Q-omics provides the consensus-scored CC2D1B profile across patient tissues and cancer cell-line models. CC2D1B expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, CC2D1B is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, CC2D1B RNA expression shows 19,907 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, HNSC, and ACC as cancer lineages where CC2D1B 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 CC2D1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CC2D1B survival associations across molecular data types. CC2D1B RNA expression shows survival associations in the most cancer types (26), 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 CC2D1B RNA expression–survival associations across cancer types. High CC2D1B expression shows unfavorable associations in LIHC, LGG, KIRC, KICH, CESC and MESO. 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 CC2D1B RNA expression.
This table summarizes CC2D1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CC2D1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CC2D1B shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, BLCA, STAD and KIRP. The HNSC box plot shows higher CC2D1B RNA expression in tumor versus normal tissue (log2 FC = +0.758, t-test p < 0.001).
This table shows molecular features associated with CC2D1B in patient tissues and cancer cell lines. In patient samples, CC2D1B shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, CC2D1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and SKIN.
