Q-omics provides the consensus-scored DHX36 profile across patient tissues and cancer cell-line models. DHX36 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DHX36 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, DHX36 protein abundance shows 23,054 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where DHX36 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 DHX36 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DHX36 survival associations across molecular data types. DHX36 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DHX36 RNA expression–survival associations across cancer types. High DHX36 expression shows unfavorable associations in ACC, UCEC, KICH and LIHC, but favorable associations in KIRC and BRCA. 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 DHX36 RNA expression.
This table summarizes DHX36 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for DHX36. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DHX36 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, CHOL, LUSC and STAD. The HNSC box plot shows higher DHX36 RNA expression in tumor versus normal tissue (log2 FC = +1.223, t-test p < 0.001).
This table shows molecular features associated with DHX36 in patient tissues and cancer cell lines. In patient samples, DHX36 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, DHX36 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
