Q-omics provides the consensus-scored DCP1A profile across patient tissues and cancer cell-line models. DCP1A expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DCP1A is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, DCP1A RNA expression shows 20,469 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, LIHC, and ACC as cancer lineages where DCP1A 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 DCP1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DCP1A survival associations across molecular data types. DCP1A RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DCP1A RNA expression–survival associations across cancer types. High DCP1A expression shows unfavorable associations in LIHC and ACC, but favorable associations in KIRC, READ, UCS and BRCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for DCP1A RNA expression.
This table summarizes DCP1A 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 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for DCP1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DCP1A shows lower tumor expression in THCA, LUSC and BRCA and higher tumor expression in LIHC, STAD and COAD. The LIHC box plot shows higher DCP1A RNA expression in tumor versus normal tissue (log2 FC = +0.690, t-test p < 0.001).
This table shows molecular features associated with DCP1A in patient tissues and cancer cell lines. In patient samples, DCP1A shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, DCP1A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Lymphoma.
