Q-omics provides the consensus-scored WNT2 profile across patient tissues and cancer cell-line models. WNT2 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, WNT2 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, WNT2 RNA expression shows 14,900 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UCEC, COAD, and LSCC as cancer lineages where WNT2 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 WNT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WNT2 survival associations across molecular data types. WNT2 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (6) 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 WNT2 RNA expression–survival associations across cancer types. High WNT2 expression shows unfavorable associations in UVM, but favorable associations in UCEC, COAD, LUAD, DLBC and THYM. 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 WNT2 RNA expression.
This table summarizes WNT2 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 3. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for WNT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WNT2 shows lower tumor expression in KIRC and LUSC and higher tumor expression in COAD, HNSC, BLCA and STAD. The COAD box plot shows higher WNT2 RNA expression in tumor versus normal tissue (log2 FC = +3.288, t-test p < 0.001).
This table shows molecular features associated with WNT2 in patient tissues and cancer cell lines. In patient samples, WNT2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, WNT2 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 UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
