Q-omics provides the consensus-scored WAPL profile across patient tissues and cancer cell-line models. WAPL expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, WAPL is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, WAPL protein abundance shows 22,909 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, THCA, and BRCA as cancer lineages where WAPL 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 WAPL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WAPL survival associations across molecular data types. WAPL RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WAPL RNA expression–survival associations across cancer types. High WAPL expression shows unfavorable associations in ACC, but favorable associations in KIRC, SCLC, UCS, THYM and SKCM. The KIRC 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 KIRC as the clearest survival context for WAPL RNA expression.
This table summarizes WAPL 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 7. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for WAPL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WAPL shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, STAD and COAD. The THCA box plot shows higher WAPL RNA expression in normal versus tumor tissue (log2 FC = −0.586, t-test p < 0.001).
This table shows molecular features associated with WAPL in patient tissues and cancer cell lines. In patient samples, WAPL shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, WAPL 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 BONE and BLOOD_Leukemia.
