Q-omics provides the consensus-scored NEUROG1 profile across patient tissues and cancer cell-line models. NEUROG1 expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, NEUROG1 is differentially expressed in 3, with the highest sampling consensus in HNSC. Additionally, NEUROG1 RNA expression shows 9,267 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LIHC, HNSC, and TGCT as cancer lineages where NEUROG1 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 NEUROG1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NEUROG1 survival associations across molecular data types. NEUROG1 RNA expression shows survival associations in the most cancer types (15), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NEUROG1 RNA expression–survival associations across cancer types. High NEUROG1 expression shows unfavorable associations in LIHC, ACC, LGG, HNSC and SKCM, but favorable associations in OV. The LIHC 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 LIHC as the clearest survival context for NEUROG1 RNA expression.
This table summarizes NEUROG1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for NEUROG1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NEUROG1 shows higher tumor expression in HNSC, UCEC and LUSC. The HNSC box plot shows higher NEUROG1 RNA expression in tumor versus normal tissue (log2 FC = +0.021, t-test p = .036).
This table shows molecular features associated with NEUROG1 in patient tissues and cancer cell lines. In patient samples, NEUROG1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, NEUROG1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
