Q-omics provides the consensus-scored NUDT22 profile across patient tissues and cancer cell-line models. NUDT22 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, NUDT22 is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, NUDT22 RNA expression shows 18,623 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, BLCA, and ACC as cancer lineages where NUDT22 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 NUDT22 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NUDT22 survival associations across molecular data types. NUDT22 RNA expression shows survival associations in the most cancer types (23), 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 NUDT22 RNA expression–survival associations across cancer types. High NUDT22 expression shows unfavorable associations in UVM, ACC, KICH, LGG and KIRC, but favorable associations in KIRP. The UVM 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 UVM as the clearest survival context for NUDT22 RNA expression.
This table summarizes NUDT22 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NUDT22. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NUDT22 shows higher tumor expression in BLCA, LIHC, LUAD, HNSC, UCEC and LUSC. The BLCA box plot shows higher NUDT22 RNA expression in tumor versus normal tissue (log2 FC = +0.875, t-test p < 0.001).
This table shows molecular features associated with NUDT22 in patient tissues and cancer cell lines. In patient samples, NUDT22 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, NUDT22 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and SOFT_TISSUE.
