Q-omics provides the consensus-scored GMDS profile across patient tissues and cancer cell-line models. GMDS expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, GMDS is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, GMDS protein abundance shows 26,764 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where GMDS 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 GMDS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GMDS survival associations across molecular data types. GMDS RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GMDS RNA expression–survival associations across cancer types. High GMDS expression shows unfavorable associations in ACC, KICH and LIHC, but favorable associations in READ, UCEC and UVM. The ACC 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 ACC as the clearest survival context for GMDS RNA expression.
This table summarizes GMDS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 11. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GMDS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GMDS shows lower tumor expression in HNSC, KICH and KIRC and higher tumor expression in LUAD, LIHC and COAD. The HNSC box plot shows higher GMDS RNA expression in normal versus tumor tissue (log2 FC = −1.181, t-test p < 0.001).
This table shows molecular features associated with GMDS in patient tissues and cancer cell lines. In patient samples, GMDS shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, GMDS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
