Q-omics provides the consensus-scored NADK profile across patient tissues and cancer cell-line models. NADK expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, NADK is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, NADK protein abundance shows 23,781 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where NADK 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 NADK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NADK survival associations across molecular data types. NADK RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) 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 NADK RNA expression–survival associations across cancer types. High NADK expression shows unfavorable associations in KIRC, LGG, ACC, KICH and UVM, but favorable associations in MESO. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for NADK RNA expression.
This table summarizes NADK tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NADK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NADK shows lower tumor expression in KICH and higher tumor expression in HNSC, LUAD, STAD, KIRP and BLCA. The HNSC box plot shows higher NADK RNA expression in tumor versus normal tissue (log2 FC = +0.640, t-test p < 0.001).
This table shows molecular features associated with NADK in patient tissues and cancer cell lines. In patient samples, NADK 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, NADK 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 BLOOD_Leukemia and BLOOD_Lymphoma.
