Q-omics provides the consensus-scored NEUROG3 profile across patient tissues and cancer cell-line models. NEUROG3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, NEUROG3 is differentially expressed in 9, with the highest sampling consensus in COAD. Additionally, NEUROG3 RNA expression shows 9,462 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight UCEC, COAD, and ESCA as cancer lineages where NEUROG3 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 NEUROG3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NEUROG3 survival associations across molecular data types. NEUROG3 RNA expression shows survival associations in the most cancer types (25), 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 NEUROG3 RNA expression–survival associations across cancer types. High NEUROG3 expression shows unfavorable associations in UCEC, KIRC, UVM and COAD, but favorable associations in SKCM and PAAD. The UCEC 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 UCEC as the clearest survival context for NEUROG3 RNA expression.
This table summarizes NEUROG3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for NEUROG3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NEUROG3 shows lower tumor expression in COAD, HNSC, LUSC and LUAD and higher tumor expression in UCEC and KIRC. The COAD box plot shows higher NEUROG3 RNA expression in normal versus tumor tissue (log2 FC = −1.578, t-test p < 0.001).
This table shows molecular features associated with NEUROG3 in patient tissues and cancer cell lines. In patient samples, NEUROG3 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, NEUROG3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BREAST.
