Q-omics provides the consensus-scored OGA profile across patient tissues and cancer cell-line models. OGA expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, OGA is differentially expressed in 6, with the highest sampling consensus in LIHC. Additionally, OGA RNA expression shows 21,552 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where OGA 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 OGA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OGA survival associations across molecular data types. OGA RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OGA RNA expression–survival associations across cancer types. High OGA expression shows unfavorable associations in ACC, OV and HNSC, but favorable associations in UCS, LGG and SKCM. The ACC 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 ACC as the clearest survival context for OGA RNA expression.
This table summarizes OGA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for OGA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OGA shows lower tumor expression in LUSC and higher tumor expression in LIHC, KIRC, HNSC, CHOL and KIRP. The LIHC box plot shows higher OGA RNA expression in tumor versus normal tissue (log2 FC = +0.844, t-test p < 0.001).
This table shows molecular features associated with OGA in patient tissues and cancer cell lines. In patient samples, OGA 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, OGA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
