Q-omics provides the consensus-scored EPGN profile across patient tissues and cancer cell-line models. EPGN expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, EPGN is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, EPGN RNA expression shows 15,592 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight LUAD, KIRC, and HNSC as cancer lineages where EPGN 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 EPGN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EPGN survival associations across molecular data types. EPGN RNA expression shows survival associations in the most cancer types (18), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EPGN RNA expression–survival associations across cancer types. High EPGN expression shows unfavorable associations in LUAD, KIRC, SKCM, UCEC, KIRP and UVM. The LUAD 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 LUAD as the clearest survival context for EPGN RNA expression.
This table summarizes EPGN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for EPGN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EPGN shows lower tumor expression in KIRC, LUAD, KICH and PRAD and higher tumor expression in READ and BRCA. The KIRC box plot shows higher EPGN RNA expression in normal versus tumor tissue (log2 FC = −0.611, t-test p < 0.001).
This table shows molecular features associated with EPGN in patient tissues and cancer cell lines. In patient samples, EPGN 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, EPGN 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 URINARY_TRACT and SKIN.
