cytochrome P450 family 2 subfamily W member 1Genealiases: []
Q-omics provides the consensus-scored CYP2W1 profile across patient tissues and cancer cell-line models. CYP2W1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CYP2W1 is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, CYP2W1 RNA expression shows 16,696 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, LIHC, and TGCT as cancer lineages where CYP2W1 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 CYP2W1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CYP2W1 survival associations across molecular data types. CYP2W1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) 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 CYP2W1 RNA expression–survival associations across cancer types. High CYP2W1 expression shows unfavorable associations in KIRP, LUAD, BLCA and KIRC, but favorable associations in UCS and SCLC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRP as the clearest survival context for CYP2W1 RNA expression.
This table summarizes CYP2W1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 1. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CYP2W1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CYP2W1 shows lower tumor expression in KICH and higher tumor expression in LIHC, COAD, STAD, LUSC and BRCA. The LIHC box plot shows higher CYP2W1 RNA expression in tumor versus normal tissue (log2 FC = +0.417, t-test p < 0.001).
This table shows molecular features associated with CYP2W1 in patient tissues and cancer cell lines. In patient samples, CYP2W1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, CYP2W1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and SOFT_TISSUE.
