Q-omics provides the consensus-scored FMO2 profile across patient tissues and cancer cell-line models. FMO2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, FMO2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, FMO2 RNA expression shows 19,653 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, HNSC, and LUAD as cancer lineages where FMO2 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 FMO2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FMO2 survival associations across molecular data types. FMO2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) 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 FMO2 RNA expression–survival associations across cancer types. High FMO2 expression shows unfavorable associations in OV, but favorable associations in KIRC, SKCM, LUAD, HNSC and ESCA. 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 FMO2 RNA expression.
This table summarizes FMO2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for FMO2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FMO2 shows lower tumor expression in HNSC, KICH, LUAD, THCA, COAD and LUSC. The HNSC box plot shows higher FMO2 RNA expression in normal versus tumor tissue (log2 FC = −4.026, t-test p < 0.001).
This table shows molecular features associated with FMO2 in patient tissues and cancer cell lines. In patient samples, FMO2 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, FMO2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LARGE_INTESTINE.
