Q-omics provides the consensus-scored AFP profile across patient tissues and cancer cell-line models. AFP expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, AFP is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, AFP RNA expression shows 10,785 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight MESO, HNSC, and TGCT as cancer lineages where AFP 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 AFP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AFP survival associations across molecular data types. AFP RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) 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 AFP RNA expression–survival associations across cancer types. High AFP expression shows unfavorable associations in MESO, HNSC, KIRP, LGG and KICH, but favorable associations in READ. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify MESO as the clearest survival context for AFP RNA expression.
This table summarizes AFP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for AFP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AFP shows lower tumor expression in KICH, BRCA and KIRC and higher tumor expression in HNSC, COAD and LIHC. The HNSC box plot shows higher AFP RNA expression in tumor versus normal tissue (log2 FC = +0.120, t-test p < 0.001).
This table shows molecular features associated with AFP in patient tissues and cancer cell lines. In patient samples, AFP 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, AFP 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 BLOOD_Myeloma and BONE.
