomes may exert opposing roles with either pro- or antitumoral properties in a context-dependent manner.
Keyphrases
- wild type
- epstein barr virus
- induced apoptosis
- ulcerative colitis
- poor prognosis
- mouse model
- skin cancer
- cell cycle arrest
- endothelial cells
- immune response
- high fat diet induced
- basal cell carcinoma
- anti inflammatory
- signaling pathway
- adipose tissue
- type diabetes
- high glucose
- machine learning
- electronic health record
- metabolic syndrome
- diabetic rats
- single cell
- data analysis
- big data
- induced pluripotent stem cells
- deep learning
- nk cells