Q-omics provides the consensus-scored OMP profile across patient tissues and cancer cell-line models. OMP expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, OMP is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, OMP RNA expression shows 15,965 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight BRCA, KIRC, and ESCA as cancer lineages where OMP 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 OMP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OMP survival associations across molecular data types. OMP RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible OMP RNA expression–survival associations across cancer types. High OMP expression shows unfavorable associations in LGG, KICH, MESO and THCA, but favorable associations in BRCA and READ. The BRCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .004). Together, the overview and detailed table identify BRCA as the clearest survival context for OMP RNA expression.
This table summarizes OMP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for OMP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OMP shows lower tumor expression in KIRC, HNSC and READ and higher tumor expression in LUAD, PAAD and STAD. The KIRC box plot shows higher OMP RNA expression in normal versus tumor tissue (log2 FC = −0.242, t-test p < 0.001).
This table shows molecular features associated with OMP in patient tissues and cancer cell lines. In patient samples, OMP shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, OMP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BONE.
