Research Paper Volume 16, Issue 4 pp 3989—4013
Unlocking the potential of senescence-related gene signature as a diagnostic and prognostic biomarker in sepsis: insights from meta-analyses, single-cell RNA sequencing, and in vitro experiments
Figure 4. Unsupervised clustering based on TGFBI and MAD1L1 expression. (A) The consensus clustering algorithm divided 802 samples in the training cohort into two subgroups, C1 and C2. (B) PCA was performed to validate the robustness of the clustering. (C) The expression levels of TGFBI (left) and MAD1L1 (right) were compared between C1 and C2 subgroups. (D) The clustering was associated with sepsis characteristics. (E) Subjects in the C2 subgroup exhibited worse prognoses than those in C1 subgroup. (F) The clustering was associated with cellular senescence levels. (G) Signaling pathways enriched in C1 and C2 samples were identified. Abbreviations: PCA, principal component analysis; C1, cluster 1; C2, cluster 2; ***P < 0.001.