Q-omics provides the consensus-scored PCBD2 profile across patient tissues and cancer cell-line models. PCBD2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PCBD2 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, PCBD2 RNA expression shows 20,619 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and THCA as cancer lineages where PCBD2 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 PCBD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCBD2 survival associations across molecular data types. PCBD2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCBD2 RNA expression–survival associations across cancer types. High PCBD2 expression shows unfavorable associations in UVM and LGG, but favorable associations in READ, KIRC, KIRP and LUSC. The UVM 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 UVM as the clearest survival context for PCBD2 RNA expression.
This table summarizes PCBD2 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 10. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PCBD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCBD2 shows lower tumor expression in THCA and higher tumor expression in READ, LIHC, KIRC, COAD and BRCA. The THCA box plot shows higher PCBD2 RNA expression in normal versus tumor tissue (log2 FC = −0.667, t-test p < 0.001).
This table shows molecular features associated with PCBD2 in patient tissues and cancer cell lines. In patient samples, PCBD2 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, PCBD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
