Q-omics provides the consensus-scored RAD51D profile across patient tissues and cancer cell-line models. RAD51D expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RAD51D is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, RAD51D RNA expression shows 20,455 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where RAD51D 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 RAD51D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RAD51D survival associations across molecular data types. RAD51D RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RAD51D RNA expression–survival associations across cancer types. High RAD51D expression shows unfavorable associations in ACC, LIHC, KIRP, KICH and MESO, but favorable associations in SCLC. 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 RAD51D RNA expression.
This table summarizes RAD51D tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for RAD51D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RAD51D shows lower tumor expression in THCA and higher tumor expression in HNSC, COAD, STAD, BLCA and KIRC. The HNSC box plot shows higher RAD51D RNA expression in tumor versus normal tissue (log2 FC = +1.007, t-test p < 0.001).
This table shows molecular features associated with RAD51D in patient tissues and cancer cell lines. In patient samples, RAD51D 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, RAD51D 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 LUNG_SCLC and BLOOD_Leukemia.
