Q-omics provides the consensus-scored NCLN profile across patient tissues and cancer cell-line models. NCLN expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, NCLN is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, NCLN protein abundance shows 20,915 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRC, and HNSC as cancer lineages where NCLN 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 NCLN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NCLN survival associations across molecular data types. NCLN RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) 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 NCLN RNA expression–survival associations across cancer types. High NCLN expression shows unfavorable associations in KIRC, ACC, UVM, MESO and LIHC, but favorable associations in SCLC. The KIRC 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 KIRC as the clearest survival context for NCLN RNA expression.
This table summarizes NCLN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NCLN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NCLN shows higher tumor expression in HNSC, KIRC, COAD, KIRP, STAD and BLCA. The HNSC box plot shows higher NCLN RNA expression in tumor versus normal tissue (log2 FC = +1.363, t-test p < 0.001).
This table shows molecular features associated with NCLN in patient tissues and cancer cell lines. In patient samples, NCLN shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, NCLN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Lymphoma.
