Q-omics provides the consensus-scored GSDME profile across patient tissues and cancer cell-line models. GSDME expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, GSDME is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, GSDME protein abundance shows 28,512 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight STAD, and HNSC as cancer lineages where GSDME shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for GSDME — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GSDME survival associations across molecular data types. GSDME RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GSDME RNA expression–survival associations across cancer types. High GSDME expression shows unfavorable associations in STAD, LIHC and HNSC, but favorable associations in ACC, KIRP and ESCA. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify STAD as the clearest survival context for GSDME RNA expression.
This table summarizes GSDME tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GSDME. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GSDME shows lower tumor expression in KICH, UCEC and BRCA and higher tumor expression in HNSC, LUAD and KIRC. The HNSC box plot shows higher GSDME RNA expression in tumor versus normal tissue (log2 FC = +3.081, t-test p < 0.001).
This table shows molecular features associated with GSDME in patient tissues and cancer cell lines. In patient samples, GSDME shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, GSDME RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BONE.
