Q-omics provides the consensus-scored WDR73 profile across patient tissues and cancer cell-line models. WDR73 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, WDR73 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, WDR73 RNA expression shows 21,493 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCS, KICH, and UVM as cancer lineages where WDR73 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 WDR73 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WDR73 survival associations across molecular data types. WDR73 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WDR73 RNA expression–survival associations across cancer types. High WDR73 expression shows unfavorable associations in LGG, UVM and KICH, but favorable associations in UCS, UCEC and READ. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .010). Together, the overview and detailed table identify UCS as the clearest survival context for WDR73 RNA expression.
This table summarizes WDR73 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for WDR73. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WDR73 shows lower tumor expression in KICH and THCA and higher tumor expression in LIHC, HNSC, COAD and CHOL. The KICH box plot shows higher WDR73 RNA expression in normal versus tumor tissue (log2 FC = −0.821, t-test p < 0.001).
This table shows molecular features associated with WDR73 in patient tissues and cancer cell lines. In patient samples, WDR73 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, WDR73 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 BLOOD_Lymphoma and BLOOD_Leukemia.
