Q-omics provides the consensus-scored FEN1 profile across patient tissues and cancer cell-line models. FEN1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, FEN1 is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, FEN1 protein abundance shows 31,295 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, BLCA, and LSCC as cancer lineages where FEN1 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 FEN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FEN1 survival associations across molecular data types. FEN1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) 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 FEN1 RNA expression–survival associations across cancer types. High FEN1 expression shows unfavorable associations in ACC, MESO, KIRP, KICH and LIHC, but favorable associations in OV. The ACC 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 ACC as the clearest survival context for FEN1 RNA expression.
This table summarizes FEN1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for FEN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FEN1 shows higher tumor expression in BLCA, HNSC, KIRC, COAD, KIRP and LIHC. The BLCA box plot shows higher FEN1 RNA expression in tumor versus normal tissue (log2 FC = +2.147, t-test p < 0.001).
This table shows molecular features associated with FEN1 in patient tissues and cancer cell lines. In patient samples, FEN1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, FEN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
