Q-omics provides the consensus-scored CYP4F2 profile across patient tissues and cancer cell-line models. CYP4F2 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, CYP4F2 is differentially expressed in 6, with the highest sampling consensus in KIRC. Additionally, CYP4F2 RNA expression shows 11,240 significant gene co-expression associations, with the highest sampling consensus in BLCA. Together, these results highlight BRCA, KIRC, and BLCA as cancer lineages where CYP4F2 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 CYP4F2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CYP4F2 survival associations across molecular data types. CYP4F2 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (7) 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 CYP4F2 RNA expression–survival associations across cancer types. High CYP4F2 expression shows unfavorable associations in LUAD, but favorable associations in BRCA, LIHC, UCS, SCLC and LAML. The BRCA 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 BRCA as the clearest survival context for CYP4F2 RNA expression.
This table summarizes CYP4F2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CYP4F2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CYP4F2 shows lower tumor expression in KIRC, KIRP, KICH, LIHC and CHOL and higher tumor expression in LUSC. The KIRC box plot shows higher CYP4F2 RNA expression in normal versus tumor tissue (log2 FC = −2.829, t-test p < 0.001).
This table shows molecular features associated with CYP4F2 in patient tissues and cancer cell lines. In patient samples, CYP4F2 shows the broadest associations at the RNA and protein expression levels, with BLCA recurring as the lineage with the largest associated feature set. In cancer cell lines, CYP4F2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LARGE_INTESTINE.
