Q-omics provides the consensus-scored NAGA profile across patient tissues and cancer cell-line models. NAGA expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, NAGA is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, NAGA protein abundance shows 20,667 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KICH, KIRC, and PDAC as cancer lineages where NAGA 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 NAGA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NAGA survival associations across molecular data types. NAGA RNA expression shows survival associations in the most cancer types (25), 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 NAGA RNA expression–survival associations across cancer types. High NAGA expression shows unfavorable associations in KICH, LGG, ACC and LIHC, but favorable associations in SCLC and ESCA. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KICH as the clearest survival context for NAGA RNA expression.
This table summarizes NAGA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NAGA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NAGA shows lower tumor expression in COAD and higher tumor expression in KIRC, HNSC, STAD, LIHC and BRCA. The KIRC box plot shows higher NAGA RNA expression in tumor versus normal tissue (log2 FC = +0.736, t-test p < 0.001).
This table shows molecular features associated with NAGA in patient tissues and cancer cell lines. In patient samples, NAGA shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, NAGA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
