ADIPOQ-AS1

associated omics data
ADIPOQ antisense RNA 1Genealiases: []

Q-omics provides the consensus-scored ADIPOQ-AS1 profile across patient tissues and cancer cell-line models. ADIPOQ-AS1 expression is associated with patient survival in 12 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ADIPOQ-AS1 is differentially expressed in 6, with the highest sampling consensus in BRCA. Additionally, ADIPOQ-AS1 RNA expression shows 6,569 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight KICH, BRCA, and STAD as cancer lineages where ADIPOQ-AS1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics 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.

Survival associations

This table summarizes ADIPOQ-AS1 survival associations across molecular data types. ADIPOQ-AS1 RNA expression shows survival associations in the most cancer types (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
ADIPOQ-AS1 data typeSurvival analysisLineage consensusLineage of highest sampling consensus
RNAKaplan–Meier12KICH (69)view →
This table ranks reproducible ADIPOQ-AS1 RNA expression–survival associations across cancer types. High ADIPOQ-AS1 expression shows unfavorable associations in KICH, CHOL, ESCA, STAD, OV and BLCA. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .007). Together, the overview and detailed table identify KICH as the clearest survival context for ADIPOQ-AS1 RNA expression.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
KICHOSTertileII,III,IV0.7940.973.00769view →
CHOLDFSTertileAll0.1030.533.00754view →
ESCAOSTertileAll0.1980.872.00336view →
STADDFSTertileIV0.0870.415<.00132view →
OVOSTertileAll0.7730.858.00530view →
BLCADFSTertileIV0.2250.487.00327view →
Pink = unfavorable, green = favorable. all 12 lineages →

ADIPOQ-AS1-KICH (OS)

Kaplan–Meier survival curve for ADIPOQ-AS1 RNA expression in KICH: high vs low expression groups.

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Tumor vs Normal expression

This table summarizes ADIPOQ-AS1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in BRCA for RNA.
ADIPOQ-AS1 data typeExpression analysisLineage consensusLineage of highest sampling consensus
RNABox plot6BRCA (6)view →
This table ranks reproducible tumor–normal expression differences for ADIPOQ-AS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADIPOQ-AS1 shows lower tumor expression in BRCA, KIRC, LIHC, STAD and HNSC and higher tumor expression in UCEC. The BRCA box plot shows higher ADIPOQ-AS1 RNA expression in normal versus tumor tissue (log2 FC = −0.747, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
BRCAAllIII,IV−0.747<.0016view →
KIRCAllII,III,IV−0.005.0065view →
LIHCFemaleAll−0.007.0044view →
UCECAllIV+0.090.0462view →
STADMaleII,III,IV−0.015.0451view →
HNSCMaleAll−0.014.0361view →
Green = repressed in tumor. all 6 lineages →

ADIPOQ-AS1-BRCA

Tumor-vs-normal expression box plot for ADIPOQ-AS1 in BRCA.

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Cross-omics associations

This table shows molecular features associated with ADIPOQ-AS1 in patient tissues and cancer cell lines. In patient samples, ADIPOQ-AS1 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
Function (RNA)6,569STAD (5688)view →
RNA3,201KIRP (800)view →