cytochrome P450 family 4 subfamily F member 8Genealiases: CPF8 · CYPIVF8
Q-omics provides the consensus-scored CYP4F8 profile across patient tissues and cancer cell-line models. CYP4F8 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, CYP4F8 is differentially expressed in 5, with the highest sampling consensus in COAD. Additionally, CYP4F8 RNA expression shows 6,461 significant pathway-activity associations, with the highest sampling consensus in BRCA. Together, these results highlight BLCA, COAD, and BRCA as cancer lineages where CYP4F8 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 CYP4F8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CYP4F8 survival associations across molecular data types. CYP4F8 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CYP4F8 RNA expression–survival associations across cancer types. High CYP4F8 expression shows unfavorable associations in UCEC and UVM, but favorable associations in BLCA, HNSC, ACC and CESC. The BLCA 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 BLCA as the clearest survival context for CYP4F8 RNA expression.
This table summarizes CYP4F8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for CYP4F8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CYP4F8 shows lower tumor expression in PRAD and higher tumor expression in COAD, STAD, LUSC and LUAD. The COAD box plot shows higher CYP4F8 RNA expression in tumor versus normal tissue (log2 FC = +0.124, t-test p < 0.001).
This table shows molecular features associated with CYP4F8 in patient tissues and cancer cell lines. In patient samples, CYP4F8 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, CYP4F8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and URINARY_TRACT.
