Q-omics provides the consensus-scored DSCR9 profile across patient tissues and cancer cell-line models. DSCR9 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, DSCR9 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, DSCR9 RNA expression shows 17,177 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, and UVM as cancer lineages where DSCR9 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 DSCR9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DSCR9 survival associations across molecular data types. DSCR9 RNA expression shows survival associations in the most cancer types (28). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DSCR9 RNA expression–survival associations across cancer types. High DSCR9 expression shows unfavorable associations in KIRC, ACC, LIHC, BRCA and UVM, but favorable associations in PAAD. The KIRC 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 KIRC as the clearest survival context for DSCR9 RNA expression.
This table summarizes DSCR9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for DSCR9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DSCR9 shows higher tumor expression in KIRC, BLCA, LIHC, HNSC, COAD and UCEC. The KIRC box plot shows higher DSCR9 RNA expression in tumor versus normal tissue (log2 FC = +0.143, t-test p < 0.001).
This table shows molecular features associated with DSCR9 in patient tissues and cancer cell lines. In patient samples, DSCR9 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, DSCR9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD.
