Q-omics provides the consensus-scored HIRA profile across patient tissues and cancer cell-line models. HIRA 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, HIRA is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, HIRA protein abundance shows 22,310 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, THCA, and LSCC as cancer lineages where HIRA 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 HIRA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HIRA survival associations across molecular data types. HIRA RNA expression shows survival associations in the most cancer types (26), followed by mutation status (10) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HIRA RNA expression–survival associations across cancer types. High HIRA expression shows unfavorable associations in ACC, LIHC and KICH, but favorable associations in SCLC, KIRP and READ. 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 HIRA RNA expression.
This table summarizes HIRA 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 8. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for HIRA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HIRA shows lower tumor expression in THCA and KIRP and higher tumor expression in STAD, COAD, HNSC and LIHC. The THCA box plot shows higher HIRA RNA expression in normal versus tumor tissue (log2 FC = −1.797, t-test p < 0.001).
This table shows molecular features associated with HIRA in patient tissues and cancer cell lines. In patient samples, HIRA 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, HIRA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
