Q-omics provides the consensus-scored ENDOV profile across patient tissues and cancer cell-line models. ENDOV expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ENDOV is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, ENDOV RNA expression shows 18,715 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KICH as cancer lineages where ENDOV 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 ENDOV — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ENDOV survival associations across molecular data types. ENDOV RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) 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 ENDOV RNA expression–survival associations across cancer types. High ENDOV expression shows unfavorable associations in ACC, COAD, MESO and UCS, but favorable associations in BRCA and LGG. 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 ENDOV RNA expression.
This table summarizes ENDOV 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 1. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ENDOV. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ENDOV shows lower tumor expression in KICH, UCEC and THCA and higher tumor expression in LIHC, CHOL and KIRP. The KICH box plot shows higher ENDOV RNA expression in normal versus tumor tissue (log2 FC = −0.904, t-test p < 0.001).
This table shows molecular features associated with ENDOV in patient tissues and cancer cell lines. In patient samples, ENDOV shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ENDOV RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
