Q-omics provides the consensus-scored AFDN-DT profile across patient tissues and cancer cell-line models. AFDN-DT expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, AFDN-DT is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, AFDN-DT RNA expression shows 18,287 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight BRCA, HNSC, and TGCT as cancer lineages where AFDN-DT 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-DT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AFDN-DT survival associations across molecular data types. AFDN-DT RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AFDN-DT RNA expression–survival associations across cancer types. High AFDN-DT expression shows unfavorable associations in BRCA, OV, SKCM, UVM and THCA, but favorable associations in READ. The BRCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify BRCA as the clearest survival context for AFDN-DT RNA expression.
This table summarizes AFDN-DT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for AFDN-DT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AFDN-DT shows lower tumor expression in HNSC, KICH and KIRP and higher tumor expression in COAD, LIHC and THCA. The HNSC box plot shows higher AFDN-DT RNA expression in normal versus tumor tissue (log2 FC = −0.605, t-test p < 0.001).
This table shows molecular features associated with AFDN-DT in patient tissues and cancer cell lines. In patient samples, AFDN-DT shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, AFDN-DT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in NCI60_ALL.
