Q-omics provides the consensus-scored ACOT9 profile across patient tissues and cancer cell-line models. ACOT9 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ACOT9 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, ACOT9 protein abundance shows 30,392 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight HNSC, and PDAC as cancer lineages where ACOT9 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 ACOT9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACOT9 survival associations across molecular data types. ACOT9 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACOT9 RNA expression–survival associations across cancer types. High ACOT9 expression shows unfavorable associations in HNSC, ACC, LGG, MESO, BRCA and LIHC. The HNSC 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 HNSC as the clearest survival context for ACOT9 RNA expression.
This table summarizes ACOT9 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 11. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ACOT9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACOT9 shows lower tumor expression in KICH and LUSC and higher tumor expression in HNSC, COAD, LIHC and READ. The HNSC box plot shows higher ACOT9 RNA expression in tumor versus normal tissue (log2 FC = +1.662, t-test p < 0.001).
This table shows molecular features associated with ACOT9 in patient tissues and cancer cell lines. In patient samples, ACOT9 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, ACOT9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BONE.
