Q-omics provides the consensus-scored WNT6 profile across patient tissues and cancer cell-line models. WNT6 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, WNT6 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, WNT6 RNA expression shows 14,420 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, KICH, and TGCT as cancer lineages where WNT6 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 WNT6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WNT6 survival associations across molecular data types. WNT6 RNA expression shows survival associations in the most cancer types (21), 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 WNT6 RNA expression–survival associations across cancer types. High WNT6 expression shows unfavorable associations in KIRP, ACC, LAML and LGG, but favorable associations in ESCA and THYM. 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 WNT6 RNA expression.
This table summarizes WNT6 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 4. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for WNT6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WNT6 shows lower tumor expression in KICH, KIRP and BRCA and higher tumor expression in LUAD, LIHC and THCA. The KICH box plot shows higher WNT6 RNA expression in normal versus tumor tissue (log2 FC = −0.782, t-test p < 0.001).
This table shows molecular features associated with WNT6 in patient tissues and cancer cell lines. In patient samples, WNT6 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, WNT6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
