Q-omics provides the consensus-scored WNT2B profile across patient tissues and cancer cell-line models. WNT2B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, WNT2B is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, WNT2B RNA expression shows 20,653 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, HNSC, and UVM as cancer lineages where WNT2B 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 WNT2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WNT2B survival associations across molecular data types. WNT2B RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) 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 WNT2B RNA expression–survival associations across cancer types. High WNT2B expression shows unfavorable associations in ACC and LGG, but favorable associations in HNSC, LUSC, ESCA and THYM. The ACC 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 ACC as the clearest survival context for WNT2B RNA expression.
This table summarizes WNT2B 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 4. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for WNT2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WNT2B shows lower tumor expression in BLCA, COAD, LUAD, THCA and UCEC and higher tumor expression in HNSC. The HNSC box plot shows higher WNT2B RNA expression in tumor versus normal tissue (log2 FC = +1.210, t-test p < 0.001).
This table shows molecular features associated with WNT2B in patient tissues and cancer cell lines. In patient samples, WNT2B shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, WNT2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
