Q-omics provides the consensus-scored DNASE1L3 profile across patient tissues and cancer cell-line models. DNASE1L3 expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DNASE1L3 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, DNASE1L3 RNA expression shows 15,807 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight KIRC, COAD, and CCRCC as cancer lineages where DNASE1L3 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 DNASE1L3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DNASE1L3 survival associations across molecular data types. DNASE1L3 RNA expression shows survival associations in the most cancer types (30), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DNASE1L3 RNA expression–survival associations across cancer types. High DNASE1L3 expression shows unfavorable associations in UVM and BLCA, but favorable associations in KIRC, LIHC, ACC and KICH. 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 DNASE1L3 RNA expression.
This table summarizes DNASE1L3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for DNASE1L3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DNASE1L3 shows lower tumor expression in COAD, KIRC, BLCA, KICH, KIRP and HNSC. The COAD box plot shows higher DNASE1L3 RNA expression in normal versus tumor tissue (log2 FC = −3.610, t-test p < 0.001).
This table shows molecular features associated with DNASE1L3 in patient tissues and cancer cell lines. In patient samples, DNASE1L3 shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, DNASE1L3 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 KIDNEY and BLOOD_Leukemia.
