Q-omics provides the consensus-scored DGKB profile across patient tissues and cancer cell-line models. DGKB expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DGKB is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, DGKB protein abundance shows 34,285 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRP, and GBM as cancer lineages where DGKB 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 DGKB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DGKB survival associations across molecular data types. DGKB RNA expression shows survival associations in the most cancer types (26), followed by mutation status (10) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DGKB RNA expression–survival associations across cancer types. High DGKB expression shows unfavorable associations in ACC, BLCA and UVM, but favorable associations in KIRC, LUSC and LGG. The ACC 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 ACC as the clearest survival context for DGKB RNA expression.
This table summarizes DGKB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRP for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for DGKB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DGKB shows lower tumor expression in KIRP, BLCA, KICH, UCEC, BRCA and STAD. The KIRP box plot shows higher DGKB RNA expression in normal versus tumor tissue (log2 FC = −0.700, t-test p < 0.001).
This table shows molecular features associated with DGKB in patient tissues and cancer cell lines. In patient samples, DGKB 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, DGKB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
