Q-omics provides the consensus-scored NAGPA profile across patient tissues and cancer cell-line models. NAGPA expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, NAGPA is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, NAGPA RNA expression shows 17,593 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KICH, HNSC, and UVM as cancer lineages where NAGPA 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 NAGPA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NAGPA survival associations across molecular data types. NAGPA RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NAGPA RNA expression–survival associations across cancer types. High NAGPA expression shows unfavorable associations in KICH, LIHC, UCS, UVM, LGG and KIRC. The KICH 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 KICH as the clearest survival context for NAGPA RNA expression.
This table summarizes NAGPA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NAGPA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NAGPA shows higher tumor expression in HNSC, KIRC, KIRP, LIHC, STAD and THCA. The HNSC box plot shows higher NAGPA RNA expression in tumor versus normal tissue (log2 FC = +1.188, t-test p < 0.001).
This table shows molecular features associated with NAGPA in patient tissues and cancer cell lines. In patient samples, NAGPA shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, NAGPA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and UPPER_AERODIGESTIVE_TRACT.
