Q-omics provides the consensus-scored WAC profile across patient tissues and cancer cell-line models. WAC expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, WAC is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, WAC protein abundance shows 22,125 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, LIHC, and PDAC as cancer lineages where WAC 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 WAC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WAC survival associations across molecular data types. WAC RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WAC RNA expression–survival associations across cancer types. High WAC expression shows unfavorable associations in ACC, KIRP, LIHC and CESC, but favorable associations in KIRC and LGG. 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 WAC RNA expression.
This table summarizes WAC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 8. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for WAC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WAC shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, HNSC, CHOL and ESCA. The LIHC box plot shows higher WAC RNA expression in tumor versus normal tissue (log2 FC = +0.878, t-test p < 0.001).
This table shows molecular features associated with WAC in patient tissues and cancer cell lines. In patient samples, WAC shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, WAC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
