Q-omics provides the consensus-scored CCDC166 profile across patient tissues and cancer cell-line models. CCDC166 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, CCDC166 is differentially expressed in 9, with the highest sampling consensus in LUSC. Additionally, CCDC166 RNA expression shows 6,527 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight LIHC, LUSC, and STAD as cancer lineages where CCDC166 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 CCDC166 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC166 survival associations across molecular data types. CCDC166 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC166 RNA expression–survival associations across cancer types. High CCDC166 expression shows unfavorable associations in LIHC, ACC, PRAD, LUAD and PAAD, but favorable associations in LUSC. The LIHC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify LIHC as the clearest survival context for CCDC166 RNA expression.
This table summarizes CCDC166 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in LUSC for RNA.
This table ranks reproducible tumor–normal expression differences for CCDC166. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC166 shows higher tumor expression in LUSC, LIHC, UCEC, STAD, BRCA and COAD. The LUSC box plot shows higher CCDC166 RNA expression in tumor versus normal tissue (log2 FC = +0.081, t-test p < 0.001).
This table shows molecular features associated with CCDC166 in patient tissues and cancer cell lines. In patient samples, CCDC166 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, CCDC166 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
