RNU6-1235P

Q-omics provides the consensus-scored RNU6-1235P profile across patient tissues and cancer cell-line models. RNU6-1235P expression is associated with patient survival in 2 of 34 cancer types, with the highest sampling consensus in PCPG. Additionally, RNU6-1235P RNA expression shows 1,130 significant gene co-expression associations, with the highest sampling consensus in LGG. Together, these results highlight PCPG, and LGG as cancer lineages where RNU6-1235P 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 RNU6-1235P survival associations across molecular data types. RNU6-1235P 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.

RNU6-1235P data type	Survival analysis	Lineage consensus	Lineage of highest sampling consensus
RNA	Kaplan–Meier	2	PCPG (36)	view →

This table ranks reproducible RNU6-1235P RNA expression–survival associations across cancer types. High RNU6-1235P expression shows unfavorable associations in PCPG and SKCM. The PCPG Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify PCPG as the clearest survival context for RNU6-1235P RNA expression.

Lineage	Measure	Split	Stage	AUC1 high	AUC2 low	p	Sampling consensus
PCPG	OS	Tertile	All	0.516	0.948	.002	36	view →
SKCM	DFS	Tertile	III,IV	0.129	0.601	.002	18	view →

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

RNU6-1235P-PCPG (OS)

Explore this curve interactively →