Q-omics provides the consensus-scored POLR2J3 profile across patient tissues and cancer cell-line models. POLR2J3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, POLR2J3 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, POLR2J3 RNA expression shows 15,896 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KICH, COAD, and UVM as cancer lineages where POLR2J3 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 POLR2J3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes POLR2J3 survival associations across molecular data types. POLR2J3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible POLR2J3 RNA expression–survival associations across cancer types. High POLR2J3 expression shows unfavorable associations in KICH, KIRC, LGG and ACC, but favorable associations in CESC and PAAD. The KICH 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 KICH as the clearest survival context for POLR2J3 RNA expression.
This table summarizes POLR2J3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for POLR2J3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. POLR2J3 shows higher tumor expression in COAD, LIHC, KIRC, THCA, LUSC and CHOL. The COAD box plot shows higher POLR2J3 RNA expression in tumor versus normal tissue (log2 FC = +0.295, t-test p < 0.001).
This table shows molecular features associated with POLR2J3 in patient tissues and cancer cell lines. In patient samples, POLR2J3 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, POLR2J3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and LARGE_INTESTINE.
