Q-omics provides the consensus-scored WFIKKN2 profile across patient tissues and cancer cell-line models. WFIKKN2 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, WFIKKN2 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, WFIKKN2 RNA expression shows 11,791 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, BLCA, and TGCT as cancer lineages where WFIKKN2 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 WFIKKN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WFIKKN2 survival associations across molecular data types. WFIKKN2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WFIKKN2 RNA expression–survival associations across cancer types. High WFIKKN2 expression shows unfavorable associations in KIRC, STAD, LGG and ACC, but favorable associations in KIRP and UCS. The KIRC 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 KIRC as the clearest survival context for WFIKKN2 RNA expression.
This table summarizes WFIKKN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for WFIKKN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WFIKKN2 shows lower tumor expression in BLCA, KIRC, KICH, COAD, LUAD and LUSC. The BLCA box plot shows higher WFIKKN2 RNA expression in normal versus tumor tissue (log2 FC = −0.376, t-test p < 0.001).
This table shows molecular features associated with WFIKKN2 in patient tissues and cancer cell lines. In patient samples, WFIKKN2 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, WFIKKN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and LARGE_INTESTINE.
