Q-omics provides the consensus-scored FEM1C profile across patient tissues and cancer cell-line models. FEM1C expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, FEM1C is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, FEM1C RNA expression shows 19,572 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LGG, KIRC, and UVM as cancer lineages where FEM1C 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 FEM1C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FEM1C survival associations across molecular data types. FEM1C RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FEM1C RNA expression–survival associations across cancer types. High FEM1C expression shows unfavorable associations in LGG, KICH, UVM and PAAD, but favorable associations in KIRC and READ. The LGG 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 LGG as the clearest survival context for FEM1C RNA expression.
This table summarizes FEM1C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for FEM1C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FEM1C shows lower tumor expression in COAD, LUAD, LUSC and BLCA and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher FEM1C RNA expression in tumor versus normal tissue (log2 FC = +0.820, t-test p < 0.001).
This table shows molecular features associated with FEM1C in patient tissues and cancer cell lines. In patient samples, FEM1C shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, FEM1C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
