Q-omics provides the consensus-scored FGF19 profile across patient tissues and cancer cell-line models. FGF19 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, FGF19 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, FGF19 RNA expression shows 8,231 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight BRCA, HNSC, and TGCT as cancer lineages where FGF19 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 FGF19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FGF19 survival associations across molecular data types. FGF19 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FGF19 RNA expression–survival associations across cancer types. High FGF19 expression shows unfavorable associations in LUAD, COAD, HNSC and UVM, but favorable associations in BRCA and ESCA. The BRCA 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 BRCA as the clearest survival context for FGF19 RNA expression.
This table summarizes FGF19 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 1. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for FGF19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FGF19 shows lower tumor expression in BRCA and higher tumor expression in HNSC, COAD, UCEC, LUSC and STAD. The HNSC box plot shows higher FGF19 RNA expression in tumor versus normal tissue (log2 FC = +0.756, t-test p < 0.001).
This table shows molecular features associated with FGF19 in patient tissues and cancer cell lines. In patient samples, FGF19 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, FGF19 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Lymphoma.
