Q-omics provides the consensus-scored KCNJ2 profile across patient tissues and cancer cell-line models. KCNJ2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, KCNJ2 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, KCNJ2 protein abundance shows 22,271 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight UVM, KIRC, and LUAD as cancer lineages where KCNJ2 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 KCNJ2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KCNJ2 survival associations across molecular data types. KCNJ2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (10) 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 KCNJ2 RNA expression–survival associations across cancer types. High KCNJ2 expression shows unfavorable associations in UVM, LGG, LIHC and KIRP, but favorable associations in SKCM and HNSC. The UVM 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 UVM as the clearest survival context for KCNJ2 RNA expression.
This table summarizes KCNJ2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for KCNJ2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KCNJ2 shows lower tumor expression in COAD and BRCA and higher tumor expression in KIRC, THCA, KIRP and LIHC. The KIRC box plot shows higher KCNJ2 RNA expression in tumor versus normal tissue (log2 FC = +1.788, t-test p < 0.001).
This table shows molecular features associated with KCNJ2 in patient tissues and cancer cell lines. In patient samples, KCNJ2 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, KCNJ2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in CNS and UPPER_AERODIGESTIVE_TRACT.
