Q-omics provides the consensus-scored URGCP profile across patient tissues and cancer cell-line models. URGCP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, URGCP is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, URGCP RNA expression shows 20,114 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight CESC, HNSC, and ACC as cancer lineages where URGCP 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 URGCP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes URGCP survival associations across molecular data types. URGCP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible URGCP RNA expression–survival associations across cancer types. High URGCP expression shows unfavorable associations in CESC, LGG and ACC, but favorable associations in KIRP, PAAD and ESCA. The CESC 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 CESC as the clearest survival context for URGCP RNA expression.
This table summarizes URGCP 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 6. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for URGCP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. URGCP shows lower tumor expression in THCA and COAD and higher tumor expression in HNSC, LIHC, KIRC and STAD. The HNSC box plot shows higher URGCP RNA expression in tumor versus normal tissue (log2 FC = +0.705, t-test p < 0.001).
This table shows molecular features associated with URGCP in patient tissues and cancer cell lines. In patient samples, URGCP shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, URGCP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
