Q-omics provides the consensus-scored DAPL1 profile across patient tissues and cancer cell-line models. DAPL1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, DAPL1 is differentially expressed in 10, with the highest sampling consensus in LUSC. Additionally, DAPL1 RNA expression shows 11,358 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight UCS, LUSC, and ESCA as cancer lineages where DAPL1 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 DAPL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DAPL1 survival associations across molecular data types. DAPL1 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (2) 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 DAPL1 RNA expression–survival associations across cancer types. High DAPL1 expression shows unfavorable associations in UCS and SKCM, but favorable associations in BRCA, UVM, MESO and LGG. The UCS Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify UCS as the clearest survival context for DAPL1 RNA expression.
This table summarizes DAPL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in LUSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for DAPL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DAPL1 shows lower tumor expression in HNSC, KIRP, KIRC and BRCA and higher tumor expression in LUSC and COAD. The LUSC box plot shows higher DAPL1 RNA expression in tumor versus normal tissue (log2 FC = +5.192, t-test p < 0.001).
This table shows molecular features associated with DAPL1 in patient tissues and cancer cell lines. In patient samples, DAPL1 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, DAPL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in CNS and BONE.
