Q-omics provides the consensus-scored GCNT1 profile across patient tissues and cancer cell-line models. GCNT1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, GCNT1 is differentially expressed in 7, with the highest sampling consensus in UCEC. Additionally, GCNT1 RNA expression shows 19,347 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight SKCM, UCEC, and THYM as cancer lineages where GCNT1 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 GCNT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GCNT1 survival associations across molecular data types. GCNT1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (10) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GCNT1 RNA expression–survival associations across cancer types. High GCNT1 expression shows unfavorable associations in KIRP, ACC, UVM and LGG, but favorable associations in SKCM and CHOL. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for GCNT1 RNA expression.
This table summarizes GCNT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 2. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for GCNT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GCNT1 shows higher tumor expression in UCEC, KICH, COAD, PRAD, KIRC and HNSC. The UCEC box plot shows higher GCNT1 RNA expression in tumor versus normal tissue (log2 FC = +2.929, t-test p < 0.001).
This table shows molecular features associated with GCNT1 in patient tissues and cancer cell lines. In patient samples, GCNT1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, GCNT1 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 UPPER_AERODIGESTIVE_TRACT and BONE.
