Q-omics provides the consensus-scored ST3GAL1 profile across patient tissues and cancer cell-line models. ST3GAL1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ST3GAL1 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, ST3GAL1 protein abundance shows 23,042 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, KICH, and PDAC as cancer lineages where ST3GAL1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics 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.
Premium analyses for ST3GAL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ST3GAL1 survival associations across molecular data types. ST3GAL1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ST3GAL1 RNA expression–survival associations across cancer types. High ST3GAL1 expression shows unfavorable associations in UVM, LGG, KIRP and UCEC, but favorable associations in KIRC and THCA. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for ST3GAL1 RNA expression.
This table summarizes ST3GAL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ST3GAL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ST3GAL1 shows lower tumor expression in LUAD, THCA and KIRP and higher tumor expression in KICH, COAD and BRCA. The KICH box plot shows higher ST3GAL1 RNA expression in tumor versus normal tissue (log2 FC = +2.467, t-test p < 0.001).
This table shows molecular features associated with ST3GAL1 in patient tissues and cancer cell lines. In patient samples, ST3GAL1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, ST3GAL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Lymphoma.
