Q-omics provides the consensus-scored MYO1E profile across patient tissues and cancer cell-line models. MYO1E expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, MYO1E is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, MYO1E protein abundance shows 23,763 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where MYO1E 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 MYO1E — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MYO1E survival associations across molecular data types. MYO1E RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MYO1E RNA expression–survival associations across cancer types. High MYO1E expression shows unfavorable associations in MESO, LUAD, PAAD, LGG and CESC, but favorable associations in UCEC. The MESO 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 MESO as the clearest survival context for MYO1E RNA expression.
This table summarizes MYO1E 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 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MYO1E. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MYO1E shows lower tumor expression in KICH and higher tumor expression in HNSC, LUAD, LUSC, THCA and STAD. The HNSC box plot shows higher MYO1E RNA expression in tumor versus normal tissue (log2 FC = +0.868, t-test p < 0.001).
This table shows molecular features associated with MYO1E in patient tissues and cancer cell lines. In patient samples, MYO1E shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, MYO1E RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BONE.
