Q-omics provides the consensus-scored GATB profile across patient tissues and cancer cell-line models. GATB expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, GATB is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, GATB RNA expression shows 17,198 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, THCA, and UVM as cancer lineages where GATB 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 GATB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GATB survival associations across molecular data types. GATB RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GATB RNA expression–survival associations across cancer types. High GATB expression shows unfavorable associations in LUAD, KICH, HNSC and CESC, but favorable associations in KIRP and KIRC. The KIRP 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 KIRP as the clearest survival context for GATB RNA expression.
This table summarizes GATB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 8. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GATB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GATB shows lower tumor expression in THCA, KICH and BRCA and higher tumor expression in LUAD, LIHC and LUSC. The THCA box plot shows higher GATB RNA expression in normal versus tumor tissue (log2 FC = −0.612, t-test p < 0.001).
This table shows molecular features associated with GATB in patient tissues and cancer cell lines. In patient samples, GATB 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, GATB 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 OVARY and UPPER_AERODIGESTIVE_TRACT.
