Q-omics provides the consensus-scored NISCH profile across patient tissues and cancer cell-line models. NISCH expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, NISCH is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, NISCH protein abundance shows 27,082 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight UVM, KIRC, and LUAD as cancer lineages where NISCH 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 NISCH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NISCH survival associations across molecular data types. NISCH RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NISCH RNA expression–survival associations across cancer types. High NISCH expression shows unfavorable associations in ACC, KIRC and COAD, but favorable associations in UVM, HNSC and UCS. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for NISCH RNA expression.
This table summarizes NISCH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NISCH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NISCH shows lower tumor expression in KIRC, LUAD, KIRP, BRCA and LUSC and higher tumor expression in LIHC. The KIRC box plot shows higher NISCH RNA expression in normal versus tumor tissue (log2 FC = −0.952, t-test p < 0.001).
This table shows molecular features associated with NISCH in patient tissues and cancer cell lines. In patient samples, NISCH shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, NISCH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
