Q-omics provides the consensus-scored WFDC5 profile across patient tissues and cancer cell-line models. WFDC5 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, WFDC5 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, WFDC5 RNA expression shows 10,370 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight OV, KICH, and ESCA as cancer lineages where WFDC5 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 WFDC5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WFDC5 survival associations across molecular data types. WFDC5 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WFDC5 RNA expression–survival associations across cancer types. High WFDC5 expression shows unfavorable associations in OV, KIRC, SKCM and MESO, but favorable associations in KIRP and ESCA. 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 WFDC5 RNA expression.
This table summarizes WFDC5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for WFDC5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WFDC5 shows lower tumor expression in KICH, LUAD and KIRC and higher tumor expression in LUSC, HNSC and KIRP. The KICH box plot shows higher WFDC5 RNA expression in normal versus tumor tissue (log2 FC = −1.207, t-test p < 0.001).
This table shows molecular features associated with WFDC5 in patient tissues and cancer cell lines. In patient samples, WFDC5 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, WFDC5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in CNS and SKIN.
