Q-omics provides the consensus-scored WDFY2 profile across patient tissues and cancer cell-line models. WDFY2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, WDFY2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, WDFY2 RNA expression shows 20,962 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, HNSC, and THYM as cancer lineages where WDFY2 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 WDFY2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WDFY2 survival associations across molecular data types. WDFY2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) 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 WDFY2 RNA expression–survival associations across cancer types. High WDFY2 expression shows unfavorable associations in ACC, HNSC, READ, MESO and KIRP, but favorable associations in SCLC. The ACC 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 ACC as the clearest survival context for WDFY2 RNA expression.
This table summarizes WDFY2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for WDFY2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WDFY2 shows lower tumor expression in KIRP, KIRC, KICH and THCA and higher tumor expression in HNSC and COAD. The HNSC box plot shows higher WDFY2 RNA expression in tumor versus normal tissue (log2 FC = +0.848, t-test p < 0.001).
This table shows molecular features associated with WDFY2 in patient tissues and cancer cell lines. In patient samples, WDFY2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, WDFY2 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 PANCREAS and BLOOD_Leukemia.
