Q-omics provides the consensus-scored POLR1G profile across patient tissues and cancer cell-line models. POLR1G expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, POLR1G is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, POLR1G protein abundance shows 23,755 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight LIHC, COAD, and LUAD as cancer lineages where POLR1G 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 POLR1G — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes POLR1G survival associations across molecular data types. POLR1G RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible POLR1G RNA expression–survival associations across cancer types. High POLR1G expression shows unfavorable associations in LIHC, KIRP, MESO, KIRC, HNSC and UCEC. The LIHC 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 LIHC as the clearest survival context for POLR1G RNA expression.
This table summarizes POLR1G tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for POLR1G. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. POLR1G shows higher tumor expression in COAD, HNSC, BLCA, KIRC, THCA and STAD. The COAD box plot shows higher POLR1G RNA expression in tumor versus normal tissue (log2 FC = +1.589, t-test p < 0.001).
This table shows molecular features associated with POLR1G in patient tissues and cancer cell lines. In patient samples, POLR1G shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, POLR1G 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 LUNG_NSCLC_LUAD and BLOOD_Lymphoma.
