Q-omics provides the consensus-scored DOC2B profile across patient tissues and cancer cell-line models. DOC2B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DOC2B is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, DOC2B RNA expression shows 17,980 significant gene co-expression associations, with the highest sampling consensus in DLBC. Together, these results highlight ACC, KIRC, and DLBC as cancer lineages where DOC2B 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 DOC2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DOC2B survival associations across molecular data types. DOC2B RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DOC2B RNA expression–survival associations across cancer types. High DOC2B expression shows unfavorable associations in ACC and KIRP, but favorable associations in BRCA, HNSC, KIRC and OV. The ACC 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 ACC as the clearest survival context for DOC2B RNA expression.
This table summarizes DOC2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for DOC2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DOC2B shows lower tumor expression in KIRC, KICH, BLCA, HNSC, THCA and KIRP. The KIRC box plot shows higher DOC2B RNA expression in normal versus tumor tissue (log2 FC = −1.367, t-test p < 0.001).
This table shows molecular features associated with DOC2B in patient tissues and cancer cell lines. In patient samples, DOC2B shows the broadest associations at the RNA and protein expression levels, with DLBC recurring as the lineage with the largest associated feature set. In cancer cell lines, DOC2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma.
