Q-omics provides the consensus-scored ETF1 profile across patient tissues and cancer cell-line models. ETF1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ETF1 is differentially expressed in 11, with the highest sampling consensus in LUAD. Additionally, ETF1 protein abundance shows 30,137 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, LUAD, and GBM as cancer lineages where ETF1 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 ETF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ETF1 survival associations across molecular data types. ETF1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (10) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ETF1 RNA expression–survival associations across cancer types. High ETF1 expression shows unfavorable associations in HNSC, ACC, LIHC and KIRP, but favorable associations in KIRC and READ. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for ETF1 RNA expression.
This table summarizes ETF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 12. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ETF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ETF1 shows lower tumor expression in LUAD, THCA, BLCA and KICH and higher tumor expression in LIHC and COAD. The LUAD box plot shows higher ETF1 RNA expression in normal versus tumor tissue (log2 FC = −0.622, t-test p < 0.001).
This table shows molecular features associated with ETF1 in patient tissues and cancer cell lines. In patient samples, ETF1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ETF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Lymphoma.
