Q-omics provides the consensus-scored CCDC66 profile across patient tissues and cancer cell-line models. CCDC66 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CCDC66 is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, CCDC66 RNA expression shows 21,545 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where CCDC66 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 CCDC66 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC66 survival associations across molecular data types. CCDC66 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (9) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC66 RNA expression–survival associations across cancer types. High CCDC66 expression shows unfavorable associations in ACC, KIRC, LIHC and KICH, but favorable associations in BRCA and UCS. The ACC 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 ACC as the clearest survival context for CCDC66 RNA expression.
This table summarizes CCDC66 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for CCDC66. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC66 shows lower tumor expression in KIRC, THCA and KICH and higher tumor expression in LIHC, CHOL and COAD. The LIHC box plot shows higher CCDC66 RNA expression in tumor versus normal tissue (log2 FC = +0.670, t-test p < 0.001).
This table shows molecular features associated with CCDC66 in patient tissues and cancer cell lines. In patient samples, CCDC66 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, CCDC66 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
