Q-omics provides the consensus-scored CCNQ profile across patient tissues and cancer cell-line models. CCNQ expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CCNQ is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, CCNQ RNA expression shows 18,088 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, HNSC, and THYM as cancer lineages where CCNQ 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 CCNQ — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCNQ survival associations across molecular data types. CCNQ RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCNQ RNA expression–survival associations across cancer types. High CCNQ expression shows unfavorable associations in ACC, BRCA, HNSC, LIHC, KICH and ESCA. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify ACC as the clearest survival context for CCNQ RNA expression.
This table summarizes CCNQ tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CCNQ. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCNQ shows higher tumor expression in HNSC, COAD, BLCA, LIHC, STAD and LUSC. The HNSC box plot shows higher CCNQ RNA expression in tumor versus normal tissue (log2 FC = +1.414, t-test p < 0.001).
This table shows molecular features associated with CCNQ in patient tissues and cancer cell lines. In patient samples, CCNQ shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, CCNQ 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 CNS and OESOPHAGUS.
