Q-omics provides the consensus-scored NELFA profile across patient tissues and cancer cell-line models. NELFA expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, NELFA is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, NELFA protein abundance shows 25,697 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCS, COAD, and GBM as cancer lineages where NELFA 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 NELFA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NELFA survival associations across molecular data types. NELFA RNA expression shows survival associations in the most cancer types (19), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NELFA RNA expression–survival associations across cancer types. High NELFA expression shows unfavorable associations in LIHC, PRAD, KICH and LUAD, but favorable associations in UCS and SCLC. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .003). Together, the overview and detailed table identify UCS as the clearest survival context for NELFA RNA expression.
This table summarizes NELFA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for NELFA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NELFA shows higher tumor expression in COAD, LIHC, LUAD, LUSC, STAD and BLCA. The COAD box plot shows higher NELFA RNA expression in tumor versus normal tissue (log2 FC = +1.060, t-test p < 0.001).
This table shows molecular features associated with NELFA in patient tissues and cancer cell lines. In patient samples, NELFA shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, NELFA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
