Q-omics provides the consensus-scored GALE profile across patient tissues and cancer cell-line models. GALE expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, GALE is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, GALE protein abundance shows 27,301 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LGG, KIRC, and LSCC as cancer lineages where GALE 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 GALE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GALE survival associations across molecular data types. GALE RNA expression shows survival associations in the most cancer types (28), followed by mutation status (3) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GALE RNA expression–survival associations across cancer types. High GALE expression shows unfavorable associations in LGG, HNSC, GBM, UCEC and SARC, but favorable associations in COAD. The LGG 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 LGG as the clearest survival context for GALE RNA expression.
This table summarizes GALE 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 12. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for GALE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GALE shows higher tumor expression in KIRC, THCA, KIRP, BLCA, BRCA and LUAD. The KIRC box plot shows higher GALE RNA expression in tumor versus normal tissue (log2 FC = +0.689, t-test p < 0.001).
This table shows molecular features associated with GALE in patient tissues and cancer cell lines. In patient samples, GALE 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, GALE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
