Q-omics provides the consensus-scored MAPK3 profile across patient tissues and cancer cell-line models. MAPK3 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, MAPK3 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, MAPK3 protein abundance shows 29,362 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where MAPK3 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 MAPK3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAPK3 survival associations across molecular data types. MAPK3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 MAPK3 RNA expression–survival associations across cancer types. High MAPK3 expression shows unfavorable associations in BLCA, LIHC and READ, but favorable associations in KIRC, MESO and BRCA. 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 MAPK3 RNA expression.
This table summarizes MAPK3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MAPK3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAPK3 shows lower tumor expression in THCA, KICH, COAD and HNSC and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher MAPK3 RNA expression in tumor versus normal tissue (log2 FC = +0.717, t-test p < 0.001).
This table shows molecular features associated with MAPK3 in patient tissues and cancer cell lines. In patient samples, MAPK3 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, MAPK3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
