Q-omics provides the consensus-scored NUP50 profile across patient tissues and cancer cell-line models. NUP50 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NUP50 is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, NUP50 protein abundance shows 24,193 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, THCA, and GBM as cancer lineages where NUP50 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 NUP50 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NUP50 survival associations across molecular data types. NUP50 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) 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 NUP50 RNA expression–survival associations across cancer types. High NUP50 expression shows unfavorable associations in ACC, LIHC, LUAD, SARC and KIRP, but favorable associations in LUSC. The ACC 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 ACC as the clearest survival context for NUP50 RNA expression.
This table summarizes NUP50 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NUP50. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NUP50 shows lower tumor expression in THCA and higher tumor expression in HNSC, BLCA, STAD, LUSC and BRCA. The THCA box plot shows higher NUP50 RNA expression in normal versus tumor tissue (log2 FC = −1.132, t-test p < 0.001).
This table shows molecular features associated with NUP50 in patient tissues and cancer cell lines. In patient samples, NUP50 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, NUP50 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and STOMACH.
