Q-omics provides the consensus-scored PRADC1 profile across patient tissues and cancer cell-line models. PRADC1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PRADC1 is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, PRADC1 RNA expression shows 19,161 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, THCA, and THYM as cancer lineages where PRADC1 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 PRADC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRADC1 survival associations across molecular data types. PRADC1 RNA expression shows survival associations in the most cancer types (24), 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 PRADC1 RNA expression–survival associations across cancer types. High PRADC1 expression shows unfavorable associations in ACC, KICH, BRCA, SKCM and UVM, but favorable associations in KIRP. 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 PRADC1 RNA expression.
This table summarizes PRADC1 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 4. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PRADC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRADC1 shows lower tumor expression in THCA, HNSC, KIRC, COAD and KICH and higher tumor expression in LIHC. The THCA box plot shows higher PRADC1 RNA expression in normal versus tumor tissue (log2 FC = −1.305, t-test p < 0.001).
This table shows molecular features associated with PRADC1 in patient tissues and cancer cell lines. In patient samples, PRADC1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PRADC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
