GO:0036343Ontology (GO BP)GO biological process · ~5 member genes
Q-omics provides the Psychomotor behavior (GO:0036343) pathway profile, scoring each patient from the combined activity of its roughly 5 member genes. Pathway activity is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 12, with the highest sampling consensus in LIHC. Additionally, pathway RNA activity shows 28,814 significant cross-omics associations, again with the highest sampling consensus in SKCM. Together, these results highlight KIRC, LIHC, and SKCM 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 Psychomotor behavior survival associations by molecular data type. RNA-level pathway activity shows survival associations in the most cancer types (29). The rightmost column indicates the cancer type with the highest sampling consensus for each layer.
This table ranks reproducible pathway activity–survival associations across cancer types. High Psychomotor behavior activity shows favorable associations in KIRC, BLCA, MESO, KIRP and HNSC, but unfavorable associations in READ. In the KIRC Kaplan–Meier curve the low-activity group declines faster, consistent with the favorable association (log-rank p = .003). KIRC ranks highest by sampling consensus for Psychomotor behavior.
This table summarizes Psychomotor behavior tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 12 cancer types, while mass-spec protein activity shows differences in 3. The strongest signals are in LIHC for RNA and LUAD for protein.
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 THCA and lower tumor activity in LIHC, COAD, KIRP, KICH and UCEC. In the LIHC box plot, normal samples show higher pathway activity than tumor samples (log2 FC = −0.118, t-test p < 0.001).
This table shows molecular features associated with Psychomotor behavior 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 SKCM. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in UPPER_AERODIGESTIVE_TRACT.
