Q-omics provides the consensus-scored CUTA profile across patient tissues and cancer cell-line models. CUTA expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, CUTA is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, CUTA protein abundance shows 26,209 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight LUAD, COAD, and PDAC as cancer lineages where CUTA 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 CUTA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CUTA survival associations across molecular data types. CUTA RNA expression shows survival associations in the most cancer types (29), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CUTA RNA expression–survival associations across cancer types. High CUTA expression shows unfavorable associations in ACC and LIHC, but favorable associations in LUAD, UVM, KIRC and THYM. The LUAD 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 LUAD as the clearest survival context for CUTA RNA expression.
This table summarizes CUTA 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 6. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CUTA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CUTA shows lower tumor expression in KICH and higher tumor expression in COAD, LIHC, HNSC, KIRC and BRCA. The COAD box plot shows higher CUTA RNA expression in tumor versus normal tissue (log2 FC = +0.706, t-test p < 0.001).
This table shows molecular features associated with CUTA in patient tissues and cancer cell lines. In patient samples, CUTA shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, CUTA 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 BONE and SOFT_TISSUE.
