Q-omics provides the consensus-scored PDGFRL profile across patient tissues and cancer cell-line models. PDGFRL 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, PDGFRL is differentially expressed in 10, with the highest sampling consensus in LUAD. Additionally, PDGFRL protein abundance shows 23,236 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, LUAD, and BRCA as cancer lineages where PDGFRL 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 PDGFRL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDGFRL survival associations across molecular data types. PDGFRL RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PDGFRL RNA expression–survival associations across cancer types. High PDGFRL expression shows unfavorable associations in KIRC, KIRP, ACC, STAD, LGG and BLCA. The KIRC 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 KIRC as the clearest survival context for PDGFRL RNA expression.
This table summarizes PDGFRL 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 6. The strongest signals are observed in LUAD for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PDGFRL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDGFRL shows lower tumor expression in UCEC and BRCA and higher tumor expression in LUAD, LIHC, KIRC and LUSC. The LUAD box plot shows higher PDGFRL RNA expression in tumor versus normal tissue (log2 FC = +1.734, t-test p < 0.001).
This table shows molecular features associated with PDGFRL in patient tissues and cancer cell lines. In patient samples, PDGFRL shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, PDGFRL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Lymphoma.
