Q-omics provides the consensus-scored AOC3 profile across patient tissues and cancer cell-line models. AOC3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, AOC3 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, AOC3 protein abundance shows 28,766 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, BLCA, and LSCC as cancer lineages where AOC3 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 AOC3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AOC3 survival associations across molecular data types. AOC3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) 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 AOC3 RNA expression–survival associations across cancer types. High AOC3 expression shows unfavorable associations in KIRP, LUSC, ACC, UVM and BLCA, but favorable associations in UCS. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for AOC3 RNA expression.
This table summarizes AOC3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 8. The strongest signals are observed in LUAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AOC3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AOC3 shows lower tumor expression in BLCA, LUAD, KICH, LUSC, KIRP and COAD. The BLCA box plot shows higher AOC3 RNA expression in normal versus tumor tissue (log2 FC = −4.945, t-test p < 0.001).
This table shows molecular features associated with AOC3 in patient tissues and cancer cell lines. In patient samples, AOC3 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, AOC3 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 BLOOD_Myeloma and BLOOD_Leukemia.
