Q-omics provides the consensus-scored GART profile across patient tissues and cancer cell-line models. GART expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, GART is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, GART protein abundance shows 26,986 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, BLCA, and LSCC as cancer lineages where GART 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 GART — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GART survival associations across molecular data types. GART RNA expression shows survival associations in the most cancer types (24), 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 GART RNA expression–survival associations across cancer types. High GART expression shows unfavorable associations in UVM, ACC, LIHC, CESC and PAAD, but favorable associations in READ. The UVM 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 UVM as the clearest survival context for GART RNA expression.
This table summarizes GART tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 7. The strongest signals are observed in LUAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GART. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GART shows higher tumor expression in BLCA, LUAD, COAD, HNSC, STAD and LIHC. The BLCA box plot shows higher GART RNA expression in tumor versus normal tissue (log2 FC = +1.448, t-test p < 0.001).
This table shows molecular features associated with GART in patient tissues and cancer cell lines. In patient samples, GART shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, GART RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BONE and CNS.
