Q-omics provides the consensus-scored NOBOX profile across patient tissues and cancer cell-line models. NOBOX expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, NOBOX is differentially expressed in 2, with the highest sampling consensus in HNSC. Additionally, NOBOX RNA expression shows 6,559 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight SCLC, HNSC, and STAD as cancer lineages where NOBOX 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 NOBOX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NOBOX survival associations across molecular data types. NOBOX RNA expression shows survival associations in the most cancer types (14), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NOBOX RNA expression–survival associations across cancer types. High NOBOX expression shows unfavorable associations in SCLC, KIRC, MESO and SKCM, but favorable associations in UCS and LUSC. The SCLC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify SCLC as the clearest survival context for NOBOX RNA expression.
This table summarizes NOBOX tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for NOBOX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NOBOX shows higher tumor expression in HNSC and LUSC. The HNSC box plot shows higher NOBOX RNA expression in tumor versus normal tissue (log2 FC = +0.580, t-test p = .013).
This table shows molecular features associated with NOBOX in patient tissues and cancer cell lines. In patient samples, NOBOX shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, NOBOX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and LUNG_SCLC.
