To further validate the clinical significance of our findings, we conducted a pan-MAGEA analysis using the KM plotter and TIMER2.0 databases, which includes data from various cancers, summing the expression of MAGEA2, MAGEA3, and MAGEA10. Here, MAGEA3 is linked to cancer.