Q-omics provides the consensus-scored NAA35 profile across patient tissues and cancer cell-line models. NAA35 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NAA35 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, NAA35 RNA expression shows 20,754 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where NAA35 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 NAA35 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NAA35 survival associations across molecular data types. NAA35 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NAA35 RNA expression–survival associations across cancer types. High NAA35 expression shows unfavorable associations in ACC, LIHC, BLCA and MESO, but favorable associations in KIRC and SCLC. 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 NAA35 RNA expression.
This table summarizes NAA35 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NAA35. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NAA35 shows lower tumor expression in THCA and KIRC and higher tumor expression in HNSC, LIHC, BRCA and LUAD. The HNSC box plot shows higher NAA35 RNA expression in tumor versus normal tissue (log2 FC = +0.804, t-test p < 0.001).
This table shows molecular features associated with NAA35 in patient tissues and cancer cell lines. In patient samples, NAA35 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, NAA35 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 BLOOD_Lymphoma and BLOOD_Leukemia.
