Q-omics provides the consensus-scored NAE1 profile across patient tissues and cancer cell-line models. NAE1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, NAE1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, NAE1 RNA expression shows 20,455 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, HNSC, and ACC as cancer lineages where NAE1 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 NAE1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NAE1 survival associations across molecular data types. NAE1 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) 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 NAE1 RNA expression–survival associations across cancer types. High NAE1 expression shows unfavorable associations in LIHC, ACC, HNSC, SARC and KIRP, but favorable associations in READ. The LIHC 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 LIHC as the clearest survival context for NAE1 RNA expression.
This table summarizes NAE1 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 4. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NAE1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NAE1 shows higher tumor expression in HNSC, BLCA, LIHC, COAD, KIRP and LUSC. The HNSC box plot shows higher NAE1 RNA expression in tumor versus normal tissue (log2 FC = +0.827, t-test p < 0.001).
This table shows molecular features associated with NAE1 in patient tissues and cancer cell lines. In patient samples, NAE1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, NAE1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
