Q-omics provides the consensus-scored PCBD1 profile across patient tissues and cancer cell-line models. PCBD1 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, PCBD1 is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, PCBD1 RNA expression shows 16,402 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight CESC, COAD, and ACC as cancer lineages where PCBD1 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 PCBD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCBD1 survival associations across molecular data types. PCBD1 RNA expression shows survival associations in the most cancer types (29), followed by mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCBD1 RNA expression–survival associations across cancer types. High PCBD1 expression shows unfavorable associations in CESC, UVM, LGG, KIRP and HNSC, but favorable associations in SARC. The CESC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify CESC as the clearest survival context for PCBD1 RNA expression.
This table summarizes PCBD1 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 COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PCBD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCBD1 shows lower tumor expression in KICH, KIRC and LUSC and higher tumor expression in COAD, BRCA and STAD. The COAD box plot shows higher PCBD1 RNA expression in tumor versus normal tissue (log2 FC = +0.983, t-test p < 0.001).
This table shows molecular features associated with PCBD1 in patient tissues and cancer cell lines. In patient samples, PCBD1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PCBD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
