Q-omics provides the consensus-scored DUSP10 profile across patient tissues and cancer cell-line models. DUSP10 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, DUSP10 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, DUSP10 RNA expression shows 17,353 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SCLC, KIRC, and UVM as cancer lineages where DUSP10 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 DUSP10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DUSP10 survival associations across molecular data types. DUSP10 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DUSP10 RNA expression–survival associations across cancer types. High DUSP10 expression shows unfavorable associations in THCA, UVM, LGG and KIRC, but favorable associations in SCLC and LIHC. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify SCLC as the clearest survival context for DUSP10 RNA expression.
This table summarizes DUSP10 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 1. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for DUSP10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DUSP10 shows lower tumor expression in LIHC and higher tumor expression in KIRC, COAD, HNSC, KIRP and STAD. The KIRC box plot shows higher DUSP10 RNA expression in tumor versus normal tissue (log2 FC = +1.362, t-test p < 0.001).
This table shows molecular features associated with DUSP10 in patient tissues and cancer cell lines. In patient samples, DUSP10 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, DUSP10 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 BONE.
