Q-omics provides the consensus-scored ACLY profile across patient tissues and cancer cell-line models. ACLY expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, ACLY is differentially expressed in 17, with the highest sampling consensus in KIRC. Additionally, ACLY RNA expression shows 19,620 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, KIRC, and ACC as cancer lineages where ACLY 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 ACLY — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACLY survival associations across molecular data types. ACLY RNA expression shows survival associations in the most cancer types (29), followed by mutation status (8) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACLY RNA expression–survival associations across cancer types. High ACLY expression shows unfavorable associations in MESO, ACC, UVM, LIHC and CESC, but favorable associations in KIRC. The MESO 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 MESO as the clearest survival context for ACLY RNA expression.
This table summarizes ACLY tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACLY. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACLY shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, COAD, BLCA and LIHC. The KIRC box plot shows higher ACLY RNA expression in tumor versus normal tissue (log2 FC = +1.874, t-test p < 0.001).
This table shows molecular features associated with ACLY in patient tissues and cancer cell lines. In patient samples, ACLY shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ACLY RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
