cytochrome P450 family 2 subfamily E member 1Genealiases: CPE1 · CYP2E · P450-J · P450C2E
Q-omics provides the consensus-scored CYP2E1 profile across patient tissues and cancer cell-line models. CYP2E1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, CYP2E1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, CYP2E1 RNA expression shows 16,835 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LGG, HNSC, and UVM as cancer lineages where CYP2E1 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 CYP2E1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CYP2E1 survival associations across molecular data types. CYP2E1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CYP2E1 RNA expression–survival associations across cancer types. High CYP2E1 expression shows unfavorable associations in KIRC and CHOL, but favorable associations in LGG, LAML, LUSC and BRCA. The LGG 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 LGG as the clearest survival context for CYP2E1 RNA expression.
This table summarizes CYP2E1 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 2. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CYP2E1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CYP2E1 shows lower tumor expression in HNSC, KIRP, KICH, KIRC, CHOL and LIHC. The HNSC box plot shows higher CYP2E1 RNA expression in normal versus tumor tissue (log2 FC = −1.202, t-test p < 0.001).
This table shows molecular features associated with CYP2E1 in patient tissues and cancer cell lines. In patient samples, CYP2E1 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, CYP2E1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
