Q-omics provides the consensus-scored MYL10 profile across patient tissues and cancer cell-line models. MYL10 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, MYL10 is differentially expressed in 7, with the highest sampling consensus in BLCA. Additionally, MYL10 RNA expression shows 8,404 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight SCLC, BLCA, and TGCT as cancer lineages where MYL10 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 MYL10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MYL10 survival associations across molecular data types. MYL10 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) 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 MYL10 RNA expression–survival associations across cancer types. High MYL10 expression shows unfavorable associations in COAD, KICH and LUAD, but favorable associations in SCLC, CHOL and UCEC. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SCLC as the clearest survival context for MYL10 RNA expression.
This table summarizes MYL10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 2. The strongest signals are observed in BLCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for MYL10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MYL10 shows lower tumor expression in BLCA and higher tumor expression in CHOL, THCA, BRCA, COAD and KIRP. The BLCA box plot shows higher MYL10 RNA expression in normal versus tumor tissue (log2 FC = −0.404, t-test p < 0.001).
This table shows molecular features associated with MYL10 in patient tissues and cancer cell lines. In patient samples, MYL10 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, MYL10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SKIN.
