Q-omics provides the consensus-scored CCNB2 profile across patient tissues and cancer cell-line models. CCNB2 expression is associated with patient survival in 31 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, CCNB2 is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, CCNB2 RNA expression shows 26,957 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight MESO, HNSC, and LSCC as cancer lineages where CCNB2 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 CCNB2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCNB2 survival associations across molecular data types. CCNB2 RNA expression shows survival associations in the most cancer types (31), followed by mutation status (3) 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 CCNB2 RNA expression–survival associations across cancer types. High CCNB2 expression shows unfavorable associations in MESO, KIRP, ACC, KIRC, UVM and KICH. The MESO 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 MESO as the clearest survival context for CCNB2 RNA expression.
This table summarizes CCNB2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CCNB2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCNB2 shows higher tumor expression in HNSC, LUAD, BLCA, KIRP, KIRC and COAD. The HNSC box plot shows higher CCNB2 RNA expression in tumor versus normal tissue (log2 FC = +2.163, t-test p < 0.001).
This table shows molecular features associated with CCNB2 in patient tissues and cancer cell lines. In patient samples, CCNB2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CCNB2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
