Q-omics provides the consensus-scored PAPOLG profile across patient tissues and cancer cell-line models. PAPOLG expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PAPOLG is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PAPOLG protein abundance shows 23,059 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where PAPOLG 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 PAPOLG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAPOLG survival associations across molecular data types. PAPOLG RNA expression shows survival associations in the most cancer types (27), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PAPOLG RNA expression–survival associations across cancer types. High PAPOLG expression shows unfavorable associations in ACC, MESO, LIHC and KIRP, but favorable associations in KIRC and SCLC. 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 PAPOLG RNA expression.
This table summarizes PAPOLG 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 5. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PAPOLG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAPOLG shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, BLCA, LIHC and LUSC. The HNSC box plot shows higher PAPOLG RNA expression in tumor versus normal tissue (log2 FC = +0.906, t-test p < 0.001).
This table shows molecular features associated with PAPOLG in patient tissues and cancer cell lines. In patient samples, PAPOLG 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, PAPOLG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
