Q-omics provides the consensus-scored GLOD4 profile across patient tissues and cancer cell-line models. GLOD4 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GLOD4 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, GLOD4 protein abundance shows 22,722 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, KICH, and PDAC as cancer lineages where GLOD4 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 GLOD4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GLOD4 survival associations across molecular data types. GLOD4 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GLOD4 RNA expression–survival associations across cancer types. High GLOD4 expression shows unfavorable associations in UVM, ACC and CHOL, but favorable associations in KIRC, BRCA and SCLC. The KIRC 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 KIRC as the clearest survival context for GLOD4 RNA expression.
This table summarizes GLOD4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GLOD4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GLOD4 shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, BLCA, LUSC and CHOL. The KICH box plot shows higher GLOD4 RNA expression in normal versus tumor tissue (log2 FC = −1.604, t-test p < 0.001).
This table shows molecular features associated with GLOD4 in patient tissues and cancer cell lines. In patient samples, GLOD4 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, GLOD4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
