Q-omics provides the consensus-scored UNC50 profile across patient tissues and cancer cell-line models. UNC50 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, UNC50 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, UNC50 RNA expression shows 19,818 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where UNC50 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 UNC50 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UNC50 survival associations across molecular data types. UNC50 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) 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 UNC50 RNA expression–survival associations across cancer types. High UNC50 expression shows unfavorable associations in UVM, LIHC, KIRP, HNSC and CESC, but favorable associations in KIRC. The UVM 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 UVM as the clearest survival context for UNC50 RNA expression.
This table summarizes UNC50 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for UNC50. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UNC50 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, BLCA, COAD and CHOL. The HNSC box plot shows higher UNC50 RNA expression in tumor versus normal tissue (log2 FC = +0.643, t-test p < 0.001).
This table shows molecular features associated with UNC50 in patient tissues and cancer cell lines. In patient samples, UNC50 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, UNC50 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Lymphoma.
