Q-omics provides the consensus-scored FYCO1 profile across patient tissues and cancer cell-line models. FYCO1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, FYCO1 is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, FYCO1 protein abundance shows 29,562 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, LIHC, and BRCA as cancer lineages where FYCO1 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 FYCO1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FYCO1 survival associations across molecular data types. FYCO1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FYCO1 RNA expression–survival associations across cancer types. High FYCO1 expression shows unfavorable associations in LGG, but favorable associations in KIRC, LUAD, HNSC, UCS and ESCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for FYCO1 RNA expression.
This table summarizes FYCO1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for FYCO1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FYCO1 shows lower tumor expression in BLCA, HNSC, THCA, LUSC and UCEC and higher tumor expression in LIHC. The LIHC box plot shows higher FYCO1 RNA expression in tumor versus normal tissue (log2 FC = +0.971, t-test p < 0.001).
This table shows molecular features associated with FYCO1 in patient tissues and cancer cell lines. In patient samples, FYCO1 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, FYCO1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in OVARY and UPPER_AERODIGESTIVE_TRACT.
