Q-omics provides the consensus-scored CBR1 profile across patient tissues and cancer cell-line models. CBR1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CBR1 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, CBR1 protein abundance shows 20,993 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, KIRC, and PDAC as cancer lineages where CBR1 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 CBR1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CBR1 survival associations across molecular data types. CBR1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) 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 CBR1 RNA expression–survival associations across cancer types. High CBR1 expression shows unfavorable associations in UVM, LGG, LAML and CHOL, but favorable associations in LUSC and THCA. The UVM 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 UVM as the clearest survival context for CBR1 RNA expression.
This table summarizes CBR1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, 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 CBR1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CBR1 shows lower tumor expression in KIRC, THCA and KICH and higher tumor expression in HNSC, LUSC and LIHC. The KIRC box plot shows higher CBR1 RNA expression in normal versus tumor tissue (log2 FC = −0.854, t-test p < 0.001).
This table shows molecular features associated with CBR1 in patient tissues and cancer cell lines. In patient samples, CBR1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, CBR1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SKIN.
