Q-omics provides the consensus-scored NUP160 profile across patient tissues and cancer cell-line models. NUP160 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NUP160 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, NUP160 protein abundance shows 31,097 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where NUP160 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 NUP160 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NUP160 survival associations across molecular data types. NUP160 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NUP160 RNA expression–survival associations across cancer types. High NUP160 expression shows unfavorable associations in ACC, MESO, LIHC and LGG, but favorable associations in KIRC and UCS. 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 NUP160 RNA expression.
This table summarizes NUP160 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for NUP160. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NUP160 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, COAD, STAD and BLCA. The HNSC box plot shows higher NUP160 RNA expression in tumor versus normal tissue (log2 FC = +0.908, t-test p < 0.001).
This table shows molecular features associated with NUP160 in patient tissues and cancer cell lines. In patient samples, NUP160 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, NUP160 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
