one cut homeobox 1Genealiases: HNF-6 · HNF6 · HNF6A
Q-omics provides the consensus-scored ONECUT1 profile across patient tissues and cancer cell-line models. ONECUT1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ONECUT1 is differentially expressed in 10, with the highest sampling consensus in LUAD. Additionally, ONECUT1 RNA expression shows 14,783 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and LUAD as cancer lineages where ONECUT1 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 ONECUT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ONECUT1 survival associations across molecular data types. ONECUT1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ONECUT1 RNA expression–survival associations across cancer types. High ONECUT1 expression shows unfavorable associations in UVM, KIRP, STAD and LGG, but favorable associations in LUAD and SCLC. The UVM 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 UVM as the clearest survival context for ONECUT1 RNA expression.
This table summarizes ONECUT1 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 LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for ONECUT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ONECUT1 shows higher tumor expression in LUAD, HNSC, LUSC, BLCA, UCEC and STAD. The LUAD box plot shows higher ONECUT1 RNA expression in tumor versus normal tissue (log2 FC = +0.862, t-test p < 0.001).
This table shows molecular features associated with ONECUT1 in patient tissues and cancer cell lines. In patient samples, ONECUT1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ONECUT1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and SKIN.
