Q-omics provides the consensus-scored CCND1 profile across patient tissues and cancer cell-line models. CCND1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CCND1 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, CCND1 RNA expression shows 19,823 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, and UVM as cancer lineages where CCND1 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 CCND1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCND1 survival associations across molecular data types. CCND1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 CCND1 RNA expression–survival associations across cancer types. High CCND1 expression shows unfavorable associations in HNSC, MESO, UVM, ACC and PAAD, but favorable associations in KIRC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for CCND1 RNA expression.
This table summarizes CCND1 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CCND1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCND1 shows higher tumor expression in KIRC, COAD, THCA, STAD, READ and CHOL. The KIRC box plot shows higher CCND1 RNA expression in tumor versus normal tissue (log2 FC = +2.365, t-test p < 0.001).
This table shows molecular features associated with CCND1 in patient tissues and cancer cell lines. In patient samples, CCND1 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, CCND1 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 LARGE_INTESTINE and BREAST.
