RNU5F-7P

Q-omics provides the consensus-scored RNU5F-7P profile across patient tissues and cancer cell-line models. RNU5F-7P expression is associated with patient survival in 2 of 34 cancer types, with the highest sampling consensus in ESCA. Additionally, RNU5F-7P RNA expression shows 5,415 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight ESCA, and STAD as cancer lineages where RNU5F-7P 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.

Survival associations

This table summarizes RNU5F-7P survival associations across molecular data types. RNU5F-7P RNA expression shows survival associations in the most cancer types (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.

RNU5F-7P data type	Survival analysis	Lineage consensus	Lineage of highest sampling consensus
RNA	Kaplan–Meier	2	BRCA (12)	view →

This table ranks reproducible RNU5F-7P RNA expression–survival associations across cancer types. High RNU5F-7P expression shows unfavorable associations in BRCA, but favorable associations in ESCA. The ESCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .039). Together, the overview and detailed table identify ESCA as the clearest survival context for RNU5F-7P RNA expression.

Lineage	Measure	Split	Stage	AUC1 high	AUC2 low	p	Sampling consensus
ESCA	OS	Tertile	III,IV	0.802	0.368	.039	12	view →
BRCA	OS	Tertile	All	0.168	0.579	.047	12	view →

Pink = unfavorable, green = favorable. all 2 lineages →

RNU5F-7P-ESCA (OS)

Explore this curve interactively →