Q-omics provides the consensus-scored ACAD11 profile across patient tissues and cancer cell-line models. ACAD11 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ACAD11 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, ACAD11 RNA expression shows 20,234 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, and UVM as cancer lineages where ACAD11 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 ACAD11 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACAD11 survival associations across molecular data types. ACAD11 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACAD11 RNA expression–survival associations across cancer types. High ACAD11 expression shows unfavorable associations in MESO, KICH, LUSC and COAD, but favorable associations in KIRC and HNSC. 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 ACAD11 RNA expression.
This table summarizes ACAD11 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 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ACAD11. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACAD11 shows lower tumor expression in KIRP, KICH, LIHC and BRCA and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher ACAD11 RNA expression in tumor versus normal tissue (log2 FC = +1.318, t-test p < 0.001).
This table shows molecular features associated with ACAD11 in patient tissues and cancer cell lines. In patient samples, ACAD11 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ACAD11 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 BREAST and UPPER_AERODIGESTIVE_TRACT.
