Q-omics provides the consensus-scored MEP1A profile across patient tissues and cancer cell-line models. MEP1A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MEP1A is differentially expressed in 9, with the highest sampling consensus in COAD. Additionally, MEP1A RNA expression shows 11,916 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, COAD, and THYM as cancer lineages where MEP1A 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 MEP1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MEP1A survival associations across molecular data types. MEP1A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 MEP1A RNA expression–survival associations across cancer types. High MEP1A expression shows unfavorable associations in LIHC and UVM, but favorable associations in KIRC, LUAD, CESC and OV. 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 MEP1A RNA expression.
This table summarizes MEP1A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 2. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MEP1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MEP1A shows lower tumor expression in COAD and READ and higher tumor expression in KIRC, HNSC, LIHC and KIRP. The COAD box plot shows higher MEP1A RNA expression in normal versus tumor tissue (log2 FC = −2.979, t-test p < 0.001).
This table shows molecular features associated with MEP1A in patient tissues and cancer cell lines. In patient samples, MEP1A shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, MEP1A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
