Q-omics provides the consensus-scored GLUL profile across patient tissues and cancer cell-line models. GLUL expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, GLUL is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, GLUL RNA expression shows 18,168 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, THCA, and UVM as cancer lineages where GLUL 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 GLUL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GLUL survival associations across molecular data types. GLUL RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) 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 GLUL RNA expression–survival associations across cancer types. High GLUL expression shows unfavorable associations in ACC, KICH and SCLC, but favorable associations in BRCA, COAD and SARC. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify ACC as the clearest survival context for GLUL RNA expression.
This table summarizes GLUL 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 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GLUL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GLUL shows lower tumor expression in THCA, KICH, HNSC and STAD and higher tumor expression in KIRC and LIHC. The THCA box plot shows higher GLUL RNA expression in normal versus tumor tissue (log2 FC = −1.268, t-test p < 0.001).
This table shows molecular features associated with GLUL in patient tissues and cancer cell lines. In patient samples, GLUL shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, GLUL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
