Q-omics provides the consensus-scored WNT4 profile across patient tissues and cancer cell-line models. WNT4 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, WNT4 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, WNT4 RNA expression shows 16,078 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, KIRC, and TGCT as cancer lineages where WNT4 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 WNT4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WNT4 survival associations across molecular data types. WNT4 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3) 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 WNT4 RNA expression–survival associations across cancer types. High WNT4 expression shows unfavorable associations in KIRP and ACC, but favorable associations in SCLC, PAAD, UCS and SARC. The KIRP 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 KIRP as the clearest survival context for WNT4 RNA expression.
This table summarizes WNT4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for WNT4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WNT4 shows lower tumor expression in KIRC, THCA, UCEC and KICH and higher tumor expression in HNSC and LIHC. The KIRC box plot shows higher WNT4 RNA expression in normal versus tumor tissue (log2 FC = −1.085, t-test p < 0.001).
This table shows molecular features associated with WNT4 in patient tissues and cancer cell lines. In patient samples, WNT4 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, WNT4 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 SOFT_TISSUE and OVARY.
