Q-omics provides the consensus-scored CYP2D6 profile across patient tissues and cancer cell-line models. CYP2D6 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, CYP2D6 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, CYP2D6 RNA expression shows 18,257 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KICH, and UVM as cancer lineages where CYP2D6 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 CYP2D6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CYP2D6 survival associations across molecular data types. CYP2D6 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CYP2D6 RNA expression–survival associations across cancer types. High CYP2D6 expression shows unfavorable associations in ACC and KIRC, but favorable associations in HNSC, CESC, UCEC and BLCA. The HNSC 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 HNSC as the clearest survival context for CYP2D6 RNA expression.
This table summarizes CYP2D6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for CYP2D6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CYP2D6 shows lower tumor expression in KICH, CHOL, THCA and LIHC and higher tumor expression in UCEC and LUAD. The KICH box plot shows higher CYP2D6 RNA expression in normal versus tumor tissue (log2 FC = −0.530, t-test p < 0.001).
This table shows molecular features associated with CYP2D6 in patient tissues and cancer cell lines. In patient samples, CYP2D6 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, CYP2D6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
