Q-omics provides the consensus-scored PRAF2 profile across patient tissues and cancer cell-line models. PRAF2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PRAF2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PRAF2 protein abundance shows 16,372 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRP, HNSC, and PDAC as cancer lineages where PRAF2 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 PRAF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRAF2 survival associations across molecular data types. PRAF2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRAF2 RNA expression–survival associations across cancer types. High PRAF2 expression shows unfavorable associations in KIRP, MESO, LIHC, UVM and LGG, but favorable associations in SCLC. The KIRP 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 KIRP as the clearest survival context for PRAF2 RNA expression.
This table summarizes PRAF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PRAF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRAF2 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, THCA, COAD and BRCA. The HNSC box plot shows higher PRAF2 RNA expression in tumor versus normal tissue (log2 FC = +1.107, t-test p < 0.001).
This table shows molecular features associated with PRAF2 in patient tissues and cancer cell lines. In patient samples, PRAF2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PRAF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BLOOD_Leukemia.
