Q-omics provides the consensus-scored H2AP profile across patient tissues and cancer cell-line models. H2AP expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, H2AP is differentially expressed in 4, with the highest sampling consensus in HNSC. Additionally, H2AP RNA expression shows 7,035 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where H2AP 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 H2AP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes H2AP survival associations across molecular data types. H2AP RNA expression shows survival associations in the most cancer types (11), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible H2AP RNA expression–survival associations across cancer types. High H2AP expression shows unfavorable associations in KIRC, LUSC, STAD, LUAD and LGG, but favorable associations in ACC. The KIRC 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 KIRC as the clearest survival context for H2AP RNA expression.
This table summarizes H2AP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 4. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for H2AP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. H2AP shows lower tumor expression in KIRC and higher tumor expression in HNSC, BRCA and LUSC. The HNSC box plot shows higher H2AP RNA expression in tumor versus normal tissue (log2 FC = +0.122, t-test p = .023).
This table shows molecular features associated with H2AP in patient tissues and cancer cell lines. In patient samples, H2AP 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, H2AP 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 BLOOD_Leukemia and CNS.
