Q-omics provides the consensus-scored CCNF profile across patient tissues and cancer cell-line models. CCNF expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CCNF is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, CCNF RNA expression shows 20,934 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, HNSC, and LSCC as cancer lineages where CCNF 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 CCNF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCNF survival associations across molecular data types. CCNF RNA expression shows survival associations in the most cancer types (28), followed by mutation status (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCNF RNA expression–survival associations across cancer types. High CCNF expression shows unfavorable associations in KIRP, MESO, ACC, KIRC, LIHC and LGG. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRP as the clearest survival context for CCNF RNA expression.
This table summarizes CCNF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for CCNF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCNF shows higher tumor expression in HNSC, COAD, BLCA, KIRP, KIRC and STAD. The HNSC box plot shows higher CCNF RNA expression in tumor versus normal tissue (log2 FC = +1.656, t-test p < 0.001).
This table shows molecular features associated with CCNF in patient tissues and cancer cell lines. In patient samples, CCNF shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CCNF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
