Q-omics provides the consensus-scored PFN3 profile across patient tissues and cancer cell-line models. PFN3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in DLBC. Among the 18 cancer types available for tumor–normal comparison, PFN3 is differentially expressed in 7, with the highest sampling consensus in KIRC. Additionally, PFN3 RNA expression shows 6,777 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight DLBC, KIRC, and TGCT as cancer lineages where PFN3 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 PFN3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PFN3 survival associations across molecular data types. PFN3 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PFN3 RNA expression–survival associations across cancer types. High PFN3 expression shows unfavorable associations in DLBC, KICH and ACC, but favorable associations in UCS, BRCA and COAD. The DLBC 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 DLBC as the clearest survival context for PFN3 RNA expression.
This table summarizes PFN3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PFN3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PFN3 shows lower tumor expression in KIRC, KIRP, KICH and CHOL and higher tumor expression in BRCA and BLCA. The KIRC box plot shows higher PFN3 RNA expression in normal versus tumor tissue (log2 FC = −0.368, t-test p < 0.001).
This table shows molecular features associated with PFN3 in patient tissues and cancer cell lines. In patient samples, PFN3 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PFN3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma.
