Q-omics provides the consensus-scored HAGH profile across patient tissues and cancer cell-line models. HAGH expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, HAGH is differentially expressed in 12, with the highest sampling consensus in LUAD. Additionally, HAGH protein abundance shows 32,374 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, LUAD, and GBM as cancer lineages where HAGH 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 HAGH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HAGH survival associations across molecular data types. HAGH RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HAGH RNA expression–survival associations across cancer types. High HAGH expression shows unfavorable associations in UVM, UCS and HNSC, but favorable associations in MESO, LIHC and KIRC. The UVM 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 UVM as the clearest survival context for HAGH RNA expression.
This table summarizes HAGH 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 9. The strongest signals are observed in LUAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HAGH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HAGH shows lower tumor expression in LUAD, LUSC, KIRP, KICH and CHOL and higher tumor expression in BRCA. The LUAD box plot shows higher HAGH RNA expression in normal versus tumor tissue (log2 FC = −0.520, t-test p < 0.001).
This table shows molecular features associated with HAGH in patient tissues and cancer cell lines. In patient samples, HAGH shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, HAGH 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.
