GO:1990743Ontology (GO BP)GO biological process · ~5 member genes
Q-omics provides the Protein sialylation (GO:1990743) pathway profile, scoring each patient from the combined activity of its roughly 5 member genes. Pathway activity is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 12, with the highest sampling consensus in HNSC. Additionally, pathway RNA activity shows 30,689 significant cross-omics associations, again with the highest sampling consensus in HNSC. Together, these results highlight KIRP, and HNSC 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 Protein sialylation survival associations by molecular data type. RNA-level pathway activity shows survival associations in the most cancer types (22). 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 Protein sialylation activity shows favorable associations in CHOL, but unfavorable associations in KIRP, UVM, MESO, THCA and KIRC. In the KIRP Kaplan–Meier curve the high-activity group declines faster, consistent with the unfavorable association (log-rank p < 0.001). KIRP ranks highest by sampling consensus for Protein sialylation.
This table summarizes Protein sialylation tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 12 cancer types. The strongest signals are in HNSC for RNA.
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 HNSC and COAD and lower tumor activity in LUAD, LUSC, KIRC and THCA. In the HNSC box plot, tumor samples show higher pathway activity than matched normal samples (log2 FC = +0.057, t-test p < 0.001).
This table shows molecular features associated with Protein sialylation 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 HNSC. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in CNS.