Q-omics provides the consensus-scored EPS8L1 profile across patient tissues and cancer cell-line models. EPS8L1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EPS8L1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, EPS8L1 protein abundance shows 16,656 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, KIRC, and HNSC as cancer lineages where EPS8L1 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 EPS8L1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPS8L1 survival associations across molecular data types. EPS8L1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) 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 EPS8L1 RNA expression–survival associations across cancer types. High EPS8L1 expression shows unfavorable associations in ACC, SKCM, KIRC and LGG, but favorable associations in MESO and STAD. The ACC 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 ACC as the clearest survival context for EPS8L1 RNA expression.
This table summarizes EPS8L1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for EPS8L1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPS8L1 shows lower tumor expression in KIRC, HNSC and KICH and higher tumor expression in COAD, LUAD and BRCA. The KIRC box plot shows higher EPS8L1 RNA expression in normal versus tumor tissue (log2 FC = −2.206, t-test p < 0.001).
This table shows molecular features associated with EPS8L1 in patient tissues and cancer cell lines. In patient samples, EPS8L1 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, EPS8L1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BONE.
