Q-omics provides the consensus-scored MAPK6 profile across patient tissues and cancer cell-line models. MAPK6 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, MAPK6 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, MAPK6 RNA expression shows 19,764 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, HNSC, and ACC as cancer lineages where MAPK6 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 MAPK6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAPK6 survival associations across molecular data types. MAPK6 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) 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 MAPK6 RNA expression–survival associations across cancer types. High MAPK6 expression shows unfavorable associations in MESO, UVM, ACC, LUAD and KICH, but favorable associations in UCEC. The MESO 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 MESO as the clearest survival context for MAPK6 RNA expression.
This table summarizes MAPK6 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MAPK6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAPK6 shows lower tumor expression in COAD and higher tumor expression in HNSC, LIHC, LUSC, LUAD and UCEC. The HNSC box plot shows higher MAPK6 RNA expression in tumor versus normal tissue (log2 FC = +1.258, t-test p < 0.001).
This table shows molecular features associated with MAPK6 in patient tissues and cancer cell lines. In patient samples, MAPK6 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, MAPK6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and LARGE_INTESTINE.
