Q-omics provides the consensus-scored MME profile across patient tissues and cancer cell-line models. MME expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, MME is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, MME protein abundance shows 17,835 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight LUSC, KIRP, and BRCA as cancer lineages where MME 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 MME — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MME survival associations across molecular data types. MME RNA expression shows survival associations in the most cancer types (27), followed by mutation status (7) 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 MME RNA expression–survival associations across cancer types. High MME expression shows unfavorable associations in LUSC, CESC, MESO and BLCA, but favorable associations in LGG and KIRC. The LUSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify LUSC as the clearest survival context for MME RNA expression.
This table summarizes MME tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MME. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MME shows lower tumor expression in KIRP, LUAD and BRCA and higher tumor expression in HNSC, BLCA and COAD. The KIRP box plot shows higher MME RNA expression in normal versus tumor tissue (log2 FC = −2.981, t-test p < 0.001).
This table shows molecular features associated with MME in patient tissues and cancer cell lines. In patient samples, MME shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, MME RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BONE.
