Q-omics provides the consensus-scored DPP10 profile across patient tissues and cancer cell-line models. DPP10 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DPP10 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, DPP10 RNA expression shows 15,897 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where DPP10 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 DPP10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DPP10 survival associations across molecular data types. DPP10 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (10) 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 DPP10 RNA expression–survival associations across cancer types. High DPP10 expression shows unfavorable associations in ACC, SCLC and STAD, but favorable associations in COAD, LGG and ESCA. 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 DPP10 RNA expression.
This table summarizes DPP10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for DPP10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DPP10 shows lower tumor expression in KIRC, COAD and STAD and higher tumor expression in UCEC, LUAD and BRCA. The KIRC box plot shows higher DPP10 RNA expression in normal versus tumor tissue (log2 FC = −0.478, t-test p < 0.001).
This table shows molecular features associated with DPP10 in patient tissues and cancer cell lines. In patient samples, DPP10 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, DPP10 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 SOFT_TISSUE and BLOOD_Leukemia.
