Q-omics provides the consensus-scored DNASE1L2 profile across patient tissues and cancer cell-line models. DNASE1L2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, DNASE1L2 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, DNASE1L2 RNA expression shows 17,208 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, COAD, and ACC as cancer lineages where DNASE1L2 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 DNASE1L2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DNASE1L2 survival associations across molecular data types. DNASE1L2 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DNASE1L2 RNA expression–survival associations across cancer types. High DNASE1L2 expression shows unfavorable associations in MESO, KIRC, KIRP, ACC and UVM, but favorable associations in SKCM. The MESO 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 MESO as the clearest survival context for DNASE1L2 RNA expression.
This table summarizes DNASE1L2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for DNASE1L2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DNASE1L2 shows higher tumor expression in COAD, LIHC, STAD, UCEC, BLCA and LUAD. The COAD box plot shows higher DNASE1L2 RNA expression in tumor versus normal tissue (log2 FC = +1.304, t-test p < 0.001).
This table shows molecular features associated with DNASE1L2 in patient tissues and cancer cell lines. In patient samples, DNASE1L2 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, DNASE1L2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
