Q-omics provides the consensus-scored ZBED3 profile across patient tissues and cancer cell-line models. ZBED3 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ZBED3 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, ZBED3 RNA expression shows 20,542 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, THCA, and THYM as cancer lineages where ZBED3 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 ZBED3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZBED3 survival associations across molecular data types. ZBED3 RNA expression shows survival associations in the most cancer types (26), followed by mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZBED3 RNA expression–survival associations across cancer types. High ZBED3 expression shows unfavorable associations in KICH, but favorable associations in KIRC, READ, HNSC, UVM and UCS. 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 ZBED3 RNA expression.
This table summarizes ZBED3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ZBED3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZBED3 shows lower tumor expression in THCA, BLCA, LUSC and LUAD and higher tumor expression in COAD and LIHC. The THCA box plot shows higher ZBED3 RNA expression in normal versus tumor tissue (log2 FC = −0.865, t-test p < 0.001).
This table shows molecular features associated with ZBED3 in patient tissues and cancer cell lines. In patient samples, ZBED3 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, ZBED3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
