Q-omics provides the consensus-scored EPS8 profile across patient tissues and cancer cell-line models. EPS8 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, EPS8 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, EPS8 protein abundance shows 20,487 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRC, THCA, and HNSC as cancer lineages where EPS8 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 EPS8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPS8 survival associations across molecular data types. EPS8 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) 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 EPS8 RNA expression–survival associations across cancer types. High EPS8 expression shows unfavorable associations in PAAD, UVM, LGG and MESO, but favorable associations in KIRC and THCA. 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 EPS8 RNA expression.
This table summarizes EPS8 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 7. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for EPS8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPS8 shows lower tumor expression in BRCA, LUSC and READ and higher tumor expression in THCA, KIRC and STAD. The THCA box plot shows higher EPS8 RNA expression in tumor versus normal tissue (log2 FC = +1.514, t-test p < 0.001).
This table shows molecular features associated with EPS8 in patient tissues and cancer cell lines. In patient samples, EPS8 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, EPS8 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 SKIN and SOFT_TISSUE.
