Protein unfolding

associated omics data
GO:0043335Ontology (GO BP)GO biological process · ~5 member genes

Q-omics provides the Protein unfolding (GO:0043335) pathway profile, scoring each patient from the combined activity of its roughly 5 member genes. Pathway activity is associated with patient survival in 27 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 8, with the highest sampling consensus in LUAD. Additionally, pathway RNA activity shows 34,002 significant cross-omics associations, again with the highest sampling consensus in KIRC. Together, these results highlight UCS, LUAD, 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 unfolding survival associations by molecular data type. RNA-level pathway activity shows survival associations in the most cancer types (27). 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–Meier27UCS (96)view →
GO function (Protein (mass-spec))Kaplan–Meier7PDAC (33)view →
This table ranks reproducible pathway activity–survival associations across cancer types. High Protein unfolding activity shows favorable associations in ESCA, but unfavorable associations in UCS, KIRC, STAD, COAD and MESO. In the UCS Kaplan–Meier curve the high-activity group declines faster, consistent with the unfavorable association (log-rank p < 0.001). UCS ranks highest by sampling consensus for Protein unfolding.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
UCSOSMedianII,III,IV0.1890.721<.00196view →
KIRCDFSMedianII,III,IV0.3730.617<.00186view →
STADDFSMedianII,III,IV0.2680.469<.00181view →
ESCADFSMedianIII,IV0.5600.301.00354view →
COADDFSQuartileII,III,IV0.5610.775.00146view →
MESODFSMedianII,III,IV0.3000.488.00433view →
Pink = unfavorable, green = favorable. all 27 lineages →

Protein unfolding-UCS (OS)

Kaplan–Meier survival curve for Protein unfolding pathway activity in UCS: high vs low activity groups.

Explore this curve interactively →

Tumor vs Normal activity

This table summarizes Protein unfolding tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 8 cancer types, while mass-spec protein activity shows differences in 4. The strongest signals are in LUAD for RNA and LSCC for protein.
Data typeActivity analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Box plot8LUAD (9)view →
GO function (Protein (mass-spec))Box plot4LSCC (8)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 LUAD, KIRC, LUSC and PAAD and lower tumor activity in KICH and BRCA. In the LUAD box plot, tumor samples show higher pathway activity than matched normal samples (log2 FC = +0.066, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
LUADAllIII,IV+0.066<.0019view →
KIRCMaleAll+0.033<.0018view →
KICHFemaleII,III,IV−0.105<.0016view →
BRCAFemaleAll−0.057<.0016view →
LUSCAllAll+0.035.0013view →
PAADFemaleAll+0.084.0422view →
Pink = higher activity in tumor. all 8 lineages →

Protein unfolding-LUAD

Tumor-vs-normal pathway-activity box plot for Protein unfolding in LUAD.

Explore this plot interactively →

Cross-omics associations

This table shows molecular features associated with Protein unfolding 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 KIRC. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in SOFT_TISSUE.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA34,002KIRC (15194)view →
Protein (mass-spec)5,390BRCA (1068)view →
Protein (mass-spec)
Protein (mass-spec)17,845COAD (3424)view →
RNA3,089PDAC (728)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
CRISPR
CRISPR2,068SOFT_TISSUE (172)view →
RNA1,957BONE (530)view →
RNA
RNA3,668BONE (568)view →
CRISPR1,842LIVER (129)view →
Protein (mass-spec)
RNA3,010BLOOD_Leukemia (1076)view →
CRISPR1,514LUNG_NSCLC_LUSC (181)view →
shRNA
shRNA2,030BLOOD_Leukemia (306)view →
RNA1,704UPPER_AERODIGESTIVE_TRACT (588)view →