Q-omics provides the consensus-scored WDFY4 profile across patient tissues and cancer cell-line models. WDFY4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, WDFY4 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, WDFY4 protein abundance shows 25,139 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KIRC, and LSCC as cancer lineages where WDFY4 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 WDFY4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WDFY4 survival associations across molecular data types. WDFY4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (12) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WDFY4 RNA expression–survival associations across cancer types. High WDFY4 expression shows unfavorable associations in LGG, but favorable associations in HNSC, SKCM, LUAD, CESC and KIRC. The HNSC 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 HNSC as the clearest survival context for WDFY4 RNA expression.
This table summarizes WDFY4 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for WDFY4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WDFY4 shows lower tumor expression in LUSC, LUAD and COAD and higher tumor expression in KIRC, STAD and BRCA. The KIRC box plot shows higher WDFY4 RNA expression in tumor versus normal tissue (log2 FC = +1.472, t-test p < 0.001).
This table shows molecular features associated with WDFY4 in patient tissues and cancer cell lines. In patient samples, WDFY4 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, WDFY4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Lymphoma.
