cytochrome P450 family 2 subfamily B member 6Genealiases: CPB6 · CYP2B · CYP2B7 · CYPIIB6 · EFVM · IIB1
Q-omics provides the consensus-scored CYP2B6 profile across patient tissues and cancer cell-line models. CYP2B6 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CYP2B6 is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, CYP2B6 RNA expression shows 11,686 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight ACC, KIRP, and ESCA as cancer lineages where CYP2B6 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 CYP2B6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CYP2B6 survival associations across molecular data types. CYP2B6 RNA expression shows survival associations in the most cancer types (14), followed by mutation status (5) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CYP2B6 RNA expression–survival associations across cancer types. High CYP2B6 expression shows unfavorable associations in ACC, ESCA and DLBC, but favorable associations in LIHC, THCA and SCLC. The ACC 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 ACC as the clearest survival context for CYP2B6 RNA expression.
This table summarizes CYP2B6 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 1. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CYP2B6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CYP2B6 shows lower tumor expression in KIRP, KIRC, KICH, LIHC and CHOL and higher tumor expression in STAD. The KIRP box plot shows higher CYP2B6 RNA expression in normal versus tumor tissue (log2 FC = −3.854, t-test p < 0.001).
This table shows molecular features associated with CYP2B6 in patient tissues and cancer cell lines. In patient samples, CYP2B6 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, CYP2B6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and LARGE_INTESTINE.
