Q-omics provides the consensus-scored WFDC2 profile across patient tissues and cancer cell-line models. WFDC2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, WFDC2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, WFDC2 protein abundance shows 15,566 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight UVM, KIRC, and LUAD as cancer lineages where WFDC2 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 WFDC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WFDC2 survival associations across molecular data types. WFDC2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WFDC2 RNA expression–survival associations across cancer types. High WFDC2 expression shows unfavorable associations in LGG and GBM, but favorable associations in UVM, MESO, BLCA and CESC. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify UVM as the clearest survival context for WFDC2 RNA expression.
This table summarizes WFDC2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for WFDC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WFDC2 shows lower tumor expression in KIRC, KICH, HNSC, COAD and LUSC and higher tumor expression in UCEC. The KIRC box plot shows higher WFDC2 RNA expression in normal versus tumor tissue (log2 FC = −3.346, t-test p < 0.001).
This table shows molecular features associated with WFDC2 in patient tissues and cancer cell lines. In patient samples, WFDC2 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, WFDC2 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 BLOOD_Leukemia and LUNG_SCLC.
