Q-omics provides the consensus-scored GCNT2P1 profile across patient tissues and cancer cell-line models. GCNT2P1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, GCNT2P1 is differentially expressed in 5, with the highest sampling consensus in UCEC. Additionally, GCNT2P1 RNA expression shows 16,140 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight READ, UCEC, and UVM as cancer lineages where GCNT2P1 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 GCNT2P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GCNT2P1 survival associations across molecular data types. GCNT2P1 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GCNT2P1 RNA expression–survival associations across cancer types. High GCNT2P1 expression shows unfavorable associations in READ, COAD, BRCA and THCA, but favorable associations in BLCA and KIRP. The READ Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify READ as the clearest survival context for GCNT2P1 RNA expression.
This table summarizes GCNT2P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in UCEC for RNA.
This table ranks reproducible tumor–normal expression differences for GCNT2P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GCNT2P1 shows lower tumor expression in COAD, BRCA and KIRC and higher tumor expression in UCEC and LIHC. The UCEC box plot shows higher GCNT2P1 RNA expression in tumor versus normal tissue (log2 FC = +0.329, t-test p = .008).
This table shows molecular features associated with GCNT2P1 in patient tissues and cancer cell lines. In patient samples, GCNT2P1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, GCNT2P1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST.
