Q-omics provides the consensus-scored EVPL profile across patient tissues and cancer cell-line models. EVPL expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, EVPL is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, EVPL protein abundance shows 19,689 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight SKCM, COAD, and LUAD as cancer lineages where EVPL 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 EVPL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EVPL survival associations across molecular data types. EVPL RNA expression shows survival associations in the most cancer types (20), followed by mutation status (8) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EVPL RNA expression–survival associations across cancer types. High EVPL expression shows unfavorable associations in SKCM, ACC, PAAD, KIRC and MESO, but favorable associations in LUSC. The SKCM 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 SKCM as the clearest survival context for EVPL RNA expression.
This table summarizes EVPL 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EVPL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EVPL shows lower tumor expression in KIRC and KICH and higher tumor expression in COAD, BLCA, THCA and BRCA. The COAD box plot shows higher EVPL RNA expression in tumor versus normal tissue (log2 FC = +1.874, t-test p < 0.001).
This table shows molecular features associated with EVPL in patient tissues and cancer cell lines. In patient samples, EVPL shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, EVPL 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 BLOOD_Lymphoma and LUNG_NSCLC_LUAD.
