Q-omics provides the consensus-scored H2ACP2 profile across patient tissues and cancer cell-line models. H2ACP2 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, H2ACP2 is differentially expressed in 2, with the highest sampling consensus in HNSC. Additionally, H2ACP2 RNA expression shows 8,077 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where H2ACP2 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 H2ACP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes H2ACP2 survival associations across molecular data types. H2ACP2 RNA expression shows survival associations in the most cancer types (14). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible H2ACP2 RNA expression–survival associations across cancer types. High H2ACP2 expression shows unfavorable associations in ACC, SKCM, MESO, LIHC and SARC, but favorable associations in LUSC. 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 H2ACP2 RNA expression.
This table summarizes H2ACP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for H2ACP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. H2ACP2 shows higher tumor expression in HNSC and LUSC. The HNSC box plot shows higher H2ACP2 RNA expression in tumor versus normal tissue (log2 FC = +0.116, t-test p = .018).
This table shows molecular features associated with H2ACP2 in patient tissues and cancer cell lines. In patient samples, H2ACP2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set.
