Q-omics provides the consensus-scored MAP2K1 profile across patient tissues and cancer cell-line models. MAP2K1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, MAP2K1 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, MAP2K1 protein abundance shows 25,285 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where MAP2K1 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 MAP2K1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAP2K1 survival associations across molecular data types. MAP2K1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAP2K1 RNA expression–survival associations across cancer types. High MAP2K1 expression shows unfavorable associations in MESO, HNSC, UVM, ACC, CESC and BLCA. 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 MAP2K1 RNA expression.
This table summarizes MAP2K1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MAP2K1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAP2K1 shows lower tumor expression in LIHC and higher tumor expression in HNSC, BLCA, STAD, LUSC and COAD. The HNSC box plot shows higher MAP2K1 RNA expression in tumor versus normal tissue (log2 FC = +1.274, t-test p < 0.001).
This table shows molecular features associated with MAP2K1 in patient tissues and cancer cell lines. In patient samples, MAP2K1 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, MAP2K1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and LARGE_INTESTINE.
