Q-omics provides the consensus-scored MYEOV profile across patient tissues and cancer cell-line models. MYEOV expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, MYEOV is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, MYEOV RNA expression shows 15,528 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and COAD as cancer lineages where MYEOV 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 MYEOV — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MYEOV survival associations across molecular data types. MYEOV RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MYEOV RNA expression–survival associations across cancer types. High MYEOV expression shows unfavorable associations in UVM, ACC, PAAD, LUAD, LUSC and MESO. The UVM 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 UVM as the clearest survival context for MYEOV RNA expression.
This table summarizes MYEOV tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for MYEOV. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MYEOV shows higher tumor expression in COAD, KIRC, THCA, LUAD, KIRP and LUSC. The COAD box plot shows higher MYEOV RNA expression in tumor versus normal tissue (log2 FC = +2.862, t-test p < 0.001).
This table shows molecular features associated with MYEOV in patient tissues and cancer cell lines. In patient samples, MYEOV 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, MYEOV 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 LUNG_SCLC and BONE.
