Q-omics provides the consensus-scored OGN profile across patient tissues and cancer cell-line models. OGN expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, OGN is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, OGN protein abundance shows 32,639 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight BLCA, and PDAC as cancer lineages where OGN 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 OGN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OGN survival associations across molecular data types. OGN RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OGN RNA expression–survival associations across cancer types. High OGN expression shows unfavorable associations in BLCA, KICH, OV and ACC, but favorable associations in LIHC and KIRC. The BLCA 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 BLCA as the clearest survival context for OGN RNA expression.
This table summarizes OGN 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 7. The strongest signals are observed in BLCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for OGN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OGN shows lower tumor expression in BLCA, COAD, LUAD, THCA, KICH and KIRC. The BLCA box plot shows higher OGN RNA expression in normal versus tumor tissue (log2 FC = −5.922, t-test p < 0.001).
This table shows molecular features associated with OGN in patient tissues and cancer cell lines. In patient samples, OGN shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, OGN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BREAST.
