Q-omics provides the consensus-scored WIF1 profile across patient tissues and cancer cell-line models. WIF1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, WIF1 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, WIF1 RNA expression shows 13,980 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCEC, KIRC, and GBM as cancer lineages where WIF1 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 WIF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WIF1 survival associations across molecular data types. WIF1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WIF1 RNA expression–survival associations across cancer types. High WIF1 expression shows unfavorable associations in KIRC and HNSC, but favorable associations in UCEC, BRCA, COAD and MESO. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify UCEC as the clearest survival context for WIF1 RNA expression.
This table summarizes WIF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for WIF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WIF1 shows lower tumor expression in KIRC, LUAD, HNSC, LUSC, STAD and BRCA. The KIRC box plot shows higher WIF1 RNA expression in normal versus tumor tissue (log2 FC = −0.483, t-test p < 0.001).
This table shows molecular features associated with WIF1 in patient tissues and cancer cell lines. In patient samples, WIF1 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, WIF1 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 KIDNEY and LUNG_NSCLC_LUAD.
