Q-omics provides the consensus-scored MAP4K4 profile across patient tissues and cancer cell-line models. MAP4K4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, MAP4K4 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, MAP4K4 protein abundance shows 20,833 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight MESO, HNSC, and PDAC as cancer lineages where MAP4K4 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 MAP4K4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAP4K4 survival associations across molecular data types. MAP4K4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) 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 MAP4K4 RNA expression–survival associations across cancer types. High MAP4K4 expression shows unfavorable associations in MESO, ACC, KIRP, BLCA, CESC and STAD. 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 MAP4K4 RNA expression.
This table summarizes MAP4K4 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 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MAP4K4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAP4K4 shows higher tumor expression in HNSC, KIRP, KIRC, COAD, LIHC and STAD. The HNSC box plot shows higher MAP4K4 RNA expression in tumor versus normal tissue (log2 FC = +1.596, t-test p < 0.001).
This table shows molecular features associated with MAP4K4 in patient tissues and cancer cell lines. In patient samples, MAP4K4 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, MAP4K4 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 CNS and BLOOD_Leukemia.
