Q-omics provides the consensus-scored NOP10 profile across patient tissues and cancer cell-line models. NOP10 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, NOP10 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, NOP10 protein abundance shows 21,493 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, HNSC, and LSCC as cancer lineages where NOP10 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 NOP10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NOP10 survival associations across molecular data types. NOP10 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NOP10 RNA expression–survival associations across cancer types. High NOP10 expression shows unfavorable associations in UVM, ACC, HNSC, LIHC and KICH, but favorable associations in UCEC. 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 NOP10 RNA expression.
This table summarizes NOP10 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 6. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for NOP10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NOP10 shows higher tumor expression in HNSC, KIRC, BLCA, LIHC, UCEC and KIRP. The HNSC box plot shows higher NOP10 RNA expression in tumor versus normal tissue (log2 FC = +1.081, t-test p < 0.001).
This table shows molecular features associated with NOP10 in patient tissues and cancer cell lines. In patient samples, NOP10 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, NOP10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BLOOD_Leukemia.
