Q-omics provides the consensus-scored APH1B profile across patient tissues and cancer cell-line models. APH1B expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, APH1B is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, APH1B protein abundance shows 23,853 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where APH1B 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 APH1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APH1B survival associations across molecular data types. APH1B RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) 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 APH1B RNA expression–survival associations across cancer types. High APH1B expression shows unfavorable associations in STAD and LUSC, but favorable associations in ACC, KIRC, KIRP and BRCA. The ACC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for APH1B RNA expression.
This table summarizes APH1B 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 6. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for APH1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APH1B shows lower tumor expression in LUAD, KIRP, LUSC, UCEC and KIRC and higher tumor expression in HNSC. The HNSC box plot shows higher APH1B RNA expression in tumor versus normal tissue (log2 FC = +0.797, t-test p < 0.001).
This table shows molecular features associated with APH1B in patient tissues and cancer cell lines. In patient samples, APH1B shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, APH1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
