Regulation of hematopoietic stem cell differentiation

associated omics data
GO:1902036Ontology (GO BP)GO biological process · ~17 member genes

Q-omics provides the Regulation of hematopoietic stem cell differentiation (GO:1902036) pathway profile, scoring each patient from the combined activity of its roughly 17 member genes. Pathway activity is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 13, with the highest sampling consensus in KICH. Additionally, pathway RNA activity shows 36,570 significant cross-omics associations, again with the highest sampling consensus in STAD. Together, these results highlight KICH, 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 hematopoietic stem cell differentiation 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–Meier25KICH (93)view →
GO function (Protein (mass-spec))Kaplan–Meier6PDAC (54)view →
This table ranks reproducible pathway activity–survival associations across cancer types. High Regulation of hematopoietic stem cell differentiation activity shows unfavorable associations in KICH, UCEC, KIRC, LGG, READ and THCA. In the KICH Kaplan–Meier curve the high-activity group declines faster, consistent with the unfavorable association (log-rank p < 0.001). KICH ranks highest by sampling consensus for Regulation of hematopoietic stem cell differentiation.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
KICHDFSTertileAll0.4471.000<.00193view →
UCECDFSQuartileAll0.5430.768.00356view →
KIRCDFSTertileIV0.1780.471.00449view →
LGGOSMedianAll0.8550.930<.00148view →
READDFSMedianAll0.7400.900.00145view →
THCAOSMedianII,III,IV0.9141.000.00144view →
Pink = unfavorable, green = favorable. all 25 lineages →

Regulation of hematopoietic stem cell differentiation-KICH (DFS)

Kaplan–Meier survival curve for Regulation of hematopoietic stem cell differentiation pathway activity in KICH: high vs low activity groups.

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Tumor vs Normal activity

This table summarizes Regulation of hematopoietic stem cell differentiation tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 13 cancer types, while mass-spec protein activity shows differences in 4. The strongest signals are in KICH for RNA and HNSC for protein.
Data typeActivity analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Box plot13KICH (9)view →
GO function (Protein (mass-spec))Box plot4HNSC (4)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 COAD, LUAD and HNSC and lower tumor activity in KICH, THCA and BRCA. In the KICH box plot, normal samples show higher pathway activity than tumor samples (log2 FC = −0.073, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
KICHFemaleAll−0.073<.0019view →
THCAAllII,III,IV−0.047<.0018view →
COADMaleAll+0.045<.0017view →
LUADFemaleAll+0.041<.0017view →
BRCAAllIII,IV−0.071<.0016view →
HNSCAllAll+0.027.0026view →
Pink = higher activity in tumor. all 13 lineages →

Regulation of hematopoietic stem cell differentiation-KICH

Tumor-vs-normal pathway-activity box plot for Regulation of hematopoietic stem cell differentiation in KICH.

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Cross-omics associations

This table shows molecular features associated with Regulation of hematopoietic stem cell differentiation 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 URINARY_TRACT.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA36,570STAD (23520)view →
Protein (mass-spec)4,897BRCA (1137)view →
Protein (mass-spec)
Protein (mass-spec)19,216GBM (8866)view →
RNA3,833BRCA (1512)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
CRISPR
CRISPR1,939URINARY_TRACT (154)view →
RNA1,467BONE (197)view →
RNA
RNA10,448BLOOD_Leukemia (5137)view →
CRISPR1,915BONE (140)view →
Protein (mass-spec)
RNA3,267BLOOD_Leukemia (1835)view →
Protein (mass-spec)1,668BLOOD_Leukemia (931)view →
shRNA
CRISPR1,317LUNG_NSCLC_LUSC (153)view →
shRNA1,309BLOOD_Myeloma (241)view →