Q-omics provides the consensus-scored NAA60 profile across patient tissues and cancer cell-line models. NAA60 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, NAA60 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, NAA60 RNA expression shows 17,579 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UCEC, KICH, and ACC as cancer lineages where NAA60 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 NAA60 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NAA60 survival associations across molecular data types. NAA60 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) 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 NAA60 RNA expression–survival associations across cancer types. High NAA60 expression shows unfavorable associations in ACC, UVM and BLCA, but favorable associations in UCEC, BRCA and CESC. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify UCEC as the clearest survival context for NAA60 RNA expression.
This table summarizes NAA60 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NAA60. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NAA60 shows lower tumor expression in KICH and higher tumor expression in LIHC, HNSC, STAD, KIRP and BRCA. The KICH box plot shows higher NAA60 RNA expression in normal versus tumor tissue (log2 FC = −0.838, t-test p < 0.001).
This table shows molecular features associated with NAA60 in patient tissues and cancer cell lines. In patient samples, NAA60 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, NAA60 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 OVARY and UPPER_AERODIGESTIVE_TRACT.
