Q-omics provides the consensus-scored GMPS profile across patient tissues and cancer cell-line models. GMPS expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, GMPS is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, GMPS protein abundance shows 30,905 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight MESO, HNSC, and LSCC as cancer lineages where GMPS 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 GMPS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GMPS survival associations across molecular data types. GMPS RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GMPS RNA expression–survival associations across cancer types. High GMPS expression shows unfavorable associations in MESO, ACC, LIHC, UCEC, PAAD and KICH. The MESO 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 MESO as the clearest survival context for GMPS RNA expression.
This table summarizes GMPS tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for GMPS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GMPS shows higher tumor expression in HNSC, BLCA, COAD, LUSC, LIHC and LUAD. The HNSC box plot shows higher GMPS RNA expression in tumor versus normal tissue (log2 FC = +1.624, t-test p < 0.001).
This table shows molecular features associated with GMPS in patient tissues and cancer cell lines. In patient samples, GMPS shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, GMPS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
