Q-omics provides the consensus-scored CCDC102B profile across patient tissues and cancer cell-line models. CCDC102B expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CCDC102B is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, CCDC102B RNA expression shows 19,039 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, HNSC, and UVM as cancer lineages where CCDC102B 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 CCDC102B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC102B survival associations across molecular data types. CCDC102B RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC102B RNA expression–survival associations across cancer types. High CCDC102B expression shows unfavorable associations in KIRP, BLCA, UVM, UCEC and STAD, but favorable associations in SKCM. The KIRP 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 KIRP as the clearest survival context for CCDC102B RNA expression.
This table summarizes CCDC102B 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 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CCDC102B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC102B shows lower tumor expression in KICH, LUSC and LUAD and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher CCDC102B RNA expression in tumor versus normal tissue (log2 FC = +0.844, t-test p < 0.001).
This table shows molecular features associated with CCDC102B in patient tissues and cancer cell lines. In patient samples, CCDC102B 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, CCDC102B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
