Q-omics provides the consensus-scored DEFB123 profile across patient tissues and cancer cell-line models. DEFB123 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in KICH. Additionally, DEFB123 RNA expression shows 9,412 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KICH, and TGCT as cancer lineages where DEFB123 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 DEFB123 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DEFB123 survival associations across molecular data types. DEFB123 RNA expression shows survival associations in the most cancer types (16), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DEFB123 RNA expression–survival associations across cancer types. High DEFB123 expression shows unfavorable associations in KICH, LIHC, UCEC, PAAD and UCS, but favorable associations in HNSC. The KICH 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 KICH as the clearest survival context for DEFB123 RNA expression.
This table shows molecular features associated with DEFB123 in patient tissues and cancer cell lines. In patient samples, DEFB123 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, DEFB123 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 LUNG_NSCLC_LUAD and UPPER_AERODIGESTIVE_TRACT.
