Q-omics provides the consensus-scored MAP2K4 profile across patient tissues and cancer cell-line models. MAP2K4 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MAP2K4 is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, MAP2K4 protein abundance shows 24,045 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KICH, and GBM as cancer lineages where MAP2K4 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 MAP2K4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAP2K4 survival associations across molecular data types. MAP2K4 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAP2K4 RNA expression–survival associations across cancer types. High MAP2K4 expression shows unfavorable associations in KICH, LUSC and UVM, but favorable associations in KIRC, BRCA and UCS. The KIRC 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 KIRC as the clearest survival context for MAP2K4 RNA expression.
This table summarizes MAP2K4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MAP2K4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAP2K4 shows lower tumor expression in KICH, COAD, READ and THCA and higher tumor expression in CHOL and KIRP. The KICH box plot shows higher MAP2K4 RNA expression in normal versus tumor tissue (log2 FC = −1.398, t-test p < 0.001).
This table shows molecular features associated with MAP2K4 in patient tissues and cancer cell lines. In patient samples, MAP2K4 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, MAP2K4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
