Q-omics provides the consensus-scored PFKP profile across patient tissues and cancer cell-line models. PFKP expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PFKP is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, PFKP protein abundance shows 27,544 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where PFKP 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 PFKP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PFKP survival associations across molecular data types. PFKP RNA expression shows survival associations in the most cancer types (27), followed by mutation status (8) 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 PFKP RNA expression–survival associations across cancer types. High PFKP expression shows unfavorable associations in UVM, LUAD, HNSC, ACC and CESC, but favorable associations in KIRC. The UVM 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 UVM as the clearest survival context for PFKP RNA expression.
This table summarizes PFKP 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PFKP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PFKP shows higher tumor expression in KIRC, LUAD, KIRP, HNSC, COAD and LIHC. The KIRC box plot shows higher PFKP RNA expression in tumor versus normal tissue (log2 FC = +2.536, t-test p < 0.001).
This table shows molecular features associated with PFKP in patient tissues and cancer cell lines. In patient samples, PFKP shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PFKP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
