Q-omics provides the consensus-scored NOCT profile across patient tissues and cancer cell-line models. NOCT 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, NOCT is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, NOCT RNA expression shows 19,365 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where NOCT 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 NOCT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NOCT survival associations across molecular data types. NOCT RNA expression shows survival associations in the most cancer types (25), 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 NOCT RNA expression–survival associations across cancer types. High NOCT expression shows unfavorable associations in UVM, BLCA, KIRP, MESO, HNSC and THCA. 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 NOCT RNA expression.
This table summarizes NOCT 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 4. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NOCT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NOCT shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, KIRC, STAD and UCEC. The HNSC box plot shows higher NOCT RNA expression in tumor versus normal tissue (log2 FC = +1.197, t-test p < 0.001).
This table shows molecular features associated with NOCT in patient tissues and cancer cell lines. In patient samples, NOCT 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, NOCT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Myeloma.
