Q-omics provides the consensus-scored NOL10 profile across patient tissues and cancer cell-line models. NOL10 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, NOL10 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, NOL10 protein abundance shows 33,314 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, HNSC, and LSCC as cancer lineages where NOL10 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 NOL10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NOL10 survival associations across molecular data types. NOL10 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NOL10 RNA expression–survival associations across cancer types. High NOL10 expression shows unfavorable associations in KIRP, ACC, LIHC, BLCA, MESO and KICH. The KIRP 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 KIRP as the clearest survival context for NOL10 RNA expression.
This table summarizes NOL10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NOL10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NOL10 shows higher tumor expression in HNSC, BLCA, LUAD, STAD, LUSC and LIHC. The HNSC box plot shows higher NOL10 RNA expression in tumor versus normal tissue (log2 FC = +0.950, t-test p < 0.001).
This table shows molecular features associated with NOL10 in patient tissues and cancer cell lines. In patient samples, NOL10 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, NOL10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
