Q-omics provides the consensus-scored WNT9A profile across patient tissues and cancer cell-line models. WNT9A expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, WNT9A is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, WNT9A RNA expression shows 18,024 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight OV, COAD, and THYM as cancer lineages where WNT9A 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 WNT9A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WNT9A survival associations across molecular data types. WNT9A RNA expression shows survival associations in the most cancer types (21), followed by mutation status (8) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WNT9A RNA expression–survival associations across cancer types. High WNT9A expression shows unfavorable associations in OV, BLCA, UVM, BRCA and DLBC, but favorable associations in SKCM. The OV 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 OV as the clearest survival context for WNT9A RNA expression.
This table summarizes WNT9A 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 COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for WNT9A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WNT9A shows lower tumor expression in COAD, BLCA, LUAD, THCA and LUSC and higher tumor expression in HNSC. The COAD box plot shows higher WNT9A RNA expression in normal versus tumor tissue (log2 FC = −1.165, t-test p < 0.001).
This table shows molecular features associated with WNT9A in patient tissues and cancer cell lines. In patient samples, WNT9A shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, WNT9A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
