Q-omics provides the consensus-scored POLR2D profile across patient tissues and cancer cell-line models. POLR2D expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, POLR2D is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, POLR2D protein abundance shows 23,663 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, HNSC, and GBM as cancer lineages where POLR2D 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 POLR2D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes POLR2D survival associations across molecular data types. POLR2D RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) 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 POLR2D RNA expression–survival associations across cancer types. High POLR2D expression shows unfavorable associations in KIRP, ACC, LIHC, MESO and KICH, but favorable associations in OV. The KIRP 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 KIRP as the clearest survival context for POLR2D RNA expression.
This table summarizes POLR2D 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 5. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for POLR2D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. POLR2D shows higher tumor expression in HNSC, COAD, BLCA, KIRC, LIHC and LUAD. The HNSC box plot shows higher POLR2D RNA expression in tumor versus normal tissue (log2 FC = +1.127, t-test p < 0.001).
This table shows molecular features associated with POLR2D in patient tissues and cancer cell lines. In patient samples, POLR2D 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, POLR2D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
