RNA, U4atac small nuclear 17, pseudogeneGenealiases: []
Q-omics provides the consensus-scored RNU4ATAC17P profile across patient tissues and cancer cell-line models. RNU4ATAC17P expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RNU4ATAC17P is differentially expressed in 1, with the highest sampling consensus in LUSC. Additionally, RNU4ATAC17P RNA expression shows 5,023 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight KIRC, LUSC, and STAD as cancer lineages where RNU4ATAC17P 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 RNU4ATAC17P — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RNU4ATAC17P survival associations across molecular data types. RNU4ATAC17P RNA expression shows survival associations in the most cancer types (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RNU4ATAC17P RNA expression–survival associations across cancer types. High RNU4ATAC17P expression shows unfavorable associations in KIRC, KICH, LIHC and ESCA, but favorable associations in SKCM and LUSC. The KIRC 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 KIRC as the clearest survival context for RNU4ATAC17P RNA expression.
This table summarizes RNU4ATAC17P tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in LUSC for RNA.
This table ranks reproducible tumor–normal expression differences for RNU4ATAC17P. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RNU4ATAC17P shows higher tumor expression in LUSC. The LUSC box plot shows higher RNU4ATAC17P RNA expression in tumor versus normal tissue (log2 FC = +0.119, t-test p = .002).
This table shows molecular features associated with RNU4ATAC17P in patient tissues and cancer cell lines. In patient samples, RNU4ATAC17P shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set.
