Q-omics provides the consensus-scored DEFB121 profile across patient tissues and cancer cell-line models. DEFB121 expression is associated with patient survival in 10 of 34 cancer types, with the highest sampling consensus in UCS. Additionally, DEFB121 RNA expression shows 5,619 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight UCS, and STAD as cancer lineages where DEFB121 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 DEFB121 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DEFB121 survival associations across molecular data types. DEFB121 RNA expression shows survival associations in the most cancer types (10), 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 DEFB121 RNA expression–survival associations across cancer types. High DEFB121 expression shows unfavorable associations in UCS, KIRC, THCA, KIRP, BRCA and DLBC. The UCS 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 UCS as the clearest survival context for DEFB121 RNA expression.
This table shows molecular features associated with DEFB121 in patient tissues and cancer cell lines. In patient samples, DEFB121 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, DEFB121 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 KIDNEY.
