Q-omics provides the consensus-scored PAQR9 profile across patient tissues and cancer cell-line models. PAQR9 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, PAQR9 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, PAQR9 RNA expression shows 11,883 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LUAD, KIRC, and TGCT as cancer lineages where PAQR9 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 PAQR9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAQR9 survival associations across molecular data types. PAQR9 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PAQR9 RNA expression–survival associations across cancer types. High PAQR9 expression shows unfavorable associations in LUAD, LIHC, THCA, DLBC and MESO, but favorable associations in UCS. The LUAD 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 LUAD as the clearest survival context for PAQR9 RNA expression.
This table summarizes PAQR9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PAQR9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAQR9 shows lower tumor expression in HNSC and KICH and higher tumor expression in KIRC, UCEC, LIHC and KIRP. The KIRC box plot shows higher PAQR9 RNA expression in tumor versus normal tissue (log2 FC = +0.360, t-test p < 0.001).
This table shows molecular features associated with PAQR9 in patient tissues and cancer cell lines. In patient samples, PAQR9 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PAQR9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_SCLC.
