Q-omics provides the consensus-scored AQR profile across patient tissues and cancer cell-line models. AQR expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, AQR is differentially expressed in 8, with the highest sampling consensus in THCA. Additionally, AQR protein abundance shows 33,811 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, THCA, and LSCC as cancer lineages where AQR 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 AQR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AQR survival associations across molecular data types. AQR RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AQR RNA expression–survival associations across cancer types. High AQR expression shows unfavorable associations in UVM, PAAD, BLCA and ACC, but favorable associations in KIRC and UCEC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for AQR RNA expression.
This table summarizes AQR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for AQR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AQR shows lower tumor expression in THCA and higher tumor expression in LIHC, CHOL, HNSC, STAD and LUSC. The THCA box plot shows higher AQR RNA expression in normal versus tumor tissue (log2 FC = −0.477, t-test p < 0.001).
This table shows molecular features associated with AQR in patient tissues and cancer cell lines. In patient samples, AQR 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, AQR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LARGE_INTESTINE.
