Q-omics provides the consensus-scored MRO profile across patient tissues and cancer cell-line models. MRO expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, MRO is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, MRO RNA expression shows 16,478 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight BLCA, KIRC, and UVM as cancer lineages where MRO 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 MRO — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MRO survival associations across molecular data types. MRO RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MRO RNA expression–survival associations across cancer types. High MRO expression shows unfavorable associations in BLCA, STAD, BRCA and LUAD, but favorable associations in KIRC and LGG. 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 MRO RNA expression.
This table summarizes MRO tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MRO. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MRO shows lower tumor expression in KIRC, THCA, KIRP, KICH, LIHC and BRCA. The KIRC box plot shows higher MRO RNA expression in normal versus tumor tissue (log2 FC = −1.829, t-test p < 0.001).
This table shows molecular features associated with MRO in patient tissues and cancer cell lines. In patient samples, MRO shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, MRO RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BONE.
