Negative regulation of oxidative stress-induced neuron intrinsic apoptotic signaling pathway

pathway activity — cross-omics
GO:1903377Cross-omicsSHRNA → RNACellPairwise association · TCGA cohorts

Across TCGA cell cohorts, RNA activity of the Negative regulation of oxidative stress-induced neuron intrinsic apoptotic signaling pathway pathway is significantly associated with the RNA expression of multiple genes, with the SOFT_TISSUE cohort showing a particularly strong set of associations.

The most reproducible pathway-associated genes across cancer lineages are PLEKHG4, LGALS1, and MYCL, each associated with the pathway in up to 6 cancer types. Since the analysis shows associations rather than directional relationships, both pathway-to-partner and partner-to-pathway views are reported.

Each partner is linked to its corresponding Q-omics profile. The box plot shows the strongest association, PLEKHG4 grouped by Negative regulation of oxidative stress-induced neuron intrinsic apoptotic signaling pathway-low versus -high activity in SOFT_TISSUE.

Pathway-associated genes by consensus

Ranked by combined sampling and lineage consensus. X-score (pathway→partner) and Y-score (partner→pathway) are standardized regression coefficients; both directions are reported because the association is undirected. The reported p-values are derived from the association test.
LineagePartner geneX-scoreY-scorep(X)p(Y)Sampling consensusLineage consensus
SOFT_TISSUEPLEKHG4 →-2.495-1.460.004.00226
LARGE_INTESTINELGALS1 →-3.113-0.721.001.00934
LARGE_INTESTINEMYCL →+1.688+0.614<.001.00834
LARGE_INTESTINEPPP1R18 →-1.815-0.618<.001.00634
BLOOD_LeukemiaPTGS1 →-2.287-0.856.007.00734
STOMACHRNF43 →+3.947+1.035<.001<.00134
Each partner links to its Q-omics profile. Showing the 6 strongest associations by consensus.

PLEKHG4 by Negative regulation of oxidative stress-induced neuron intrinsic apoptotic signaling pathway activity — SOFT_TISSUE

Box plot of PLEKHG4 in Negative regulation of oxidative stress-induced neuron intrinsic apoptotic signaling pathway-low vs -high samples in SOFT_TISSUE.

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