Q-omics provides the consensus-scored CCDC93 profile across patient tissues and cancer cell-line models. CCDC93 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, CCDC93 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, CCDC93 protein abundance shows 22,057 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight LIHC, HNSC, and LUAD as cancer lineages where CCDC93 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 CCDC93 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC93 survival associations across molecular data types. CCDC93 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (2) 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 CCDC93 RNA expression–survival associations across cancer types. High CCDC93 expression shows unfavorable associations in LIHC, MESO, ACC, CESC, KICH and KIRP. The LIHC 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 LIHC as the clearest survival context for CCDC93 RNA expression.
This table summarizes CCDC93 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 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CCDC93. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC93 shows lower tumor expression in THCA and BRCA and higher tumor expression in HNSC, LIHC, STAD and CHOL. The HNSC box plot shows higher CCDC93 RNA expression in tumor versus normal tissue (log2 FC = +0.853, t-test p < 0.001).
This table shows molecular features associated with CCDC93 in patient tissues and cancer cell lines. In patient samples, CCDC93 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, CCDC93 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 URINARY_TRACT and BLOOD_Leukemia.
