Q-omics provides the consensus-scored FGF3 profile across patient tissues and cancer cell-line models. FGF3 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, FGF3 is differentially expressed in 5, with the highest sampling consensus in LIHC. Additionally, FGF3 RNA expression shows 6,355 significant pathway-activity associations, with the highest sampling consensus in KIRC. Together, these results highlight KIRC, and LIHC as cancer lineages where FGF3 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 FGF3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FGF3 survival associations across molecular data types. FGF3 RNA expression shows survival associations in the most cancer types (14), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FGF3 RNA expression–survival associations across cancer types. High FGF3 expression shows unfavorable associations in KIRC, KICH, LGG, KIRP, LIHC and COAD. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .008). Together, the overview and detailed table identify KIRC as the clearest survival context for FGF3 RNA expression.
This table summarizes FGF3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for FGF3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FGF3 shows higher tumor expression in LIHC, COAD, UCEC, LUSC and LUAD. The LIHC box plot shows higher FGF3 RNA expression in tumor versus normal tissue (log2 FC = +0.052, t-test p < 0.001).
This table shows molecular features associated with FGF3 in patient tissues and cancer cell lines. In patient samples, FGF3 shows the broadest associations at the RNA and protein expression levels, with KIRC recurring as the lineage with the largest associated feature set. In cancer cell lines, FGF3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in CNS and BREAST.
