Q-omics provides the consensus-scored PDGFA profile across patient tissues and cancer cell-line models. PDGFA expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PDGFA is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, PDGFA RNA expression shows 18,725 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and HNSC as cancer lineages where PDGFA 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 PDGFA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDGFA survival associations across molecular data types. PDGFA RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) and 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 PDGFA RNA expression–survival associations across cancer types. High PDGFA expression shows unfavorable associations in UVM, HNSC, MESO, LGG, ACC and BLCA. 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 PDGFA RNA expression.
This table summarizes PDGFA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PDGFA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDGFA shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRC, THCA, LIHC and KIRP. The HNSC box plot shows higher PDGFA RNA expression in tumor versus normal tissue (log2 FC = +1.898, t-test p < 0.001).
This table shows molecular features associated with PDGFA in patient tissues and cancer cell lines. In patient samples, PDGFA 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, PDGFA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
