Q-omics provides the consensus-scored DBX1 profile across patient tissues and cancer cell-line models. DBX1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DBX1 is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, DBX1 protein abundance shows 22,065 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where DBX1 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 DBX1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DBX1 survival associations across molecular data types. DBX1 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3) 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 DBX1 RNA expression–survival associations across cancer types. High DBX1 expression shows unfavorable associations in KIRC, CESC and BRCA, but favorable associations in LIHC, SCLC and UCS. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for DBX1 RNA expression.
This table summarizes DBX1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for DBX1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DBX1 shows lower tumor expression in BRCA and STAD and higher tumor expression in HNSC, LUSC and COAD. The HNSC box plot shows higher DBX1 RNA expression in tumor versus normal tissue (log2 FC = +0.098, t-test p = .040).
This table shows molecular features associated with DBX1 in patient tissues and cancer cell lines. In patient samples, DBX1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, DBX1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_SCLC.
