Q-omics provides the consensus-scored EPHX4 profile across patient tissues and cancer cell-line models. EPHX4 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, EPHX4 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, EPHX4 RNA expression shows 15,135 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, COAD, and UVM as cancer lineages where EPHX4 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 EPHX4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPHX4 survival associations across molecular data types. EPHX4 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) 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 EPHX4 RNA expression–survival associations across cancer types. High EPHX4 expression shows unfavorable associations in KIRP, UCEC, PAAD, MESO, LIHC and UCS. The KIRP 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 KIRP as the clearest survival context for EPHX4 RNA expression.
This table summarizes EPHX4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for EPHX4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPHX4 shows higher tumor expression in COAD, HNSC, LUAD, THCA, KIRC and READ. The COAD box plot shows higher EPHX4 RNA expression in tumor versus normal tissue (log2 FC = +4.024, t-test p < 0.001).
This table shows molecular features associated with EPHX4 in patient tissues and cancer cell lines. In patient samples, EPHX4 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, EPHX4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and STOMACH.
