Q-omics provides the consensus-scored CFD profile across patient tissues and cancer cell-line models. CFD expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CFD is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, CFD protein abundance shows 22,025 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight UVM, BLCA, and BRCA as cancer lineages where CFD 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 CFD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CFD survival associations across molecular data types. CFD RNA expression shows survival associations in the most cancer types (28), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CFD RNA expression–survival associations across cancer types. High CFD expression shows unfavorable associations in UVM, ACC and LGG, but favorable associations in SKCM, ESCA and READ. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for CFD RNA expression.
This table summarizes CFD tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CFD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CFD shows lower tumor expression in BLCA, HNSC, THCA, COAD, LUAD and LUSC. The BLCA box plot shows higher CFD RNA expression in normal versus tumor tissue (log2 FC = −5.597, t-test p < 0.001).
This table shows molecular features associated with CFD in patient tissues and cancer cell lines. In patient samples, CFD 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, CFD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
