Q-omics provides the consensus-scored RB1CC1 profile across patient tissues and cancer cell-line models. RB1CC1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, RB1CC1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, RB1CC1 RNA expression shows 21,320 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCS, HNSC, and UVM as cancer lineages where RB1CC1 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 RB1CC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RB1CC1 survival associations across molecular data types. RB1CC1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (11) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RB1CC1 RNA expression–survival associations across cancer types. High RB1CC1 expression shows unfavorable associations in KIRP, KICH and UVM, but favorable associations in UCS, KIRC and SKCM. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify UCS as the clearest survival context for RB1CC1 RNA expression.
This table summarizes RB1CC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RB1CC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RB1CC1 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, CHOL, LUSC and LUAD. The HNSC box plot shows higher RB1CC1 RNA expression in tumor versus normal tissue (log2 FC = +0.759, t-test p < 0.001).
This table shows molecular features associated with RB1CC1 in patient tissues and cancer cell lines. In patient samples, RB1CC1 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, RB1CC1 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 BLOOD_Lymphoma and BLOOD_Leukemia.
