Q-omics provides the consensus-scored E2F6 profile across patient tissues and cancer cell-line models. E2F6 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, E2F6 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, E2F6 RNA expression shows 20,923 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, HNSC, and ACC as cancer lineages where E2F6 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 E2F6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes E2F6 survival associations across molecular data types. E2F6 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible E2F6 RNA expression–survival associations across cancer types. High E2F6 expression shows unfavorable associations in LIHC, KIRP, ACC, BLCA and LGG, but favorable associations in UCS. The LIHC 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 LIHC as the clearest survival context for E2F6 RNA expression.
This table summarizes E2F6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for E2F6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. E2F6 shows higher tumor expression in HNSC, COAD, KIRC, LIHC, STAD and LUAD. The HNSC box plot shows higher E2F6 RNA expression in tumor versus normal tissue (log2 FC = +0.836, t-test p < 0.001).
This table shows molecular features associated with E2F6 in patient tissues and cancer cell lines. In patient samples, E2F6 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, E2F6 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 BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
