Q-omics provides the consensus-scored H1-3 profile across patient tissues and cancer cell-line models. H1-3 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, H1-3 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, H1-3 protein abundance shows 21,274 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where H1-3 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 H1-3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes H1-3 survival associations across molecular data types. H1-3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) 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 H1-3 RNA expression–survival associations across cancer types. High H1-3 expression shows unfavorable associations in ACC, LGG, THCA, LIHC, KIRP and KIRC. 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 H1-3 RNA expression.
This table summarizes H1-3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for H1-3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. H1-3 shows lower tumor expression in KIRC and KICH and higher tumor expression in HNSC, LUAD, STAD and BRCA. The HNSC box plot shows higher H1-3 RNA expression in tumor versus normal tissue (log2 FC = +0.988, t-test p < 0.001).
This table shows molecular features associated with H1-3 in patient tissues and cancer cell lines. In patient samples, H1-3 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, H1-3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
