Q-omics provides the consensus-scored CCNYL6 profile across patient tissues and cancer cell-line models. CCNYL6 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, CCNYL6 is differentially expressed in 12, with the highest sampling consensus in UCEC. Additionally, CCNYL6 RNA expression shows 18,452 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LUAD, UCEC, and UVM as cancer lineages where CCNYL6 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 CCNYL6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCNYL6 survival associations across molecular data types. CCNYL6 RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCNYL6 RNA expression–survival associations across cancer types. High CCNYL6 expression shows unfavorable associations in UVM, KICH, ACC and LGG, but favorable associations in LUAD and LAML. The LUAD 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 LUAD as the clearest survival context for CCNYL6 RNA expression.
This table summarizes CCNYL6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for CCNYL6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCNYL6 shows higher tumor expression in UCEC, BRCA, BLCA, COAD, STAD and LIHC. The UCEC box plot shows higher CCNYL6 RNA expression in tumor versus normal tissue (log2 FC = +0.223, t-test p = .011).
This table shows molecular features associated with CCNYL6 in patient tissues and cancer cell lines. In patient samples, CCNYL6 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, CCNYL6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD.
