Q-omics provides the consensus-scored CDS2 profile across patient tissues and cancer cell-line models. CDS2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CDS2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, CDS2 protein abundance shows 29,690 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where CDS2 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 CDS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CDS2 survival associations across molecular data types. CDS2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CDS2 RNA expression–survival associations across cancer types. High CDS2 expression shows unfavorable associations in SKCM, LUSC and UVM, but favorable associations in KIRC, LGG and BRCA. 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 CDS2 RNA expression.
This table summarizes CDS2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 9. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CDS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CDS2 shows lower tumor expression in LUAD, THCA, UCEC and BLCA and higher tumor expression in HNSC and LIHC. The HNSC box plot shows higher CDS2 RNA expression in tumor versus normal tissue (log2 FC = +0.860, t-test p < 0.001).
This table shows molecular features associated with CDS2 in patient tissues and cancer cell lines. In patient samples, CDS2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CDS2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SKIN.
