Q-omics provides the consensus-scored PHF2 profile across patient tissues and cancer cell-line models. PHF2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PHF2 is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, PHF2 protein abundance shows 22,494 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, THCA, and GBM as cancer lineages where PHF2 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 PHF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PHF2 survival associations across molecular data types. PHF2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (4) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PHF2 RNA expression–survival associations across cancer types. High PHF2 expression shows unfavorable associations in ACC, COAD and MESO, but favorable associations in KIRC, BRCA and THYM. 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 PHF2 RNA expression.
This table summarizes PHF2 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 4. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PHF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PHF2 shows lower tumor expression in THCA, LUAD and KICH and higher tumor expression in HNSC, CHOL and LIHC. The THCA box plot shows higher PHF2 RNA expression in normal versus tumor tissue (log2 FC = −0.561, t-test p = .001).
This table shows molecular features associated with PHF2 in patient tissues and cancer cell lines. In patient samples, PHF2 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, PHF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
