divergent protein kinase domain 1CGenealiases: C18orf51 · FAM69C · FNCAD
Q-omics provides the consensus-scored DIPK1C profile across patient tissues and cancer cell-line models. DIPK1C expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, DIPK1C is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, DIPK1C RNA expression shows 10,813 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight CESC, KICH, and TGCT as cancer lineages where DIPK1C 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 DIPK1C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DIPK1C survival associations across molecular data types. DIPK1C RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DIPK1C RNA expression–survival associations across cancer types. High DIPK1C expression shows unfavorable associations in KIRP, READ and BLCA, but favorable associations in CESC, HNSC and LUSC. The CESC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .006). Together, the overview and detailed table identify CESC as the clearest survival context for DIPK1C RNA expression.
This table summarizes DIPK1C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for DIPK1C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DIPK1C shows lower tumor expression in KICH, READ and KIRP and higher tumor expression in LUSC, LUAD and THCA. The KICH box plot shows higher DIPK1C RNA expression in normal versus tumor tissue (log2 FC = −0.162, t-test p < 0.001).
This table shows molecular features associated with DIPK1C in patient tissues and cancer cell lines. In patient samples, DIPK1C shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, DIPK1C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SKIN.
