Q-omics provides the consensus-scored PHRF1 profile across patient tissues and cancer cell-line models. PHRF1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, PHRF1 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, PHRF1 RNA expression shows 19,483 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, KIRC, and ACC as cancer lineages where PHRF1 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 PHRF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PHRF1 survival associations across molecular data types. PHRF1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (9) 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 PHRF1 RNA expression–survival associations across cancer types. High PHRF1 expression shows unfavorable associations in KICH, LIHC, COAD, KIRC and LUSC, but favorable associations in SCLC. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KICH as the clearest survival context for PHRF1 RNA expression.
This table summarizes PHRF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, 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 PHRF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PHRF1 shows lower tumor expression in THCA and higher tumor expression in KIRC, HNSC, STAD, LIHC and COAD. The KIRC box plot shows higher PHRF1 RNA expression in tumor versus normal tissue (log2 FC = +0.689, t-test p < 0.001).
This table shows molecular features associated with PHRF1 in patient tissues and cancer cell lines. In patient samples, PHRF1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PHRF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
