Q-omics provides the consensus-scored MAPKAPK5 profile across patient tissues and cancer cell-line models. MAPKAPK5 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, MAPKAPK5 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, MAPKAPK5 RNA expression shows 21,248 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, COAD, and UVM as cancer lineages where MAPKAPK5 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 MAPKAPK5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAPKAPK5 survival associations across molecular data types. MAPKAPK5 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) 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 MAPKAPK5 RNA expression–survival associations across cancer types. High MAPKAPK5 expression shows unfavorable associations in LIHC, LGG and UVM, but favorable associations in UCS, SCLC and BRCA. The LIHC 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 LIHC as the clearest survival context for MAPKAPK5 RNA expression.
This table summarizes MAPKAPK5 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 4. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MAPKAPK5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAPKAPK5 shows higher tumor expression in COAD, BLCA, LIHC, STAD, HNSC and KIRC. The COAD box plot shows higher MAPKAPK5 RNA expression in tumor versus normal tissue (log2 FC = +0.617, t-test p < 0.001).
This table shows molecular features associated with MAPKAPK5 in patient tissues and cancer cell lines. In patient samples, MAPKAPK5 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, MAPKAPK5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
