Regulation of blood circulation

associated omics data
GO:1903522Ontology (GO BP)GO biological process · ~256 member genes

Q-omics provides the Regulation of blood circulation (GO:1903522) pathway profile, scoring each patient from the combined activity of its roughly 256 member genes. Pathway activity is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 14, with the highest sampling consensus in BLCA. Additionally, pathway RNA activity shows 36,410 significant cross-omics associations, again with the highest sampling consensus in STAD. Together, these results highlight READ, BLCA, and STAD 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 Regulation of blood circulation survival associations by molecular data type. RNA-level pathway activity shows survival associations in the most cancer types (25). 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–Meier25READ (59)view →
This table ranks reproducible pathway activity–survival associations across cancer types. High Regulation of blood circulation activity shows favorable associations in UCS, THCA and ESCA, but unfavorable associations in READ, SCLC and GBM. In the READ Kaplan–Meier curve the high-activity group declines faster, consistent with the unfavorable association (log-rank p = .003). READ ranks highest by sampling consensus for Regulation of blood circulation.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
READDFSTertileAll0.2500.607.00359view →
UCSDFSTertileII,III,IV0.5970.159.00448view →
SCLCDFSMedianII,III,IV0.2320.580.00131view →
THCADFSMedianIV1.0000.551.00430view →
GBMOSTertileAll0.2960.442.01027view →
ESCAOSTertileIII,IV0.6560.329.01427view →
Pink = unfavorable, green = favorable. all 25 lineages →

Regulation of blood circulation-READ (DFS)

Kaplan–Meier survival curve for Regulation of blood circulation pathway activity in READ: high vs low activity groups.

Explore this curve interactively →

Tumor vs Normal activity

This table summarizes Regulation of blood circulation tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 14 cancer types. The strongest signals are in BLCA for RNA.
Data typeActivity analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Box plot14BLCA (11)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 consistently lower tumor activity across BLCA, COAD, KICH, KIRP, LUSC and LUAD. In the BLCA box plot, normal samples show higher pathway activity than tumor samples (log2 FC = −0.030, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
BLCAAllAll−0.030<.00111view →
COADMaleII,III,IV−0.027<.00110view →
KICHMaleII,III,IV−0.026<.00110view →
KIRPFemaleAll−0.028<.0019view →
LUSCAllIII,IV−0.044<.0018view →
LUADFemaleAll−0.027<.0017view →
Pink = higher activity in tumor. all 14 lineages →

Regulation of blood circulation-BLCA

Tumor-vs-normal pathway-activity box plot for Regulation of blood circulation in BLCA.

Explore this plot interactively →

Cross-omics associations

This table shows molecular features associated with Regulation of blood circulation 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 STAD. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in PANCREAS.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA36,410STAD (22886)view →
Protein (mass-spec)25,958LSCC (12455)view →
Protein (mass-spec)
Protein (mass-spec)249OV (184)view →
RNA82OV (67)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
CRISPR
CRISPR2,028PANCREAS (270)view →
RNA1,459SKIN (232)view →
RNA
RNA8,627UPPER_AERODIGESTIVE_TRACT (3524)view →
CRISPR2,064LUNG_NSCLC_LUAD (189)view →
Protein (mass-spec)
RNA2,506BONE (630)view →
CRISPR1,579BREAST (135)view →
shRNA
shRNA1,665BLOOD_Myeloma (408)view →
RNA1,149LARGE_INTESTINE (374)view →