Q-omics provides the consensus-scored PHF13 profile across patient tissues and cancer cell-line models. PHF13 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PHF13 is differentially expressed in 9, with the highest sampling consensus in LUSC. Additionally, PHF13 RNA expression shows 20,315 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LUSC as cancer lineages where PHF13 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 PHF13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PHF13 survival associations across molecular data types. PHF13 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 PHF13 RNA expression–survival associations across cancer types. High PHF13 expression shows unfavorable associations in ACC, LGG, PAAD, MESO and BLCA, but favorable associations in BRCA. The ACC 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 ACC as the clearest survival context for PHF13 RNA expression.
This table summarizes PHF13 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 1. The strongest signals are observed in LUSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PHF13. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PHF13 shows lower tumor expression in KICH and higher tumor expression in LUSC, HNSC, THCA, COAD and LUAD. The LUSC box plot shows higher PHF13 RNA expression in tumor versus normal tissue (log2 FC = +1.100, t-test p < 0.001).
This table shows molecular features associated with PHF13 in patient tissues and cancer cell lines. In patient samples, PHF13 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, PHF13 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 SOFT_TISSUE and LARGE_INTESTINE.
