Q-omics provides the consensus-scored HACD1 profile across patient tissues and cancer cell-line models. HACD1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, HACD1 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, HACD1 RNA expression shows 17,198 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KIRC as cancer lineages where HACD1 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 HACD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HACD1 survival associations across molecular data types. HACD1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HACD1 RNA expression–survival associations across cancer types. High HACD1 expression shows unfavorable associations in UVM, HNSC, KIRC, LUAD and READ, but favorable associations in THYM. 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 HACD1 RNA expression.
This table summarizes HACD1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for HACD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HACD1 shows lower tumor expression in KIRC, BLCA, LUAD and LUSC and higher tumor expression in THCA and KIRP. The KIRC box plot shows higher HACD1 RNA expression in normal versus tumor tissue (log2 FC = −1.055, t-test p < 0.001).
This table shows molecular features associated with HACD1 in patient tissues and cancer cell lines. In patient samples, HACD1 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, HACD1 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 BLOOD_Lymphoma and BONE.
