Protein localization to nuclear body

associated omics data
GO:1903405Ontology (GO BP)GO biological process · ~12 member genes

Q-omics provides the Protein localization to nuclear body (GO:1903405) pathway profile, scoring each patient from the combined activity of its roughly 12 member genes. Pathway activity is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 11, with the highest sampling consensus in KIRC. Additionally, pathway RNA activity shows 36,800 significant cross-omics associations, again with the highest sampling consensus in HNSC. Together, these results highlight HNSC, and KIRC as cancer lineages where the pathway shows reproducible signals across outcome, tissue activity, and molecular association 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. Pathway-against-pathway and pathway-against-mutation comparisons are not available for ontology entities.

Survival associations

This table summarizes Protein localization to nuclear body survival associations by molecular data type. RNA-level pathway activity shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each layer.
Data typeSurvival analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Kaplan–Meier23HNSC (84)view →
GO function (Protein (mass-spec))Kaplan–Meier4PDAC (34)view →
This table ranks reproducible pathway activity–survival associations across cancer types. High Protein localization to nuclear body activity shows favorable associations in HNSC, BLCA and SKCM, but unfavorable associations in LGG, UVM and KIRC. In the HNSC Kaplan–Meier curve the low-activity group declines faster, consistent with the favorable association (log-rank p = .002). HNSC ranks highest by sampling consensus for Protein localization to nuclear body.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
HNSCDFSTertileIV0.5160.278.00284view →
LGGOSMedianAll0.7350.859<.00151view →
BLCADFSMedianIII,IV0.6280.382.00339view →
UVMDFSTertileIII,IV0.2640.875.00238view →
KIRCDFSTertileAll0.5360.704.00134view →
SKCMDFSTertileAll0.2830.154<.00133view →
Pink = unfavorable, green = favorable. all 23 lineages →

Tumor vs Normal activity

This table summarizes Protein localization to nuclear body tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 11 cancer types, while mass-spec protein activity shows differences in 6. The strongest signals are in KIRC for RNA and COAD for protein.
Data typeActivity analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Box plot11KIRC (11)view →
GO function (Protein (mass-spec))Box plot6COAD (9)view →
This table ranks reproducible tumor–normal activity differences for the pathway. A positive fold-change indicates higher activity in tumor tissue. The pathway shows higher tumor activity across LIHC, CHOL, STAD and LUAD and lower tumor activity in KIRC and THCA. In the KIRC box plot, normal samples show higher pathway activity than tumor samples (log2 FC = −0.025, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
KIRCAllII,III,IV−0.025<.00111view →
THCAMaleAll−0.053<.00110view →
LIHCAllII,III,IV+0.041<.0017view →
CHOLMaleAll+0.101<.0015view →
STADAllAll+0.066<.0014view →
LUADAllAll+0.032<.0014view →
Pink = higher activity in tumor. all 11 lineages →

Cross-omics associations

This table shows molecular features associated with Protein localization to nuclear body pathway activity in patient tissues and cancer cell lines. In patient samples, pathway activity is most strongly linked to RNA and protein features, with the largest associated set in HNSC. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in BLOOD_Myeloma.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA36,800HNSC (23632)view →
Protein (mass-spec)8,338LSCC (2160)view →
Protein (mass-spec)
Protein (mass-spec)26,139GBM (8199)view →
RNA8,419COAD (2067)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
shRNA
shRNA2,321BLOOD_Myeloma (316)view →
CRISPR1,644SKIN (181)view →
RNA
Inducing drug3NCI60_ALL (3)view →