Q-omics provides the consensus-scored E2F5 profile across patient tissues and cancer cell-line models. E2F5 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, E2F5 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, E2F5 protein abundance shows 36,015 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, COAD, and PDAC as cancer lineages where E2F5 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 E2F5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes E2F5 survival associations across molecular data types. E2F5 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible E2F5 RNA expression–survival associations across cancer types. High E2F5 expression shows unfavorable associations in UVM, LIHC, KIRP and KIRC, but favorable associations in SKCM and BLCA. The UVM 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 UVM as the clearest survival context for E2F5 RNA expression.
This table summarizes E2F5 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 8. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for E2F5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. E2F5 shows higher tumor expression in COAD, LIHC, LUAD, STAD, BRCA and UCEC. The COAD box plot shows higher E2F5 RNA expression in tumor versus normal tissue (log2 FC = +1.572, t-test p < 0.001).
This table shows molecular features associated with E2F5 in patient tissues and cancer cell lines. In patient samples, E2F5 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, E2F5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and BLOOD_Lymphoma.
