Q-omics provides the consensus-scored FGF12 profile across patient tissues and cancer cell-line models. FGF12 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, FGF12 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, FGF12 RNA expression shows 20,785 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight UVM, and HNSC as cancer lineages where FGF12 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 FGF12 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FGF12 survival associations across molecular data types. FGF12 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (6) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FGF12 RNA expression–survival associations across cancer types. High FGF12 expression shows unfavorable associations in UVM, UCEC, ACC and MESO, but favorable associations in KIRC and LGG. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for FGF12 RNA expression.
This table summarizes FGF12 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 FGF12. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FGF12 shows lower tumor expression in KIRC and THCA and higher tumor expression in HNSC, LIHC, LUSC and CHOL. The HNSC box plot shows higher FGF12 RNA expression in tumor versus normal tissue (log2 FC = +0.818, t-test p = .017).
This table shows molecular features associated with FGF12 in patient tissues and cancer cell lines. In patient samples, FGF12 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, FGF12 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 BLOOD_Leukemia and LARGE_INTESTINE.
