Q-omics provides the consensus-scored MAP3K7 profile across patient tissues and cancer cell-line models. MAP3K7 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, MAP3K7 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, MAP3K7 protein abundance shows 25,852 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight LIHC, HNSC, and UCEC as cancer lineages where MAP3K7 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 MAP3K7 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAP3K7 survival associations across molecular data types. MAP3K7 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAP3K7 RNA expression–survival associations across cancer types. High MAP3K7 expression shows unfavorable associations in LIHC, BLCA, SARC and SCLC, but favorable associations in UCS and SKCM. The LIHC 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 LIHC as the clearest survival context for MAP3K7 RNA expression.
This table summarizes MAP3K7 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MAP3K7. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAP3K7 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, LUAD, KIRP and LUSC. The HNSC box plot shows higher MAP3K7 RNA expression in tumor versus normal tissue (log2 FC = +0.873, t-test p < 0.001).
This table shows molecular features associated with MAP3K7 in patient tissues and cancer cell lines. In patient samples, MAP3K7 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, MAP3K7 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 SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
