Q-omics provides the consensus-scored EPX profile across patient tissues and cancer cell-line models. EPX expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, EPX is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, EPX RNA expression shows 18,457 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, KIRC, and THYM as cancer lineages where EPX 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 EPX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPX survival associations across molecular data types. EPX RNA expression shows survival associations in the most cancer types (21), followed by mutation status (6) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EPX RNA expression–survival associations across cancer types. High EPX expression shows unfavorable associations in DLBC, but favorable associations in HNSC, PAAD, UVM, ESCA and SCLC. The HNSC 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 HNSC as the clearest survival context for EPX RNA expression.
This table summarizes EPX tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EPX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPX shows lower tumor expression in KIRC, LUAD, KICH, THCA and UCEC and higher tumor expression in CHOL. The KIRC box plot shows higher EPX RNA expression in normal versus tumor tissue (log2 FC = −0.517, t-test p < 0.001).
This table shows molecular features associated with EPX in patient tissues and cancer cell lines. In patient samples, EPX 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, EPX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and LUNG_NSCLC_LUAD.
