Q-omics provides the consensus-scored CCDC102A profile across patient tissues and cancer cell-line models. CCDC102A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CCDC102A is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, CCDC102A protein abundance shows 24,627 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight ACC, KICH, and LUAD as cancer lineages where CCDC102A 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 CCDC102A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC102A survival associations across molecular data types. CCDC102A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) 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 CCDC102A RNA expression–survival associations across cancer types. High CCDC102A expression shows unfavorable associations in ACC, LGG, CESC, LAML and MESO, but favorable associations in THYM. The ACC 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 ACC as the clearest survival context for CCDC102A RNA expression.
This table summarizes CCDC102A 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 LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CCDC102A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC102A shows lower tumor expression in KICH and BLCA and higher tumor expression in LIHC, KIRC, KIRP and HNSC. The KICH box plot shows higher CCDC102A RNA expression in normal versus tumor tissue (log2 FC = −2.321, t-test p < 0.001).
This table shows molecular features associated with CCDC102A in patient tissues and cancer cell lines. In patient samples, CCDC102A 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, CCDC102A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in SKIN and SOFT_TISSUE.
