Q-omics provides the consensus-scored COPZ2 profile across patient tissues and cancer cell-line models. COPZ2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, COPZ2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, COPZ2 protein abundance shows 26,369 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, HNSC, and GBM as cancer lineages where COPZ2 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 COPZ2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COPZ2 survival associations across molecular data types. COPZ2 RNA expression shows survival associations in the most cancer types (23), 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 COPZ2 RNA expression–survival associations across cancer types. High COPZ2 expression shows unfavorable associations in KIRP, MESO, KIRC, THCA, LGG and BLCA. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify KIRP as the clearest survival context for COPZ2 RNA expression.
This table summarizes COPZ2 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 8. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for COPZ2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COPZ2 shows lower tumor expression in THCA, BLCA, UCEC and KICH and higher tumor expression in HNSC and KIRC. The HNSC box plot shows higher COPZ2 RNA expression in tumor versus normal tissue (log2 FC = +1.423, t-test p < 0.001).
This table shows molecular features associated with COPZ2 in patient tissues and cancer cell lines. In patient samples, COPZ2 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, COPZ2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and SKIN.
