PIGY upstream open reading frameGenealiases: NDUFAFQ · PREY
Q-omics provides the consensus-scored PYURF profile across patient tissues and cancer cell-line models. PYURF expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, PYURF is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, PYURF RNA expression shows 17,563 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight MESO, HNSC, and UVM as cancer lineages where PYURF 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 PYURF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PYURF survival associations across molecular data types. PYURF RNA expression shows survival associations in the most cancer types (24), followed by 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 PYURF RNA expression–survival associations across cancer types. High PYURF expression shows unfavorable associations in LGG, STAD, KICH and LUAD, but favorable associations in MESO and BLCA. The MESO Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .009). Together, the overview and detailed table identify MESO as the clearest survival context for PYURF RNA expression.
This table summarizes PYURF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PYURF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PYURF shows lower tumor expression in LUAD and KICH and higher tumor expression in HNSC, CHOL, LIHC and ESCA. The HNSC box plot shows higher PYURF RNA expression in tumor versus normal tissue (log2 FC = +0.514, t-test p = .002).
This table shows molecular features associated with PYURF in patient tissues and cancer cell lines. In patient samples, PYURF 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, PYURF RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BREAST and UPPER_AERODIGESTIVE_TRACT.
