Q-omics provides the consensus-scored MKNK2 profile across patient tissues and cancer cell-line models. MKNK2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, MKNK2 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, MKNK2 RNA expression shows 18,718 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, and ACC as cancer lineages where MKNK2 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 MKNK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MKNK2 survival associations across molecular data types. MKNK2 RNA expression shows survival associations in the most cancer types (24), 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 MKNK2 RNA expression–survival associations across cancer types. High MKNK2 expression shows unfavorable associations in KICH, LGG, ACC, LIHC and LUAD, but favorable associations in STAD. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KICH as the clearest survival context for MKNK2 RNA expression.
This table summarizes MKNK2 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 6. The strongest signals are observed in LUAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MKNK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MKNK2 shows lower tumor expression in LUAD, HNSC, COAD and THCA and higher tumor expression in KICH and LIHC. The KICH box plot shows higher MKNK2 RNA expression in tumor versus normal tissue (log2 FC = +0.969, t-test p < 0.001).
This table shows molecular features associated with MKNK2 in patient tissues and cancer cell lines. In patient samples, MKNK2 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, MKNK2 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 OESOPHAGUS and SOFT_TISSUE.
