Q-omics provides the consensus-scored NUDC profile across patient tissues and cancer cell-line models. NUDC expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, NUDC is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, NUDC protein abundance shows 21,142 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, COAD, and GBM as cancer lineages where NUDC 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 NUDC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NUDC survival associations across molecular data types. NUDC RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) 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 NUDC RNA expression–survival associations across cancer types. High NUDC expression shows unfavorable associations in LIHC, LGG, MESO, ACC and LAML, but favorable associations in SCLC. The LIHC 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 LIHC as the clearest survival context for NUDC RNA expression.
This table summarizes NUDC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NUDC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NUDC shows lower tumor expression in KICH and higher tumor expression in COAD, HNSC, LIHC, STAD and LUSC. The COAD box plot shows higher NUDC RNA expression in tumor versus normal tissue (log2 FC = +0.998, t-test p < 0.001).
This table shows molecular features associated with NUDC in patient tissues and cancer cell lines. In patient samples, NUDC 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, NUDC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
