Q-omics provides the consensus-scored PHKG1 profile across patient tissues and cancer cell-line models. PHKG1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, PHKG1 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, PHKG1 RNA expression shows 17,856 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight PAAD, KIRC, and UVM as cancer lineages where PHKG1 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 PHKG1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PHKG1 survival associations across molecular data types. PHKG1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PHKG1 RNA expression–survival associations across cancer types. High PHKG1 expression shows unfavorable associations in KIRC, KICH, MESO, CESC and UVM, but favorable associations in PAAD. The PAAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify PAAD as the clearest survival context for PHKG1 RNA expression.
This table summarizes PHKG1 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 3. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PHKG1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PHKG1 shows lower tumor expression in BLCA, BRCA, HNSC and THCA and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher PHKG1 RNA expression in tumor versus normal tissue (log2 FC = +0.533, t-test p < 0.001).
This table shows molecular features associated with PHKG1 in patient tissues and cancer cell lines. In patient samples, PHKG1 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, PHKG1 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 BLOOD_Myeloma and BLOOD_Leukemia.
