Q-omics provides the consensus-scored WNK2 profile across patient tissues and cancer cell-line models. WNK2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, WNK2 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, WNK2 protein abundance shows 29,237 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SCLC, KICH, and GBM as cancer lineages where WNK2 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 WNK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WNK2 survival associations across molecular data types. WNK2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (9) 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 WNK2 RNA expression–survival associations across cancer types. High WNK2 expression shows unfavorable associations in UVM, SKCM and KIRC, but favorable associations in SCLC, LGG and LUSC. The SCLC 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 SCLC as the clearest survival context for WNK2 RNA expression.
This table summarizes WNK2 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 4. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for WNK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WNK2 shows lower tumor expression in KICH, THCA, BRCA and KIRC and higher tumor expression in LUSC and LUAD. The KICH box plot shows higher WNK2 RNA expression in normal versus tumor tissue (log2 FC = −0.823, t-test p < 0.001).
This table shows molecular features associated with WNK2 in patient tissues and cancer cell lines. In patient samples, WNK2 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, WNK2 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 LARGE_INTESTINE and LUNG_NSCLC_LUAD.
