Q-omics provides the consensus-scored UNK profile across patient tissues and cancer cell-line models. UNK expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, UNK is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, UNK protein abundance shows 32,056 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRP, and GBM as cancer lineages where UNK 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 UNK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UNK survival associations across molecular data types. UNK RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UNK RNA expression–survival associations across cancer types. High UNK expression shows unfavorable associations in LIHC, KIRP and KICH, but favorable associations in HNSC, BRCA and PAAD. 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 UNK RNA expression.
This table summarizes UNK tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRP for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for UNK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UNK shows lower tumor expression in THCA and higher tumor expression in KIRP, KIRC, COAD, LIHC and HNSC. The KIRP box plot shows higher UNK RNA expression in tumor versus normal tissue (log2 FC = +0.806, t-test p < 0.001).
This table shows molecular features associated with UNK in patient tissues and cancer cell lines. In patient samples, UNK shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, UNK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Lymphoma.
