In this work, we developed HDMAX2-surv, a novel framework for high-dimensional mediation analysis specifically adapted to censored survival data. Our approach integrates computational immune deconvolution with causal discovery and serial mediation analysis, addressing a critical methodological gap in understanding how molecular intermediates shape clinical outcomes.