Q-omics provides the consensus-scored PAQR3 profile across patient tissues and cancer cell-line models. PAQR3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in THCA. Among the 18 cancer types available for tumor–normal comparison, PAQR3 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, PAQR3 RNA expression shows 20,082 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight THCA, KIRC, and UVM as cancer lineages where PAQR3 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 PAQR3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAQR3 survival associations across molecular data types. PAQR3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 PAQR3 RNA expression–survival associations across cancer types. High PAQR3 expression shows unfavorable associations in THCA, KICH, UVM, MESO and LGG, but favorable associations in LUSC. The THCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify THCA as the clearest survival context for PAQR3 RNA expression.
This table summarizes PAQR3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PAQR3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAQR3 shows lower tumor expression in KIRC and THCA and higher tumor expression in HNSC, LUSC, LUAD and CHOL. The KIRC box plot shows higher PAQR3 RNA expression in normal versus tumor tissue (log2 FC = −0.569, t-test p < 0.001).
This table shows molecular features associated with PAQR3 in patient tissues and cancer cell lines. In patient samples, PAQR3 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, PAQR3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
