Q-omics provides the consensus-scored ACY3 profile across patient tissues and cancer cell-line models. ACY3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ACY3 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, ACY3 RNA expression shows 13,900 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRP, KICH, and ESCA as cancer lineages where ACY3 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 ACY3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACY3 survival associations across molecular data types. ACY3 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACY3 RNA expression–survival associations across cancer types. High ACY3 expression shows unfavorable associations in UVM, but favorable associations in KIRP, SKCM, KIRC, BLCA and UCEC. The KIRP 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 KIRP as the clearest survival context for ACY3 RNA expression.
This table summarizes ACY3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACY3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACY3 shows lower tumor expression in KICH, KIRP and BRCA and higher tumor expression in LUAD, HNSC and COAD. The KICH box plot shows higher ACY3 RNA expression in normal versus tumor tissue (log2 FC = −5.733, t-test p < 0.001).
This table shows molecular features associated with ACY3 in patient tissues and cancer cell lines. In patient samples, ACY3 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, ACY3 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 LUNG_SCLC and BLOOD_Lymphoma.
