nucleosome assembly protein 1 like 3Genealiases: MB20 · NPL3
Q-omics provides the consensus-scored NAP1L3 profile across patient tissues and cancer cell-line models. NAP1L3 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, NAP1L3 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, NAP1L3 RNA expression shows 25,067 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LGG, KICH, and GBM as cancer lineages where NAP1L3 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 NAP1L3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NAP1L3 survival associations across molecular data types. NAP1L3 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NAP1L3 RNA expression–survival associations across cancer types. High NAP1L3 expression shows unfavorable associations in BLCA, but favorable associations in LGG, UCS, PAAD, ACC and SKCM. The LGG 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 LGG as the clearest survival context for NAP1L3 RNA expression.
This table summarizes NAP1L3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for NAP1L3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NAP1L3 shows lower tumor expression in KICH, KIRC, THCA, COAD, BLCA and UCEC. The KICH box plot shows higher NAP1L3 RNA expression in normal versus tumor tissue (log2 FC = −2.666, t-test p < 0.001).
This table shows molecular features associated with NAP1L3 in patient tissues and cancer cell lines. In patient samples, NAP1L3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, NAP1L3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and OVARY.
