Q-omics provides the consensus-scored PAQR6 profile across patient tissues and cancer cell-line models. PAQR6 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PAQR6 is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, PAQR6 RNA expression shows 15,256 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where PAQR6 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 PAQR6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAQR6 survival associations across molecular data types. PAQR6 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PAQR6 RNA expression–survival associations across cancer types. High PAQR6 expression shows unfavorable associations in KIRC, ACC, KIRP and COAD, but favorable associations in BLCA and STAD. The KIRC 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 KIRC as the clearest survival context for PAQR6 RNA expression.
This table summarizes PAQR6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for PAQR6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAQR6 shows lower tumor expression in KICH and higher tumor expression in THCA, KIRC, LIHC, HNSC and KIRP. The THCA box plot shows higher PAQR6 RNA expression in tumor versus normal tissue (log2 FC = +1.675, t-test p < 0.001).
This table shows molecular features associated with PAQR6 in patient tissues and cancer cell lines. In patient samples, PAQR6 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PAQR6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and SOFT_TISSUE.
