Q-omics provides the consensus-scored CCDC113 profile across patient tissues and cancer cell-line models. CCDC113 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, CCDC113 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, CCDC113 protein abundance shows 19,868 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight READ, COAD, and LUAD as cancer lineages where CCDC113 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 CCDC113 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC113 survival associations across molecular data types. CCDC113 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC113 RNA expression–survival associations across cancer types. High CCDC113 expression shows unfavorable associations in HNSC, MESO, THCA and BLCA, but favorable associations in READ and ACC. The READ Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify READ as the clearest survival context for CCDC113 RNA expression.
This table summarizes CCDC113 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CCDC113. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC113 shows lower tumor expression in KIRC and KICH and higher tumor expression in COAD, KIRP, BRCA and STAD. The COAD box plot shows higher CCDC113 RNA expression in tumor versus normal tissue (log2 FC = +1.483, t-test p < 0.001).
This table shows molecular features associated with CCDC113 in patient tissues and cancer cell lines. In patient samples, CCDC113 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, CCDC113 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in CNS and SKIN.
