Q-omics provides the consensus-scored CCDC146 profile across patient tissues and cancer cell-line models. CCDC146 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, CCDC146 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, CCDC146 RNA expression shows 20,374 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KICH, and UVM as cancer lineages where CCDC146 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 CCDC146 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC146 survival associations across molecular data types. CCDC146 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC146 RNA expression–survival associations across cancer types. High CCDC146 expression shows unfavorable associations in LGG and UVM, but favorable associations in HNSC, KIRC, KIRP and LAML. The HNSC 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 HNSC as the clearest survival context for CCDC146 RNA expression.
This table summarizes CCDC146 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for CCDC146. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC146 shows lower tumor expression in KICH, THCA, BLCA, LUAD and BRCA and higher tumor expression in KIRC. The KICH box plot shows higher CCDC146 RNA expression in normal versus tumor tissue (log2 FC = −2.727, t-test p < 0.001).
This table shows molecular features associated with CCDC146 in patient tissues and cancer cell lines. In patient samples, CCDC146 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, CCDC146 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
