GO:0051480Ontology (GO BP)GO biological process · ~60 member genes
Q-omics provides the Regulation of cytosolic calcium ion concentration (GO:0051480) pathway profile, scoring each patient from the combined activity of its roughly 60 member genes. Pathway activity is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 14, with the highest sampling consensus in BLCA. Additionally, pathway RNA activity shows 30,453 significant cross-omics associations, again with the highest sampling consensus in LGG. Together, these results highlight COAD, BLCA, and LGG 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 Regulation of cytosolic calcium ion concentration survival associations by molecular data type. RNA-level pathway activity shows survival associations in the most cancer types (18). 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 Regulation of cytosolic calcium ion concentration activity shows favorable associations in KIRP, UVM, MESO and LGG, but unfavorable associations in COAD and READ. In the COAD Kaplan–Meier curve the high-activity group declines faster, consistent with the unfavorable association (log-rank p < 0.001). COAD ranks highest by sampling consensus for Regulation of cytosolic calcium ion concentration.
This table summarizes Regulation of cytosolic calcium ion concentration tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 14 cancer types, while mass-spec protein activity shows differences in 6. The strongest signals are in KIRC for RNA and COAD 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 KIRC and HNSC and lower tumor activity in BLCA, LUAD, COAD and LUSC. In the BLCA box plot, normal samples show higher pathway activity than tumor samples (log2 FC = −0.087, t-test p < 0.001).
This table shows molecular features associated with Regulation of cytosolic calcium ion concentration 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 LGG. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in BREAST.
