Q-omics provides the consensus-scored HACD2 profile across patient tissues and cancer cell-line models. HACD2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HACD2 is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, HACD2 RNA expression shows 18,978 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight MESO, HNSC, and THYM as cancer lineages where HACD2 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 HACD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HACD2 survival associations across molecular data types. HACD2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) 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 HACD2 RNA expression–survival associations across cancer types. High HACD2 expression shows unfavorable associations in MESO, PAAD and BLCA, but favorable associations in KIRC, LUAD and UVM. The MESO 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 MESO as the clearest survival context for HACD2 RNA expression.
This table summarizes HACD2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for HACD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HACD2 shows lower tumor expression in KIRC, THCA and KICH and higher tumor expression in HNSC, BLCA and LIHC. The HNSC box plot shows higher HACD2 RNA expression in tumor versus normal tissue (log2 FC = +0.996, t-test p < 0.001).
This table shows molecular features associated with HACD2 in patient tissues and cancer cell lines. In patient samples, HACD2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, HACD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
