Q-omics provides the consensus-scored PRODH2 profile across patient tissues and cancer cell-line models. PRODH2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PRODH2 is differentially expressed in 7, with the highest sampling consensus in KIRP. Additionally, PRODH2 RNA expression shows 8,126 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, and TGCT as cancer lineages where PRODH2 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 PRODH2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRODH2 survival associations across molecular data types. PRODH2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 PRODH2 RNA expression–survival associations across cancer types. High PRODH2 expression shows unfavorable associations in LUAD and ACC, but favorable associations in KIRP, HNSC, PAAD and KIRC. The KIRP Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .006). Together, the overview and detailed table identify KIRP as the clearest survival context for PRODH2 RNA expression.
This table summarizes PRODH2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PRODH2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRODH2 shows lower tumor expression in KIRP, KICH, LIHC, CHOL and KIRC and higher tumor expression in BLCA. The KIRP box plot shows higher PRODH2 RNA expression in normal versus tumor tissue (log2 FC = −4.368, t-test p < 0.001).
This table shows molecular features associated with PRODH2 in patient tissues and cancer cell lines. In patient samples, PRODH2 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, PRODH2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and LIVER.
