Q-omics provides the consensus-scored NOD2 profile across patient tissues and cancer cell-line models. NOD2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, NOD2 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, NOD2 RNA expression shows 18,405 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, KIRC, and GBM as cancer lineages where NOD2 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 NOD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NOD2 survival associations across molecular data types. NOD2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (8) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NOD2 RNA expression–survival associations across cancer types. High NOD2 expression shows unfavorable associations in KIRC, LIHC and UVM, but favorable associations in SKCM, ESCA and UCEC. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for NOD2 RNA expression.
This table summarizes NOD2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for NOD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NOD2 shows higher tumor expression in KIRC, COAD, KIRP, THCA, BRCA and READ. The KIRC box plot shows higher NOD2 RNA expression in tumor versus normal tissue (log2 FC = +1.470, t-test p < 0.001).
This table shows molecular features associated with NOD2 in patient tissues and cancer cell lines. In patient samples, NOD2 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, NOD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
