Q-omics provides the consensus-scored MAP4K3 profile across patient tissues and cancer cell-line models. MAP4K3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MAP4K3 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, MAP4K3 RNA expression shows 21,546 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, and THYM as cancer lineages where MAP4K3 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 MAP4K3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAP4K3 survival associations across molecular data types. MAP4K3 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAP4K3 RNA expression–survival associations across cancer types. High MAP4K3 expression shows unfavorable associations in UVM, LIHC, KIRP and STAD, but favorable associations in KIRC and LUAD. 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 MAP4K3 RNA expression.
This table summarizes MAP4K3 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 2. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MAP4K3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAP4K3 shows lower tumor expression in KIRC and THCA and higher tumor expression in HNSC, LIHC, BLCA and CHOL. The KIRC box plot shows higher MAP4K3 RNA expression in normal versus tumor tissue (log2 FC = −0.805, t-test p < 0.001).
This table shows molecular features associated with MAP4K3 in patient tissues and cancer cell lines. In patient samples, MAP4K3 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, MAP4K3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
