Q-omics provides the consensus-scored POLQ profile across patient tissues and cancer cell-line models. POLQ expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, POLQ is differentially expressed in 17, with the highest sampling consensus in BLCA. Additionally, POLQ RNA expression shows 27,165 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, BLCA, and LSCC as cancer lineages where POLQ 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 POLQ — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes POLQ survival associations across molecular data types. POLQ RNA expression shows survival associations in the most cancer types (26), followed by mutation status (9) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible POLQ RNA expression–survival associations across cancer types. High POLQ expression shows unfavorable associations in ACC, MESO, KIRP, KIRC, KICH and LIHC. The ACC 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 ACC as the clearest survival context for POLQ RNA expression.
This table summarizes POLQ tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17. The strongest signals are observed in BLCA for RNA.
This table ranks reproducible tumor–normal expression differences for POLQ. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. POLQ shows higher tumor expression in BLCA, HNSC, COAD, KIRP, KIRC and LUAD. The BLCA box plot shows higher POLQ RNA expression in tumor versus normal tissue (log2 FC = +2.272, t-test p < 0.001).
This table shows molecular features associated with POLQ in patient tissues and cancer cell lines. In patient samples, POLQ shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, POLQ 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 BREAST and BLOOD_Leukemia.
