Q-omics provides the consensus-scored NUDT2 profile across patient tissues and cancer cell-line models. NUDT2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, NUDT2 is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, NUDT2 RNA expression shows 17,191 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LUAD, LIHC, and ACC as cancer lineages where NUDT2 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 NUDT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NUDT2 survival associations across molecular data types. NUDT2 RNA expression shows survival associations in the most cancer types (22), 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 NUDT2 RNA expression–survival associations across cancer types. High NUDT2 expression shows unfavorable associations in LUAD, KICH, ACC and LIHC, but favorable associations in KIRC and LGG. The LUAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify LUAD as the clearest survival context for NUDT2 RNA expression.
This table summarizes NUDT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NUDT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NUDT2 shows lower tumor expression in UCEC and KICH and higher tumor expression in LIHC, CHOL, LUSC and COAD. The LIHC box plot shows higher NUDT2 RNA expression in tumor versus normal tissue (log2 FC = +1.210, t-test p < 0.001).
This table shows molecular features associated with NUDT2 in patient tissues and cancer cell lines. In patient samples, NUDT2 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, NUDT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Lymphoma.
