Q-omics provides the consensus-scored EPHA4 profile across patient tissues and cancer cell-line models. EPHA4 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EPHA4 is differentially expressed in 15, with the highest sampling consensus in KICH. Additionally, EPHA4 protein abundance shows 21,666 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KICH, and GBM as cancer lineages where EPHA4 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 EPHA4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPHA4 survival associations across molecular data types. EPHA4 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (8) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EPHA4 RNA expression–survival associations across cancer types. High EPHA4 expression shows unfavorable associations in OV, UVM and STAD, but favorable associations in KIRC, LIHC and SCLC. 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 EPHA4 RNA expression.
This table summarizes EPHA4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 4. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for EPHA4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPHA4 shows lower tumor expression in KICH, COAD, UCEC and READ and higher tumor expression in BLCA and THCA. The KICH box plot shows higher EPHA4 RNA expression in normal versus tumor tissue (log2 FC = −2.796, t-test p < 0.001).
This table shows molecular features associated with EPHA4 in patient tissues and cancer cell lines. In patient samples, EPHA4 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, EPHA4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
