Q-omics provides the consensus-scored GBA profile across patient tissues and cancer cell-line models. GBA expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, GBA is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, GBA RNA expression shows 18,666 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, BLCA, and ACC as cancer lineages where GBA 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 GBA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GBA survival associations across molecular data types. GBA RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GBA RNA expression–survival associations across cancer types. High GBA expression shows unfavorable associations in UVM, LIHC, BLCA, KIRP, KICH and ACC. 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 GBA RNA expression.
This table summarizes GBA 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 6. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GBA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GBA shows lower tumor expression in COAD and THCA and higher tumor expression in BLCA, KIRC, HNSC and LIHC. The BLCA box plot shows higher GBA RNA expression in tumor versus normal tissue (log2 FC = +1.040, t-test p < 0.001).
This table shows molecular features associated with GBA in patient tissues and cancer cell lines. In patient samples, GBA 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, GBA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BONE.
