Q-omics provides the consensus-scored WNK1 profile across patient tissues and cancer cell-line models. WNK1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, WNK1 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, WNK1 protein abundance shows 24,639 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, KIRC, and GBM as cancer lineages where WNK1 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 WNK1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WNK1 survival associations across molecular data types. WNK1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (9) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WNK1 RNA expression–survival associations across cancer types. High WNK1 expression shows unfavorable associations in MESO, UVM, BLCA, LIHC and ACC, but favorable associations in KIRC. The MESO 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 MESO as the clearest survival context for WNK1 RNA expression.
This table summarizes WNK1 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for WNK1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WNK1 shows lower tumor expression in KIRC and KIRP and higher tumor expression in HNSC, LIHC, CHOL and BRCA. The KIRC box plot shows higher WNK1 RNA expression in normal versus tumor tissue (log2 FC = −1.138, t-test p < 0.001).
This table shows molecular features associated with WNK1 in patient tissues and cancer cell lines. In patient samples, WNK1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, WNK1 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 LUNG_NSCLC_LUAD and BLOOD_Leukemia.
