Q-omics provides the consensus-scored PCGF5 profile across patient tissues and cancer cell-line models. PCGF5 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, PCGF5 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, PCGF5 protein abundance shows 21,047 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, THCA, and PDAC as cancer lineages where PCGF5 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 PCGF5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCGF5 survival associations across molecular data types. PCGF5 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCGF5 RNA expression–survival associations across cancer types. High PCGF5 expression shows unfavorable associations in ACC, but favorable associations in KIRC, MESO, SKCM, SCLC 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 PCGF5 RNA expression.
This table summarizes PCGF5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PCGF5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCGF5 shows lower tumor expression in THCA, LUSC, BLCA, KICH and READ and higher tumor expression in LIHC. The THCA box plot shows higher PCGF5 RNA expression in normal versus tumor tissue (log2 FC = −1.211, t-test p < 0.001).
This table shows molecular features associated with PCGF5 in patient tissues and cancer cell lines. In patient samples, PCGF5 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PCGF5 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 LUNG_SCLC.
