Q-omics provides the consensus-scored PFDN1 profile across patient tissues and cancer cell-line models. PFDN1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PFDN1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, PFDN1 RNA expression shows 18,286 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KIRC, and UVM as cancer lineages where PFDN1 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 PFDN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PFDN1 survival associations across molecular data types. PFDN1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1) 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 PFDN1 RNA expression–survival associations across cancer types. High PFDN1 expression shows unfavorable associations in HNSC, LUAD, LIHC, KICH, UVM and SCLC. The HNSC 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 HNSC as the clearest survival context for PFDN1 RNA expression.
This table summarizes PFDN1 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PFDN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PFDN1 shows lower tumor expression in LUSC and higher tumor expression in KIRC, HNSC, LIHC, KIRP and CHOL. The KIRC box plot shows higher PFDN1 RNA expression in tumor versus normal tissue (log2 FC = +0.642, t-test p < 0.001).
This table shows molecular features associated with PFDN1 in patient tissues and cancer cell lines. In patient samples, PFDN1 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, PFDN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
