Q-omics provides the consensus-scored NPAT profile across patient tissues and cancer cell-line models. NPAT 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, NPAT is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, NPAT RNA expression shows 21,771 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where NPAT 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 NPAT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NPAT survival associations across molecular data types. NPAT RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) 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 NPAT RNA expression–survival associations across cancer types. High NPAT expression shows unfavorable associations in ACC, but favorable associations in KIRC, HNSC, UCS, READ and CHOL. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for NPAT RNA expression.
This table summarizes NPAT 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 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for NPAT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NPAT shows lower tumor expression in THCA and higher tumor expression in HNSC, STAD, LIHC, LUAD and CHOL. The HNSC box plot shows higher NPAT RNA expression in tumor versus normal tissue (log2 FC = +0.707, t-test p < 0.001).
This table shows molecular features associated with NPAT in patient tissues and cancer cell lines. In patient samples, NPAT 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, NPAT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
