Q-omics provides the consensus-scored CYP4X1 profile across patient tissues and cancer cell-line models. CYP4X1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CYP4X1 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, CYP4X1 RNA expression shows 22,427 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where CYP4X1 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 CYP4X1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CYP4X1 survival associations across molecular data types. CYP4X1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CYP4X1 RNA expression–survival associations across cancer types. High CYP4X1 expression shows unfavorable associations in UVM and KIRP, but favorable associations in KIRC, HNSC, MESO and LUAD. The KIRC 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 KIRC as the clearest survival context for CYP4X1 RNA expression.
This table summarizes CYP4X1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CYP4X1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CYP4X1 shows lower tumor expression in HNSC, KICH, KIRP, THCA and KIRC and higher tumor expression in COAD. The HNSC box plot shows higher CYP4X1 RNA expression in normal versus tumor tissue (log2 FC = −1.951, t-test p < 0.001).
This table shows molecular features associated with CYP4X1 in patient tissues and cancer cell lines. In patient samples, CYP4X1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CYP4X1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in SKIN and OVARY.
