Q-omics provides the consensus-scored DHFRP3 profile across patient tissues and cancer cell-line models. DHFRP3 expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in TGCT. Additionally, DHFRP3 RNA expression shows 4,746 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight TGCT, and STAD as cancer lineages where DHFRP3 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 DHFRP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DHFRP3 survival associations across molecular data types. DHFRP3 RNA expression shows survival associations in the most cancer types (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DHFRP3 RNA expression–survival associations across cancer types. High DHFRP3 expression shows unfavorable associations in TGCT, DLBC, BRCA, BLCA, PAAD and COAD. The TGCT Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify TGCT as the clearest survival context for DHFRP3 RNA expression.
This table shows molecular features associated with DHFRP3 in patient tissues and cancer cell lines. In patient samples, DHFRP3 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, DHFRP3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in SKIN.
