Q-omics provides the consensus-scored EPN2 profile across patient tissues and cancer cell-line models. EPN2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, EPN2 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, EPN2 protein abundance shows 21,224 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight BLCA, KICH, and CCRCC as cancer lineages where EPN2 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 EPN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPN2 survival associations across molecular data types. EPN2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 EPN2 RNA expression–survival associations across cancer types. High EPN2 expression shows unfavorable associations in BLCA, ACC, MESO and LIHC, but favorable associations in KIRC and ESCA. The BLCA 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 BLCA as the clearest survival context for EPN2 RNA expression.
This table summarizes EPN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 9. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for EPN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPN2 shows lower tumor expression in KICH, LUAD and UCEC and higher tumor expression in LIHC, CHOL and HNSC. The KICH box plot shows higher EPN2 RNA expression in normal versus tumor tissue (log2 FC = −1.659, t-test p < 0.001).
This table shows molecular features associated with EPN2 in patient tissues and cancer cell lines. In patient samples, EPN2 shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, EPN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LIVER and UPPER_AERODIGESTIVE_TRACT.
