Q-omics provides the consensus-scored COPE profile across patient tissues and cancer cell-line models. COPE expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, COPE is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, COPE protein abundance shows 29,644 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCEC, KIRC, and GBM as cancer lineages where COPE 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 COPE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COPE survival associations across molecular data types. COPE RNA expression shows survival associations in the most cancer types (19), followed by mutation status (2) 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 COPE RNA expression–survival associations across cancer types. High COPE expression shows unfavorable associations in ACC, KICH, LGG and LIHC, but favorable associations in UCEC and CESC. The UCEC 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 UCEC as the clearest survival context for COPE RNA expression.
This table summarizes COPE 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 8. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for COPE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COPE shows higher tumor expression in KIRC, COAD, KIRP, LIHC, BLCA and HNSC. The KIRC box plot shows higher COPE RNA expression in tumor versus normal tissue (log2 FC = +0.671, t-test p < 0.001).
This table shows molecular features associated with COPE in patient tissues and cancer cell lines. In patient samples, COPE 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, COPE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SOFT_TISSUE.
