Q-omics provides the consensus-scored PDGFB profile across patient tissues and cancer cell-line models. PDGFB expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PDGFB is differentially expressed in 15, with the highest sampling consensus in KICH. Additionally, PDGFB RNA expression shows 17,986 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, KICH, and THYM as cancer lineages where PDGFB 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 PDGFB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDGFB survival associations across molecular data types. PDGFB RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) 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 PDGFB RNA expression–survival associations across cancer types. High PDGFB expression shows unfavorable associations in MESO, UVM, LUAD, BLCA and HNSC, but favorable associations in KIRC. 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 PDGFB RNA expression.
This table summarizes PDGFB 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 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PDGFB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDGFB shows lower tumor expression in KICH and KIRP and higher tumor expression in HNSC, COAD, STAD and LIHC. The KICH box plot shows higher PDGFB RNA expression in normal versus tumor tissue (log2 FC = −2.504, t-test p < 0.001).
This table shows molecular features associated with PDGFB in patient tissues and cancer cell lines. In patient samples, PDGFB 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, PDGFB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LIVER and LARGE_INTESTINE.
