Q-omics provides the consensus-scored EPS15 profile across patient tissues and cancer cell-line models. EPS15 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EPS15 is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, EPS15 protein abundance shows 29,612 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, LIHC, and LSCC as cancer lineages where EPS15 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 EPS15 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPS15 survival associations across molecular data types. EPS15 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EPS15 RNA expression–survival associations across cancer types. High EPS15 expression shows unfavorable associations in CESC, LUSC, LIHC and LGG, but favorable associations in KIRC and BRCA. 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 EPS15 RNA expression.
This table summarizes EPS15 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 6. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for EPS15. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPS15 shows lower tumor expression in KICH, THCA, LUSC and LUAD and higher tumor expression in LIHC and HNSC. The LIHC box plot shows higher EPS15 RNA expression in tumor versus normal tissue (log2 FC = +0.612, t-test p < 0.001).
This table shows molecular features associated with EPS15 in patient tissues and cancer cell lines. In patient samples, EPS15 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, EPS15 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
