Q-omics provides the consensus-scored DIPK2A profile across patient tissues and cancer cell-line models. DIPK2A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, DIPK2A is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, DIPK2A RNA expression shows 20,341 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, KIRC, and ACC as cancer lineages where DIPK2A 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 DIPK2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DIPK2A survival associations across molecular data types. DIPK2A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) 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 DIPK2A RNA expression–survival associations across cancer types. High DIPK2A expression shows unfavorable associations in KIRP, MESO and ACC, but favorable associations in LUSC, KIRC and HNSC. The KIRP 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 KIRP as the clearest survival context for DIPK2A RNA expression.
This table summarizes DIPK2A 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DIPK2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DIPK2A shows lower tumor expression in THCA, LUAD, KICH and UCEC and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher DIPK2A RNA expression in tumor versus normal tissue (log2 FC = +0.969, t-test p < 0.001).
This table shows molecular features associated with DIPK2A in patient tissues and cancer cell lines. In patient samples, DIPK2A 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, DIPK2A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LUNG_NSCLC_LUAD.
