Q-omics provides the consensus-scored AFDN profile across patient tissues and cancer cell-line models. AFDN expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, AFDN is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, AFDN protein abundance shows 28,129 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight OV, KICH, and LUAD as cancer lineages where AFDN 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 AFDN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AFDN survival associations across molecular data types. AFDN RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AFDN RNA expression–survival associations across cancer types. High AFDN expression shows unfavorable associations in OV, CESC and MESO, but favorable associations in KIRC, UCS and READ. The OV 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 OV as the clearest survival context for AFDN RNA expression.
This table summarizes AFDN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 11. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for AFDN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AFDN shows lower tumor expression in KICH, LUSC, KIRC, HNSC, LUAD and BRCA. The KICH box plot shows higher AFDN RNA expression in normal versus tumor tissue (log2 FC = −1.088, t-test p < 0.001).
This table shows molecular features associated with AFDN in patient tissues and cancer cell lines. In patient samples, AFDN 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, AFDN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LIVER and UPPER_AERODIGESTIVE_TRACT.
