Negative regulation of cellular response to vascular endothelial growth factor stimulus

associated omics data
GO:1902548Ontology (GO BP)GO biological process · ~18 member genes

Q-omics provides the Negative regulation of cellular response to vascular endothelial growth factor stimulus (GO:1902548) pathway profile, scoring each patient from the combined activity of its roughly 18 member genes. Pathway activity is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 14, with the highest sampling consensus in KICH. Additionally, pathway RNA activity shows 32,519 significant cross-omics associations, again with the highest sampling consensus in BRCA. Together, these results highlight UCS, KICH, and BRCA 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 cellular response to vascular endothelial growth factor stimulus 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–Meier25UCS (40)view →
GO function (Protein (mass-spec))Kaplan–Meier5PDAC (22)view →
This table ranks reproducible pathway activity–survival associations across cancer types. High Negative regulation of cellular response to vascular endothelial growth factor stimulus activity shows favorable associations in UCS, but unfavorable associations in STAD, LGG, OV, HNSC and ACC. In the UCS Kaplan–Meier curve the low-activity group declines faster, consistent with the favorable association (log-rank p = .004). UCS ranks highest by sampling consensus for Negative regulation of cellular response to vascular endothelial growth factor stimulus.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
UCSDFSQuartileII,III,IV0.7040.107.00440view →
STADOSQuartileAll0.2020.529<.00136view →
LGGOSQuartileAll0.8280.950<.00122view →
OVOSTertileAll0.3160.415.01618view →
HNSCOSQuartileIII,IV0.5190.879.00217view →
ACCDFSMedianII,III,IV0.1450.613.01116view →
Pink = unfavorable, green = favorable. all 25 lineages →

Negative regulation of cellular response to vascular endothelial growth factor stimulus-UCS (DFS)

Kaplan–Meier survival curve for Negative regulation of cellular response to vascular endothelial growth factor stimulus pathway activity in UCS: high vs low activity groups.

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Tumor vs Normal activity

This table summarizes Negative regulation of cellular response to vascular endothelial growth factor stimulus tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 14 cancer types, while mass-spec protein activity shows differences in 4. The strongest signals are in COAD for RNA and LUAD for protein.
Data typeActivity analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Box plot14COAD (10)view →
GO function (Protein (mass-spec))Box plot4LUAD (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 HNSC and lower tumor activity in KICH, COAD, KIRP, KIRC and LIHC. In the KICH box plot, normal samples show higher pathway activity than tumor samples (log2 FC = −0.150, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
KICHMaleAll−0.150<.00110view →
COADFemaleIII,IV−0.121<.00110view →
KIRPFemaleAll−0.104<.0019view →
KIRCMaleII,III,IV−0.089<.0018view →
LIHCAllII,III,IV−0.058<.0018view →
HNSCAllAll+0.040.0038view →
Pink = higher activity in tumor. all 14 lineages →

Negative regulation of cellular response to vascular endothelial growth factor stimulus-KICH

Tumor-vs-normal pathway-activity box plot for Negative regulation of cellular response to vascular endothelial growth factor stimulus in KICH.

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Cross-omics associations

This table shows molecular features associated with Negative regulation of cellular response to vascular endothelial growth factor stimulus 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 BRCA. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in LUNG_SCLC.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA32,519BRCA (13154)view →
Protein (mass-spec)12,588BRCA (3723)view →
Protein (mass-spec)
Protein (mass-spec)15,863UCEC (3081)view →
RNA2,705CCRCC (822)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
CRISPR
CRISPR1,735LUNG_SCLC (172)view →
RNA1,413LUNG_SCLC (283)view →
RNA
RNA4,720BLOOD_Leukemia (1352)view →
CRISPR1,763LUNG_SCLC (174)view →
shRNA
shRNA1,649LARGE_INTESTINE (138)view →
CRISPR1,600OESOPHAGUS (147)view →
Protein (mass-spec)
RNA931KIDNEY (140)view →
Protein (mass-spec)625BONE (131)view →