Q-omics provides the consensus-scored DERA profile across patient tissues and cancer cell-line models. DERA expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, DERA is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, DERA protein abundance shows 28,693 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight PAAD, HNSC, and GBM as cancer lineages where DERA 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 DERA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DERA survival associations across molecular data types. DERA RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DERA RNA expression–survival associations across cancer types. High DERA expression shows unfavorable associations in PAAD, HNSC, MESO, LUAD and SKCM, but favorable associations in THCA. The PAAD 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 PAAD as the clearest survival context for DERA RNA expression.
This table summarizes DERA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for DERA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DERA shows lower tumor expression in KICH and READ and higher tumor expression in HNSC, KIRC, BLCA and LUSC. The HNSC box plot shows higher DERA RNA expression in tumor versus normal tissue (log2 FC = +1.186, t-test p < 0.001).
This table shows molecular features associated with DERA in patient tissues and cancer cell lines. In patient samples, DERA 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, DERA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
