Q-omics provides the consensus-scored GLMN profile across patient tissues and cancer cell-line models. GLMN expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, GLMN is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, GLMN RNA expression shows 20,301 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, KIRC, and ACC as cancer lineages where GLMN 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 GLMN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GLMN survival associations across molecular data types. GLMN RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) 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 GLMN RNA expression–survival associations across cancer types. High GLMN expression shows unfavorable associations in LIHC, ACC, KIRP, LGG and UVM, but favorable associations in COAD. The LIHC 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 LIHC as the clearest survival context for GLMN RNA expression.
This table summarizes GLMN 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GLMN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GLMN shows higher tumor expression in KIRC, LIHC, LUAD, BLCA, HNSC and LUSC. The KIRC box plot shows higher GLMN RNA expression in tumor versus normal tissue (log2 FC = +0.459, t-test p < 0.001).
This table shows molecular features associated with GLMN in patient tissues and cancer cell lines. In patient samples, GLMN shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, GLMN 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 LARGE_INTESTINE and BREAST.
