Q-omics provides the consensus-scored MAP2K7 profile across patient tissues and cancer cell-line models. MAP2K7 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, MAP2K7 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, MAP2K7 RNA expression shows 19,932 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, and ACC as cancer lineages where MAP2K7 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 MAP2K7 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAP2K7 survival associations across molecular data types. MAP2K7 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (9) 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 MAP2K7 RNA expression–survival associations across cancer types. High MAP2K7 expression shows unfavorable associations in ACC and COAD, but favorable associations in HNSC, THYM, SCLC and CESC. The HNSC 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 HNSC as the clearest survival context for MAP2K7 RNA expression.
This table summarizes MAP2K7 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MAP2K7. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAP2K7 shows higher tumor expression in HNSC, KIRC, LIHC, KIRP, COAD and CHOL. The HNSC box plot shows higher MAP2K7 RNA expression in tumor versus normal tissue (log2 FC = +0.641, t-test p < 0.001).
This table shows molecular features associated with MAP2K7 in patient tissues and cancer cell lines. In patient samples, MAP2K7 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, MAP2K7 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
