Q-omics provides the consensus-scored DHX32 profile across patient tissues and cancer cell-line models. DHX32 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DHX32 is differentially expressed in 12, with the highest sampling consensus in KIRP. Additionally, DHX32 RNA expression shows 19,425 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRP as cancer lineages where DHX32 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 DHX32 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DHX32 survival associations across molecular data types. DHX32 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DHX32 RNA expression–survival associations across cancer types. High DHX32 expression shows unfavorable associations in ACC, BLCA, PAAD, LUAD, UVM and LIHC. The ACC 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 ACC as the clearest survival context for DHX32 RNA expression.
This table summarizes DHX32 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 6. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DHX32. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DHX32 shows higher tumor expression in KIRP, LUAD, BLCA, KIRC, THCA and BRCA. The KIRP box plot shows higher DHX32 RNA expression in tumor versus normal tissue (log2 FC = +0.483, t-test p < 0.001).
This table shows molecular features associated with DHX32 in patient tissues and cancer cell lines. In patient samples, DHX32 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, DHX32 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 BLOOD_Lymphoma and BLOOD_Leukemia.
