MAPK activated protein kinase 2Genealiases: MAPKAP-K2 · MK-2 · MK2
Q-omics provides the consensus-scored MAPKAPK2 profile across patient tissues and cancer cell-line models. MAPKAPK2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, MAPKAPK2 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, MAPKAPK2 protein abundance shows 22,826 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where MAPKAPK2 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 MAPKAPK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAPKAPK2 survival associations across molecular data types. MAPKAPK2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (6) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAPKAPK2 RNA expression–survival associations across cancer types. High MAPKAPK2 expression shows unfavorable associations in READ, LGG, KIRP and ACC, but favorable associations in HNSC and SCLC. The HNSC 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 HNSC as the clearest survival context for MAPKAPK2 RNA expression.
This table summarizes MAPKAPK2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MAPKAPK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAPKAPK2 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, COAD, KIRC and BRCA. The HNSC box plot shows higher MAPKAPK2 RNA expression in tumor versus normal tissue (log2 FC = +0.776, t-test p < 0.001).
This table shows molecular features associated with MAPKAPK2 in patient tissues and cancer cell lines. In patient samples, MAPKAPK2 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, MAPKAPK2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BONE and UPPER_AERODIGESTIVE_TRACT.
