Q-omics provides the consensus-scored FLG profile across patient tissues and cancer cell-line models. FLG expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, FLG is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, FLG RNA expression shows 15,759 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight BLCA, KIRC, and THYM as cancer lineages where FLG 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 FLG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FLG survival associations across molecular data types. FLG RNA expression shows survival associations in the most cancer types (23), followed by mutation status (18) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FLG RNA expression–survival associations across cancer types. High FLG expression shows unfavorable associations in BLCA, CHOL, SKCM and LUAD, but favorable associations in UCS and LGG. The BLCA 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 BLCA as the clearest survival context for FLG RNA expression.
This table summarizes FLG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for FLG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FLG shows lower tumor expression in KIRC, UCEC and BRCA and higher tumor expression in LIHC, LUSC and CHOL. The KIRC box plot shows higher FLG RNA expression in normal versus tumor tissue (log2 FC = −0.510, t-test p < 0.001).
This table shows molecular features associated with FLG in patient tissues and cancer cell lines. In patient samples, FLG shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, FLG 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 BLOOD_Lymphoma and BLOOD_Leukemia.
