Q-omics provides the consensus-scored SYS1-DBNDD2 profile across patient tissues and cancer cell-line models. SYS1-DBNDD2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SYS1-DBNDD2 is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, SYS1-DBNDD2 RNA expression shows 18,851 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UVM, THCA, and THYM as cancer lineages where SYS1-DBNDD2 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 SYS1-DBNDD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYS1-DBNDD2 survival associations across molecular data types. SYS1-DBNDD2 RNA expression shows survival associations in the most cancer types (20). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SYS1-DBNDD2 RNA expression–survival associations across cancer types. High SYS1-DBNDD2 expression shows unfavorable associations in UVM, BLCA, LUSC and UCEC, but favorable associations in PAAD and CHOL. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .011). Together, the overview and detailed table identify UVM as the clearest survival context for SYS1-DBNDD2 RNA expression.
This table summarizes SYS1-DBNDD2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SYS1-DBNDD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYS1-DBNDD2 shows lower tumor expression in THCA, KICH and LUAD and higher tumor expression in KIRC, BRCA and LIHC. The THCA box plot shows higher SYS1-DBNDD2 RNA expression in normal versus tumor tissue (log2 FC = −0.667, t-test p < 0.001).
This table shows molecular features associated with SYS1-DBNDD2 in patient tissues and cancer cell lines. In patient samples, SYS1-DBNDD2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SYS1-DBNDD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma.
