Q-omics provides the consensus-scored MEF2C profile across patient tissues and cancer cell-line models. MEF2C expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MEF2C is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, MEF2C RNA expression shows 29,509 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, BLCA, and LSCC as cancer lineages where MEF2C 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 MEF2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MEF2C survival associations across molecular data types. MEF2C RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MEF2C RNA expression–survival associations across cancer types. High MEF2C expression shows unfavorable associations in BLCA, but favorable associations in KIRC, LUAD, UCS, HNSC and CHOL. The KIRC 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 KIRC as the clearest survival context for MEF2C RNA expression.
This table summarizes MEF2C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for MEF2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MEF2C shows lower tumor expression in BLCA, COAD, KICH, LUSC and THCA and higher tumor expression in KIRC. The BLCA box plot shows higher MEF2C RNA expression in normal versus tumor tissue (log2 FC = −2.340, t-test p < 0.001).
This table shows molecular features associated with MEF2C in patient tissues and cancer cell lines. In patient samples, MEF2C shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, MEF2C 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 BLOOD_Leukemia.
