Q-omics provides the consensus-scored NRF1 profile across patient tissues and cancer cell-line models. NRF1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, NRF1 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, NRF1 protein abundance shows 27,026 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SCLC, COAD, and GBM as cancer lineages where NRF1 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 NRF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NRF1 survival associations across molecular data types. NRF1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 NRF1 RNA expression–survival associations across cancer types. High NRF1 expression shows unfavorable associations in KICH, ACC, LIHC and MESO, but favorable associations in SCLC and UCS. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify SCLC as the clearest survival context for NRF1 RNA expression.
This table summarizes NRF1 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 6. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NRF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NRF1 shows lower tumor expression in KICH and THCA and higher tumor expression in COAD, LIHC, HNSC and STAD. The COAD box plot shows higher NRF1 RNA expression in tumor versus normal tissue (log2 FC = +0.394, t-test p < 0.001).
This table shows molecular features associated with NRF1 in patient tissues and cancer cell lines. In patient samples, NRF1 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, NRF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
