Q-omics provides the consensus-scored FGF10 profile across patient tissues and cancer cell-line models. FGF10 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, FGF10 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, FGF10 RNA expression shows 15,219 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight MESO, BLCA, and BRCA as cancer lineages where FGF10 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 FGF10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FGF10 survival associations across molecular data types. FGF10 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FGF10 RNA expression–survival associations across cancer types. High FGF10 expression shows unfavorable associations in MESO, BLCA, DLBC and KIRP, but favorable associations in HNSC and CHOL. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify MESO as the clearest survival context for FGF10 RNA expression.
This table summarizes FGF10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for FGF10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FGF10 shows lower tumor expression in BLCA, LUAD, KIRC, THCA, COAD and KIRP. The BLCA box plot shows higher FGF10 RNA expression in normal versus tumor tissue (log2 FC = −2.798, t-test p < 0.001).
This table shows molecular features associated with FGF10 in patient tissues and cancer cell lines. In patient samples, FGF10 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, FGF10 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 STOMACH and BLOOD_Myeloma.
