Abstract
Background
Absent in melanoma 2 (AIM2) is an important developmental regulator for innate immune responses, and recent studies on AIM2 have reported its vital role in cancer development and progression. However, AIM2 in skin cutaneous melanoma (SKCM) tumor immune microenvironment has not been extensively studied.
Methods
We explored the expression and prognostic value of AIM2 at the pan-cancer level based on multiple public databases. We analyzed the SKCM transcriptome sequencing data and clinical information, available on various public databases, using differential analysis, prognostic analysis, machine learning, and various immune infiltration algorithms. We used online visualization databases to explore AIM2 expression in SKCM to determine its prognostic impact. Furthermore, we constructed a risk signature based on AIM2-related genes.
Results
Based on the pan-cancer analysis, AIM2 was found to be an independent prognostic factor for SKCM. AIM2 expression notably differed in SKCM and was associated with an improved survival rate among patients. Increased AIM2 expression promoted the immune response of patients with SKCM, inducing pyroptosis, apoptosis, and necroptosis. In vitro transwell assay and scratch test showed that the knockdown of AIM2 expression increased its invasiveness and metastasis of the SKCM cell line, A875. Knockdown of AIM2 expression revealed decreased expression of ZBP1 and MEFV, the important genes in the PANoptosis complex. Simultaneously, the expression of pyroptosis, apoptosis, and CD8+ T cell marker genes (GSDMD, CASP-8, and CD8A) also decreased. The infiltration levels of various antitumor immune cells positively correlated with AIM2 expression, and the infiltration levels notably differed between patients with high and low levels of AIM2 expression. The Tumor Immune Dysfunction and Exclusion framework analysis revealed that AIM2 expression accurately facilitated the prediction of the efficacy of SKCM immunotherapy. Mechanistic analysis revealed an association between AIM2 overexpression and PANoptosis signaling upregulation, thereby affecting the patterns of chemokines and cytokines in TIME. Furthermore, the prediction and prediction performance of the prognostic model was found to be accurate.
Conclusion
AIM2 is associated with an increased abundance of effector CD8+ T cells, positive responses to immune checkpoint blockade treatment, and improved SKCM prognoses. Therefore, it could be used as a putative enhancer and prognostic biomarker for SKCM treatment.