Q-omics provides the consensus-scored CCDC9 profile across patient tissues and cancer cell-line models. CCDC9 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CCDC9 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, CCDC9 protein abundance shows 22,173 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where CCDC9 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 CCDC9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC9 survival associations across molecular data types. CCDC9 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC9 RNA expression–survival associations across cancer types. High CCDC9 expression shows unfavorable associations in ACC, MESO, LGG, KIRP and COAD, but favorable associations in SCLC. 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 CCDC9 RNA expression.
This table summarizes CCDC9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CCDC9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC9 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, KIRC, STAD and CHOL. The HNSC box plot shows higher CCDC9 RNA expression in tumor versus normal tissue (log2 FC = +0.821, t-test p < 0.001).
This table shows molecular features associated with CCDC9 in patient tissues and cancer cell lines. In patient samples, CCDC9 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, CCDC9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
