Q-omics provides the consensus-scored POLR2C profile across patient tissues and cancer cell-line models. POLR2C expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, POLR2C is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, POLR2C protein abundance shows 25,279 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where POLR2C 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 POLR2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes POLR2C survival associations across molecular data types. POLR2C RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 POLR2C RNA expression–survival associations across cancer types. High POLR2C expression shows unfavorable associations in HNSC, LGG, CESC and BLCA, but favorable associations in KIRC and LUAD. The HNSC 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 HNSC as the clearest survival context for POLR2C RNA expression.
This table summarizes POLR2C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, 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 POLR2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. POLR2C shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, COAD, KIRC and LIHC. The HNSC box plot shows higher POLR2C RNA expression in tumor versus normal tissue (log2 FC = +0.724, t-test p < 0.001).
This table shows molecular features associated with POLR2C in patient tissues and cancer cell lines. In patient samples, POLR2C shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, POLR2C 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_NSCLC_LUAD and BLOOD_Leukemia.
