Q-omics provides the consensus-scored NRGN profile across patient tissues and cancer cell-line models. NRGN expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NRGN is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, NRGN protein abundance shows 25,120 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KICH, and GBM as cancer lineages where NRGN 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 NRGN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NRGN survival associations across molecular data types. NRGN RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) 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 NRGN RNA expression–survival associations across cancer types. High NRGN expression shows unfavorable associations in ACC, UVM, MESO and LAML, but favorable associations in UCEC and PAAD. The ACC 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 ACC as the clearest survival context for NRGN RNA expression.
This table summarizes NRGN 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 3. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NRGN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NRGN shows lower tumor expression in KICH, LUAD, KIRP and LUSC and higher tumor expression in LIHC and HNSC. The KICH box plot shows higher NRGN RNA expression in normal versus tumor tissue (log2 FC = −2.812, t-test p < 0.001).
This table shows molecular features associated with NRGN in patient tissues and cancer cell lines. In patient samples, NRGN 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, NRGN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and SKIN.
