Negative regulation of hematopoietic stem cell proliferation

associated omics data
GO:1902034Ontology (GO BP)GO biological process · ~5 member genes

Q-omics provides the Negative regulation of hematopoietic stem cell proliferation (GO:1902034) pathway profile, scoring each patient from the combined activity of its roughly 5 member genes. Pathway activity is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 8, with the highest sampling consensus in KIRC. Additionally, pathway RNA activity shows 28,244 significant cross-omics associations, again with the highest sampling consensus in KIRP. Together, these results highlight UVM, KIRC, and KIRP 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 Negative regulation of hematopoietic stem cell proliferation 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–Meier25UVM (59)view →
GO function (Protein (mass-spec))Kaplan–Meier3HNSC (11)view →
This table ranks reproducible pathway activity–survival associations across cancer types. High Negative regulation of hematopoietic stem cell proliferation activity shows favorable associations in BLCA, KIRP and DLBC, but unfavorable associations in UVM, SKCM and LGG. In the UVM Kaplan–Meier curve the high-activity group declines faster, consistent with the unfavorable association (log-rank p = .001). UVM ranks highest by sampling consensus for Negative regulation of hematopoietic stem cell proliferation.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
UVMOSMedianAll0.4210.757.00159view →
BLCADFSMedianAll0.4780.194<.00148view →
SKCMDFSTertileAll0.5140.686.00239view →
KIRPOSQuartileII,III,IV0.8970.316.00133view →
DLBCDFSMedianAll0.9430.558.00733view →
LGGOSTertileAll0.3540.533.00132view →
Pink = unfavorable, green = favorable. all 25 lineages →

Tumor vs Normal activity

This table summarizes Negative regulation of hematopoietic stem cell proliferation tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 8 cancer types. The strongest signals are in KIRC for RNA.
Data typeActivity analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Box plot8KIRC (10)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 KIRC, LIHC, LUSC and BLCA and lower tumor activity in KICH and LUAD. In the KIRC box plot, tumor samples show higher pathway activity than matched normal samples (log2 FC = +0.076, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
KIRCAllII,III,IV+0.076<.00110view →
LIHCMaleII,III,IV+0.103<.0016view →
KICHAllIV−0.055.0026view →
LUSCMaleAll+0.106<.0015view →
BLCAAllIII,IV+0.110.0074view →
LUADAllAll−0.030.0354view →
Pink = higher activity in tumor. all 8 lineages →

Cross-omics associations

This table shows molecular features associated with Negative regulation of hematopoietic stem cell proliferation 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 KIRP. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in BLOOD_Leukemia.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA28,244KIRP (7855)view →
Protein (mass-spec)14,270GBM (6642)view →
Protein (mass-spec)
Protein (mass-spec)10,692UCEC (2562)view →
RNA2,263CCRCC (890)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
shRNA
RNA1,071BLOOD_Leukemia (407)view →
shRNA800BLOOD_Myeloma (152)view →
RNA
Inducing drug2NCI60_ALL (2)view →