Q-omics provides the consensus-scored CCDC163 profile across patient tissues and cancer cell-line models. CCDC163 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, CCDC163 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, CCDC163 RNA expression shows 18,014 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KICH, KIRC, and UVM as cancer lineages where CCDC163 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 CCDC163 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC163 survival associations across molecular data types. CCDC163 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC163 RNA expression–survival associations across cancer types. High CCDC163 expression shows unfavorable associations in KICH, ACC, LIHC and THCA, but favorable associations in MESO and UCS. The KICH 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 KICH as the clearest survival context for CCDC163 RNA expression.
This table summarizes CCDC163 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for CCDC163. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC163 shows lower tumor expression in THCA and higher tumor expression in KIRC, LIHC, STAD, LUSC and LUAD. The KIRC box plot shows higher CCDC163 RNA expression in tumor versus normal tissue (log2 FC = +0.456, t-test p < 0.001).
This table shows molecular features associated with CCDC163 in patient tissues and cancer cell lines. In patient samples, CCDC163 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, CCDC163 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE.
