Q-omics provides the consensus-scored ACOT13 profile across patient tissues and cancer cell-line models. ACOT13 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, ACOT13 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, ACOT13 protein abundance shows 24,971 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight OV, HNSC, and PDAC as cancer lineages where ACOT13 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 ACOT13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACOT13 survival associations across molecular data types. ACOT13 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) 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 ACOT13 RNA expression–survival associations across cancer types. High ACOT13 expression shows unfavorable associations in KICH, HNSC, ESCA and STAD, but favorable associations in OV and KIRC. The OV 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 OV as the clearest survival context for ACOT13 RNA expression.
This table summarizes ACOT13 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 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACOT13. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACOT13 shows lower tumor expression in KICH, COAD and KIRP and higher tumor expression in HNSC, BLCA and UCEC. The HNSC box plot shows higher ACOT13 RNA expression in tumor versus normal tissue (log2 FC = +0.791, t-test p < 0.001).
This table shows molecular features associated with ACOT13 in patient tissues and cancer cell lines. In patient samples, ACOT13 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, ACOT13 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 SOFT_TISSUE and BLOOD_Myeloma.
