Q-omics provides the consensus-scored GANAB profile across patient tissues and cancer cell-line models. GANAB expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, GANAB is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, GANAB protein abundance shows 23,812 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where GANAB 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 GANAB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GANAB survival associations across molecular data types. GANAB RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) 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 GANAB RNA expression–survival associations across cancer types. High GANAB expression shows unfavorable associations in MESO, ACC, BLCA, KICH, CESC and LGG. The MESO 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 MESO as the clearest survival context for GANAB RNA expression.
This table summarizes GANAB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GANAB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GANAB shows higher tumor expression in HNSC, BLCA, KIRC, STAD, LUSC and LIHC. The HNSC box plot shows higher GANAB RNA expression in tumor versus normal tissue (log2 FC = +1.625, t-test p < 0.001).
This table shows molecular features associated with GANAB in patient tissues and cancer cell lines. In patient samples, GANAB shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, GANAB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Lymphoma.
