Q-omics provides the consensus-scored GMIP profile across patient tissues and cancer cell-line models. GMIP expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, GMIP is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, GMIP protein abundance shows 34,390 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where GMIP 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 GMIP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GMIP survival associations across molecular data types. GMIP RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GMIP RNA expression–survival associations across cancer types. High GMIP expression shows unfavorable associations in ACC and UVM, but favorable associations in HNSC, SCLC, BLCA and LUAD. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for GMIP RNA expression.
This table summarizes GMIP 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 KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GMIP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GMIP shows higher tumor expression in KIRC, HNSC, KIRP, STAD, BLCA and UCEC. The KIRC box plot shows higher GMIP RNA expression in tumor versus normal tissue (log2 FC = +1.655, t-test p < 0.001).
This table shows molecular features associated with GMIP in patient tissues and cancer cell lines. In patient samples, GMIP 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, GMIP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and UPPER_AERODIGESTIVE_TRACT.
