Q-omics provides the consensus-scored MAPK14 profile across patient tissues and cancer cell-line models. MAPK14 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, MAPK14 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, MAPK14 protein abundance shows 26,066 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where MAPK14 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 MAPK14 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAPK14 survival associations across molecular data types. MAPK14 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 MAPK14 RNA expression–survival associations across cancer types. High MAPK14 expression shows unfavorable associations in MESO, ACC and KICH, but favorable associations in KIRC, THYM and UCS. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify MESO as the clearest survival context for MAPK14 RNA expression.
This table summarizes MAPK14 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 4. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MAPK14. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAPK14 shows lower tumor expression in KICH and UCEC and higher tumor expression in HNSC, LIHC, CHOL and COAD. The HNSC box plot shows higher MAPK14 RNA expression in tumor versus normal tissue (log2 FC = +0.362, t-test p < 0.001).
This table shows molecular features associated with MAPK14 in patient tissues and cancer cell lines. In patient samples, MAPK14 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, MAPK14 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
