Q-omics provides the consensus-scored CPQ profile across patient tissues and cancer cell-line models. CPQ expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CPQ is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, CPQ protein abundance shows 24,758 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRC, THCA, and HNSC as cancer lineages where CPQ 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 CPQ — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CPQ survival associations across molecular data types. CPQ RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CPQ RNA expression–survival associations across cancer types. High CPQ expression shows unfavorable associations in LGG, GBM and CESC, but favorable associations in KIRC, ACC and THCA. The KIRC 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 KIRC as the clearest survival context for CPQ RNA expression.
This table summarizes CPQ tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CPQ. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CPQ shows lower tumor expression in THCA, KIRP, LUAD, COAD and BLCA and higher tumor expression in LIHC. The THCA box plot shows higher CPQ RNA expression in normal versus tumor tissue (log2 FC = −2.344, t-test p < 0.001).
This table shows molecular features associated with CPQ in patient tissues and cancer cell lines. In patient samples, CPQ shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, CPQ 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 STOMACH and BONE.
