Q-omics provides the consensus-scored UGCG profile across patient tissues and cancer cell-line models. UGCG expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, UGCG is differentially expressed in 9, with the highest sampling consensus in KIRP. Additionally, UGCG RNA expression shows 19,899 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRP, and UVM as cancer lineages where UGCG 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 UGCG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UGCG survival associations across molecular data types. UGCG RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UGCG RNA expression–survival associations across cancer types. High UGCG expression shows unfavorable associations in ACC, MESO, LGG and LIHC, but favorable associations in UCEC and BRCA. The ACC 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 ACC as the clearest survival context for UGCG RNA expression.
This table summarizes UGCG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRP for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for UGCG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UGCG shows lower tumor expression in BLCA and higher tumor expression in KIRP, BRCA, KIRC, THCA and LIHC. The KIRP box plot shows higher UGCG RNA expression in tumor versus normal tissue (log2 FC = +1.519, t-test p < 0.001).
This table shows molecular features associated with UGCG in patient tissues and cancer cell lines. In patient samples, UGCG 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, UGCG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BONE.
