Q-omics provides the consensus-scored PHF23 profile across patient tissues and cancer cell-line models. PHF23 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PHF23 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, PHF23 protein abundance shows 20,284 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where PHF23 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 PHF23 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PHF23 survival associations across molecular data types. PHF23 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PHF23 RNA expression–survival associations across cancer types. High PHF23 expression shows unfavorable associations in ACC, SKCM, LUAD and UCS, but favorable associations in BRCA and SCLC. 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 PHF23 RNA expression.
This table summarizes PHF23 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PHF23. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PHF23 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, LUAD, UCEC and BRCA. The HNSC box plot shows higher PHF23 RNA expression in tumor versus normal tissue (log2 FC = +0.728, t-test p < 0.001).
This table shows molecular features associated with PHF23 in patient tissues and cancer cell lines. In patient samples, PHF23 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, PHF23 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Lymphoma.
