Q-omics provides the consensus-scored DHX8 profile across patient tissues and cancer cell-line models. DHX8 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DHX8 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, DHX8 protein abundance shows 30,341 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where DHX8 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 DHX8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DHX8 survival associations across molecular data types. DHX8 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DHX8 RNA expression–survival associations across cancer types. High DHX8 expression shows unfavorable associations in ACC, MESO, LIHC, UVM and PAAD, but favorable associations in KIRC. 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 DHX8 RNA expression.
This table summarizes DHX8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DHX8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DHX8 shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRP, BLCA, LIHC and COAD. The HNSC box plot shows higher DHX8 RNA expression in tumor versus normal tissue (log2 FC = +0.846, t-test p < 0.001).
This table shows molecular features associated with DHX8 in patient tissues and cancer cell lines. In patient samples, DHX8 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, DHX8 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 BLOOD_Leukemia and LARGE_INTESTINE.
