APOA4

RNA expression — cross-omics
Cross-omicsRNA → FUNCTION-RNAPatientPairwise association · TCGA cohorts

Across TCGA patient cohorts, APOA4 RNA expression is significantly associated with the go_rna of many other GO terms, with 6,503 significant associations in total. TGCT shows the largest number of these associations.

The most reproducible APOA4-associated GO terms across cancer lineages are Regulation of very-low-density lipoprotein particle remodeling, Coenzyme A metabolic process, and Proton motive force-driven ATP synthesis. Each is linked with APOA4 in more than 7 cancer types. Because this analysis shows association rather than direction, both APOA4-to-partner and partner-to-APOA4 results are reported.

Each partner links to its own Q-omics profile. The box plot shows the strongest example, Regulation of very-low-density lipoprotein particle remodeling grouped by APOA4-low versus APOA4-high in ESCA.

RNA expression associated GO terms by consensus

Ranked by combined sampling and lineage consensus. X-score (APOA4→partner) and Y-score (partner→APOA4) are standardized regression coefficients; both directions are reported because the association is undirected. p-values are from the association test.
LineagePartner GO termX-scoreY-scorep(X)p(Y)Sampling consensusLineage consensus
ESCARegulation of very-low-density lipoprotein particle remodeling →+0.739+0.934<.001<.00138
ESCACoenzyme A metabolic process →+0.041+0.741<.001.00137
STADProton motive force-driven ATP synthesis →+0.034+0.880.001<.00137
STADObsolete negative regulation of mitochondrion organization →+0.032+0.804<.001<.00137
ESCAWater-soluble vitamin biosynthetic process →+0.051+0.848<.001.00437
ESCADicarboxylic acid metabolic process →+0.035+1.255.001<.00137
Each partner links to its Q-omics profile. Showing the 6 strongest of 6,503 associations by consensus.

Regulation of very-low-density lipoprotein particle remodeling by APOA4 expression — ESCA

Box plot of Regulation of very-low-density lipoprotein particle remodeling in APOA4-low vs APOA4-high samples in ESCA.

Explore this box plot interactively →

Exploration