Q-omics provides the consensus-scored ACAA1 profile across patient tissues and cancer cell-line models. ACAA1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ACAA1 is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, ACAA1 protein abundance shows 25,968 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRP, and PDAC as cancer lineages where ACAA1 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 ACAA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACAA1 survival associations across molecular data types. ACAA1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACAA1 RNA expression–survival associations across cancer types. High ACAA1 expression shows unfavorable associations in ACC, KICH and LGG, but favorable associations in KIRP, KIRC and MESO. 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 ACAA1 RNA expression.
This table summarizes ACAA1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, 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 ACAA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACAA1 shows lower tumor expression in KIRP, KIRC, HNSC, KICH, COAD and LIHC. The KIRP box plot shows higher ACAA1 RNA expression in normal versus tumor tissue (log2 FC = −2.144, t-test p < 0.001).
This table shows molecular features associated with ACAA1 in patient tissues and cancer cell lines. In patient samples, ACAA1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, ACAA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and UPPER_AERODIGESTIVE_TRACT.
