acyl-CoA dehydrogenase very long chainGenealiases: ACAD6 · LCACD · VLCAD
Q-omics provides the consensus-scored ACADVL profile across patient tissues and cancer cell-line models. ACADVL expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ACADVL is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, ACADVL RNA expression shows 17,560 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and HNSC as cancer lineages where ACADVL 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 ACADVL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACADVL survival associations across molecular data types. ACADVL RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACADVL RNA expression–survival associations across cancer types. High ACADVL expression shows unfavorable associations in UVM, UCS, ACC, LGG and CHOL, but favorable associations in BRCA. The UVM 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 UVM as the clearest survival context for ACADVL RNA expression.
This table summarizes ACADVL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACADVL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACADVL shows lower tumor expression in HNSC, KICH, COAD, BRCA and READ and higher tumor expression in UCEC. The HNSC box plot shows higher ACADVL RNA expression in normal versus tumor tissue (log2 FC = −1.013, t-test p < 0.001).
This table shows molecular features associated with ACADVL in patient tissues and cancer cell lines. In patient samples, ACADVL 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, ACADVL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and UPPER_AERODIGESTIVE_TRACT.
