Q-omics provides the consensus-scored NEMF profile across patient tissues and cancer cell-line models. NEMF expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, NEMF is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, NEMF RNA expression shows 21,049 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, and ACC as cancer lineages where NEMF 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 NEMF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NEMF survival associations across molecular data types. NEMF RNA expression shows survival associations in the most cancer types (26), 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 NEMF RNA expression–survival associations across cancer types. High NEMF expression shows unfavorable associations in BLCA, MESO, ACC and UVM, but favorable associations in KIRC and UCS. The KIRC 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 KIRC as the clearest survival context for NEMF RNA expression.
This table summarizes NEMF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NEMF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NEMF shows lower tumor expression in KIRC and THCA and higher tumor expression in LIHC, CHOL, STAD and PAAD. The KIRC box plot shows higher NEMF RNA expression in normal versus tumor tissue (log2 FC = −0.582, t-test p < 0.001).
This table shows molecular features associated with NEMF in patient tissues and cancer cell lines. In patient samples, NEMF 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, NEMF 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 LIVER and BLOOD_Lymphoma.
