Q-omics provides the consensus-scored H3-3A profile across patient tissues and cancer cell-line models. H3-3A expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, H3-3A is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, H3-3A RNA expression shows 20,276 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KICH as cancer lineages where H3-3A 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 H3-3A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes H3-3A survival associations across molecular data types. H3-3A RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible H3-3A RNA expression–survival associations across cancer types. High H3-3A expression shows unfavorable associations in ACC, KICH, LIHC and UVM, but favorable associations in COAD and LAML. 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 H3-3A RNA expression.
This table summarizes H3-3A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 2. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for H3-3A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. H3-3A shows lower tumor expression in KICH and higher tumor expression in BLCA, LIHC, BRCA, STAD and CHOL. The KICH box plot shows higher H3-3A RNA expression in normal versus tumor tissue (log2 FC = −1.704, t-test p < 0.001).
This table shows molecular features associated with H3-3A in patient tissues and cancer cell lines. In patient samples, H3-3A shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, H3-3A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BONE and CNS.
