Q-omics provides the consensus-scored KCNQ2 profile across patient tissues and cancer cell-line models. KCNQ2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, KCNQ2 is differentially expressed in 6, with the highest sampling consensus in KIRC. Additionally, KCNQ2 RNA expression shows 13,622 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, KIRC, and UVM as cancer lineages where KCNQ2 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 KCNQ2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KCNQ2 survival associations across molecular data types. KCNQ2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KCNQ2 RNA expression–survival associations across cancer types. High KCNQ2 expression shows unfavorable associations in KIRP, UVM, KIRC, UCEC and ACC, but favorable associations in LGG. The KIRP 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 KIRP as the clearest survival context for KCNQ2 RNA expression.
This table summarizes KCNQ2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for KCNQ2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KCNQ2 shows lower tumor expression in KIRC, KICH and READ and higher tumor expression in LUAD, LUSC and LIHC. The KIRC box plot shows higher KCNQ2 RNA expression in normal versus tumor tissue (log2 FC = −0.098, t-test p < 0.001).
This table shows molecular features associated with KCNQ2 in patient tissues and cancer cell lines. In patient samples, KCNQ2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, KCNQ2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
