Q-omics provides the consensus-scored CCDC85C profile across patient tissues and cancer cell-line models. CCDC85C expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CCDC85C is differentially expressed in 15, with the highest sampling consensus in LIHC. Additionally, CCDC85C RNA expression shows 19,802 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, LIHC, and ACC as cancer lineages where CCDC85C 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 CCDC85C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC85C survival associations across molecular data types. CCDC85C RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC85C RNA expression–survival associations across cancer types. High CCDC85C expression shows unfavorable associations in UVM, LIHC and BLCA, but favorable associations in KIRC, LGG and SCLC. The KIRC 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 KIRC as the clearest survival context for CCDC85C RNA expression.
This table summarizes CCDC85C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CCDC85C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC85C shows lower tumor expression in COAD, READ and KIRC and higher tumor expression in LIHC, HNSC and LUSC. The LIHC box plot shows higher CCDC85C RNA expression in tumor versus normal tissue (log2 FC = +1.165, t-test p < 0.001).
This table shows molecular features associated with CCDC85C in patient tissues and cancer cell lines. In patient samples, CCDC85C 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, CCDC85C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
