Q-omics provides the consensus-scored ACOT4 profile across patient tissues and cancer cell-line models. ACOT4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ACOT4 is differentially expressed in 10, with the highest sampling consensus in KIRP. Additionally, ACOT4 RNA expression shows 16,239 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KIRP, and ACC as cancer lineages where ACOT4 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 ACOT4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACOT4 survival associations across molecular data types. ACOT4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) 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 ACOT4 RNA expression–survival associations across cancer types. High ACOT4 expression shows unfavorable associations in UVM, PAAD and SCLC, but favorable associations in KIRC, BRCA 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 ACOT4 RNA expression.
This table summarizes ACOT4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACOT4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACOT4 shows lower tumor expression in KIRP, COAD and LUSC and higher tumor expression in BLCA, UCEC and BRCA. The KIRP box plot shows higher ACOT4 RNA expression in normal versus tumor tissue (log2 FC = −1.953, t-test p < 0.001).
This table shows molecular features associated with ACOT4 in patient tissues and cancer cell lines. In patient samples, ACOT4 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, ACOT4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SOFT_TISSUE.
