Q-omics provides the consensus-scored PHC1 profile across patient tissues and cancer cell-line models. PHC1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, PHC1 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, PHC1 RNA expression shows 21,005 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight MESO, KICH, and THYM as cancer lineages where PHC1 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 PHC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PHC1 survival associations across molecular data types. PHC1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PHC1 RNA expression–survival associations across cancer types. High PHC1 expression shows unfavorable associations in MESO, LUSC, ACC and THCA, but favorable associations in UCS and HNSC. The MESO 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 MESO as the clearest survival context for PHC1 RNA expression.
This table summarizes PHC1 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 6. The strongest signals are observed in KICH for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PHC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PHC1 shows lower tumor expression in KICH, THCA, LUAD and BRCA and higher tumor expression in CHOL and LIHC. The KICH box plot shows higher PHC1 RNA expression in normal versus tumor tissue (log2 FC = −1.595, t-test p < 0.001).
This table shows molecular features associated with PHC1 in patient tissues and cancer cell lines. In patient samples, PHC1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PHC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
