Q-omics provides the consensus-scored NENF profile across patient tissues and cancer cell-line models. NENF expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, NENF is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, NENF protein abundance shows 27,351 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRP, KIRC, and HNSC as cancer lineages where NENF 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 NENF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NENF survival associations across molecular data types. NENF RNA expression shows survival associations in the most cancer types (25), followed by mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NENF RNA expression–survival associations across cancer types. High NENF expression shows unfavorable associations in KIRP, ACC, UVM, LIHC, LGG and SCLC. The KIRP 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 KIRP as the clearest survival context for NENF RNA expression.
This table summarizes NENF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 10. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NENF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NENF shows lower tumor expression in KICH and higher tumor expression in KIRC, LIHC, HNSC, COAD and BRCA. The KIRC box plot shows higher NENF RNA expression in tumor versus normal tissue (log2 FC = +0.530, t-test p < 0.001).
This table shows molecular features associated with NENF in patient tissues and cancer cell lines. In patient samples, NENF 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, NENF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
