Q-omics provides the consensus-scored NELFE profile across patient tissues and cancer cell-line models. NELFE expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, NELFE is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, NELFE protein abundance shows 27,167 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KICH, KIRC, and LSCC as cancer lineages where NELFE 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 NELFE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NELFE survival associations across molecular data types. NELFE RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 NELFE RNA expression–survival associations across cancer types. High NELFE expression shows unfavorable associations in KICH, ACC, SARC, LIHC and LAML, but favorable associations in READ. The KICH 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 KICH as the clearest survival context for NELFE RNA expression.
This table summarizes NELFE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for NELFE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NELFE shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, KIRP, COAD and LIHC. The KIRC box plot shows higher NELFE RNA expression in tumor versus normal tissue (log2 FC = +0.776, t-test p < 0.001).
This table shows molecular features associated with NELFE in patient tissues and cancer cell lines. In patient samples, NELFE shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, NELFE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
