unk like zinc fingerGenealiases: C16orf28 · ZC3H5L · ZC3HDC5L
Q-omics provides the consensus-scored UNKL profile across patient tissues and cancer cell-line models. UNKL expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, UNKL is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, UNKL RNA expression shows 20,776 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, COAD, and ACC as cancer lineages where UNKL 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 UNKL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UNKL survival associations across molecular data types. UNKL RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UNKL RNA expression–survival associations across cancer types. High UNKL expression shows unfavorable associations in LIHC, KIRP and ACC, but favorable associations in HNSC, READ and UCS. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for UNKL RNA expression.
This table summarizes UNKL 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for UNKL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UNKL shows lower tumor expression in BRCA and higher tumor expression in COAD, HNSC, LIHC, KIRP and KIRC. The COAD box plot shows higher UNKL RNA expression in tumor versus normal tissue (log2 FC = +0.931, t-test p < 0.001).
This table shows molecular features associated with UNKL in patient tissues and cancer cell lines. In patient samples, UNKL 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, UNKL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and SOFT_TISSUE.
